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Executive Functions and Writing
Executive Functions and Writing Edited by
Teresa Limpo
Assistant Professor, Faculty of Psychology and Educational Sciences, University of Porto, Portugal
Thierry Olive
Senior Researcher at the Centre National de la Recherche Scientifique (CNRS) and Université de Poitiers, France
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3 Great Clarendon Street, Oxford, OX2 6DP, United Kingdom Oxford University Press is a department of the University of Oxford. It furthers the University’s objective of excellence in research, scholarship, and education by publishing worldwide. Oxford is a registered trade mark of Oxford University Press in the UK and in certain other countries © Oxford University Press 2021 The moral rights of the authors have been asserted First Edition published in 2021 Impression: 1 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without the prior permission in writing of Oxford University Press, or as expressly permitted by law, by licence or under terms agreed with the appropriate reprographics rights organization. Enquiries concerning reproduction outside the scope of the above should be sent to the Rights Department, Oxford University Press, at the address above You must not circulate this work in any other form and you must impose this same condition on any acquirer Published in the United States of America by Oxford University Press 198 Madison Avenue, New York, NY 10016, United States of America British Library Cataloguing in Publication Data Data available Library of Congress Control Number: 2020952978 ISBN 978–0–19–886356–4 DOI: 10.1093/oso/9780198863564.001.0001 Printed and bound in the UK by TJ Books Limited Oxford University Press makes no representation, express or implied, that the drug dosages in this book are correct. Readers must therefore always check the product information and clinical procedures with the most up-to-date published product information and data sheets provided by the manufacturers and the most recent codes of conduct and safety regulations. The authors and the publishers do not accept responsibility or legal liability for any errors in the text or for the misuse or misapplication of material in this work. Except where otherwise stated, drug dosages and recommendations are for the non-pregnant adult who is not breast-feeding Links to third party websites are provided by Oxford in good faith and for information only. Oxford disclaims any responsibility for the materials contained in any third party website referenced in this work.
Contents Abbreviations Contributors
vii ix
I. INTRODUCTION
1. Why Should We Be Looking at the Relationship Between Executive Functions and Writing?
3
Teresa Limpo and Thierry Olive
II. MODELS OF EXECUTIVE FUNCTIONS AND WRITING
2. Current Issues in the Conceptualization and Measurement of Executive Function Skills
17
Michael Willoughby and Kesha Hudson
3. Executive Control and the Writer(s)-Within-Community Model
38
Steve Graham
III. METHODS FOR ASSESSING EXECUTIVE FUNCTIONS AND WRITING
4. Assessment of Executive Functions in Children
79
Helen St Clair-Thompson and Yunhong Wen
5. Capturing the Challenges in Assessing Writing: Development and Writing Dimensions
103
Julie E. Dockrell and Vincent Connelly
IV. EXECUTIVE FUNCTIONS AND WRITING ACROSS THE LIFESPAN
6. Executive Functions and Writing Skills in Children and Adolescents: Developmental Associations and Dissociations
139
Stephen R. Hooper, Lara Costa, Edmund Fernandez, Alexandra Barker, Courtney Valdes, Stephanie Catlett, and Melissa Green
7. How Do Executive Functions Issues Affect Writing in Students with Neurodevelopmental Disorders? Marisa Filipe
160
vi Contents
8. Promoting Executive Functions During the Writing Process
181
Linda H. Mason and Stacie Brady
9. Executive Functions in Skilled Writers
207
Thierry Olive
10. The Ageing Writer
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São Luís Castro and Regina Abreu
V. CONCLUSIONS AND FUTURE DIRECTIONS
11. Broader Approaches to Defining, Assessing, and Strengthening Executive Control in Writing
257
George McCloskey
12. Executive Functions: Rediscovering Their Roots with the Help of Writing
276
George Georgiou
13. The Future Role of Executive Functions in Education: From Acquisition to Knowledge and Effective Application
288
Sam Goldstein and Keith D. McGoldrick
Index
297
Abbreviations CBGO CCC CD COPS CPA DIEW EC EF FPCEUP HMEC LTM MCI MEFS PENS PND SALT SIM SPAG SRSD SST SWF TAACO TAALES TTR WAM WCST WM WOLD WWC
computer-based graphic organizers Cognitive Complexity and Control conduct disorder Capitalization, Organization, Punctuation, Spelling cascading production analysis direct and indirect effects model of writing executive control executive function Faculty of Psychology and Education Sciences at University of Porto Holarchical Model of Executive Control long-term memory mild cognitive impairment McCloskey Executive Functions Scale Picks, Explores, Noted, and Subject percentage of non-overlapping data Systematic Analysis of Language Transcripts Strategy Instruction Model Spelling, Punctuation and Grammar self-regulated strategy development Stop Signal Task Sentence Writing Fluency the automatic analysis of text cohesion the automatic analysis of lexical sophistication Type Token Ratios Writing Assessment Measure Wisconsin Card Sorting Task working memory Wechsler Objective Language Dimensions Writing within Communities
Contributors Regina Abreu Research Associate, Centre for Psychology at University of Porto, Portugal Alexandra Barker Research Associate, Department of Allied Health Sciences, CB# 7120, School of Medicine, University of North Carolina- Chapel Hill, USA Stacie Brady Doctoral Student, Special Education, George Mason University, USA São Luís Castro Full Professor, Faculty of Psychology and Educational Sciences, University of Porto, Portugal Stephanie Catlett Research Associate, Department of Allied Health Sciences, CB# 7120, School of Medicine, University of North Carolina-Chapel Hill, USA Vincent Connelly Professor of Psychology, Department of Psychology, Health and Professional Development, Faculty of Health and Life Sciences, Oxford Brookes University, UK Lara Costa Research Project Director, Department of Allied Health Sciences, CB# 7120, School of Medicine, University of North Carolina-Chapel Hill, USA Julie E. Dockrell Professor of Psychology and Special Needs, Psychology and Human Development, UCL Institute of Education, UK
Edmund Fernandez Research Associate, Department of Allied Health Sciences, CB# 7120, School of Medicine, University of North Carolina-Chapel Hill, USA Marisa Filipe Assistant Professor, Digital Human- Environment Interaction Lab—HEI-Lab, Lusófona University, Portugal George Georgiou Professor, Director of the J.P. Das Centre on Developmental and Learning Disabilities, Department of Educational Psychology, University of Alberta, Canada Sam Goldstein Adjunct Assistant Professor, Department of Psychiatry, University of Utah School of Medicine; Clinical Director, Neurology, Learning and Behavior Center, USA Steve Graham Warner Professor of Educational Innovation and Leadership, Mary Lou Fulton Teachers College, Arizona State University, USA Melissa Green Research Associate, Department of Allied Health Sciences, CB# 7120, School of Medicine, University of North Carolina-Chapel Hill, USA Stephen R. Hooper Associate Dean of Medicine; Chair, Department of Allied Health Sciences, CB# 7120, School of Medicine, University of North Carolina-Chapel Hill, USA
x Contributors Kesha Hudson Post-Doctoral Fellow, Education and Workforce Development, RTI International, Research Triangle Park, NC, USA
Thierry Olive Senior Researcher at the Centre National de la Recherche Scientifique (CNRS) and Université de Poitiers, France
Teresa Limpo Assistant Professor, Faculty of Psychology and Educational Sciences, University of Porto, Portugal
Helen St Clair-Thompson Senior Lecturer in Psychology, School of Psychology, Newcastle University, UK
Linda H. Mason Professor and Endowed Director of the Helen A. Kellar Institute for Human disAbility, College of Education and Human Development, George Mason University, USA George McCloskey Professor, School of Professional and Applied Psychology, Director of School Psychology Research, Philadelphia College of Osteopathic Medicine, USA Keith D. McGoldrick Neuropsychologist, Beehive Neuropsychology, USA
Courtney Valdes Research Associate, Department of Allied Health Sciences, CB# 7120, School of Medicine, University of North Carolina-Chapel Hill, USA Yunhong Wen PhD Student in Psychology, School of Psychology, Newcastle University, UK Michael Willoughby Fellow, Education, Education and Workforce Development, RTI International, Research Triangle Park, NC, USA
I
INTRODUCTION
1 Why Should We Be Looking at the Relationship Between Executive Functions and Writing? Teresa Limpo and Thierry Olive
Introduction In 1980, John Hayes and Linda Flower introduced the first cognitive model of written composition (Hayes & Flower, 1980). This model was inspired by mainstream concepts of cognition at the time: writing was conceived as an ill-defined, goal-oriented problem, with cognitive operations working at several levels of mental representations under the supervision of a monitor. Still today, the influence of this model in shaping the development of writing research is extremely visible. The skeleton of this seminal model can be found at the root of the many cognitive models currently available to explain the process of producing writing (Berninger & Winn, 2006; Graham, 2018a; Kellogg, 1996; Kim & Schatschneider, 2017). One of the reasons for its remarkable and long-standing impact was the identification of the major cognitive processes involved in writing a text. From thinking-aloud protocols analysis, Hayes and Flower (1980) inferred three writing processes, namely, planning, translating, and revising. More important for the present volume, authors claimed that these processes recursively interacted during skilled writing under the control of a ‘monitor’ responsible for deciding which process to use and at which moment of composition as well as how to enact that process. Though not recognized explicitly, the functions ascribed to this ‘monitor’ match some of those currently gather under the umbrella term ‘executive functions’. Sixteen years later, John Hayes provided the research community with an updated version of the original model, in which he incorporated several key modifications (Hayes, 1996). Among them was the exchange of the term ‘monitor’ by ‘working memory’. Later in 2012, Hayes abandoned the idea that planning and revising are specific writing processes and conceived them as specialized writing activities that engage other writing processes (Hayes, 2012). He posits that ‘creating a written plan not only involves setting goals, generating ideas, and evaluating them but also necessarily involves translation and transcription to produce a written product’, and Teresa Limpo and Thierry Olive, Why Should We Be Looking at the Relationship Between Executive Functions and Writing? In: Executive Functions and Writing. Edited by: Teresa Limpo and Thierry Olive, Oxford University Press. © Oxford University Press 2021. DOI: 10.1093/oso/9780198863564.003.0001
4 1. Relationship Between EFs and Writing that ‘revising . . . involves planning a solution to the problem (in written form or not), translating that solution into language, and transcribing that language into new text to replace the old text’ (p. 376). As Hayes underlined, this change was aimed at further understanding writing as the result of interactions among writing subprocesses. Like in the 1996 model, working memory was assumed a central role, as it was responsible for coordinating all the cognitive and motivational processes involved in writing. Since then, the inclusion of top-down mental processes responsible for managing the writer’s cognition, affects, and/or behaviours during writing has become the norm in cognitive writing models, despite the lack of agreement on how to label those executive processes (Berninger & Winn, 2006; Graham, 2018a; Kellogg, 1996; Kim & Schatschneider, 2017). This lack of agreement is not surprising, as it mimics the absence of a consensual definition of executive functions (see Chapter 2 of this volume). There is however an overall agreement that executive functions involve a group of cognitive processes that allow individuals to successfully engage in independent, purposeful, and self-directed behaviours (Lezac, Howieson, Bieglerr, & Tranel, 2012). These executive processes are called for in tasks where success depends upon an individual being capable to sustain attention, manipulate ideas, resist to temptations, think before acting, and/or deal with unanticipated challenges (Diamond, 2013). Though executive functions may not always be needed to succeed or achieve optimal performance (e.g. in close-skilled sports, where turning the ‘automatic pilot’ on may be advisable), this does not seem to be the case of such a complex and cognitively demanding activity as writing. Since the 1980s, sound theoretical claims and empirical demonstrations supporting the complexity of writing have been provided. In part, this complexity is ascribed to the numerous processes involved in the act of producing written text that have to be orchestrated (see Chapters 3 and 9 of this volume), from the need to proficiently use a writing tool (e.g. a pen or a keyboard) or correctly spell words (Abbott & Berninger, 1993) to the importance of generating adequate ideas coherently organized to fulfil rhetorical goals (Hayes & Nash, 1996) and translated into an adapted language, while simultaneously dealing with external demands (e.g. audience) and internal beliefs (e.g. self-efficacy). Because of this complexity, it is well-established in the writing research field that, regardless of the term used, executive functions are a fundamental ingredient to produce good writing throughout the lifespan (Graham, 2018a; Harris et al., 2018; Kellogg & Whiteford, 2009; Olive, 2014), as discussed in Section IV of this volume. Despite being widely accepted, one can neither say that the relationship between executive functions and writing is grounded on a large body of empirical research nor that it is a core research topic in the field of writing research. The limited efforts to explore the nature of the connection between executive functions and writing is even more evident when we look at recent compilations of works deepening our knowledge about the role of executive functions in education (Huizinga, Baeyens, & Burack, 2018; Meltzer, 2018). Notwithstanding their relevance, writing is only cursorily addressed. There is no question that during the last decade executive functions
Introduction 5
became mainstream in neurocognition and educational research fields. Nevertheless, few attempts have been made to deeply investigate the role of executive functions in the production of written language in children and adolescents, and mainly in adults and elders. Born within the M2S Project,1 the current volume was devised with a twofold purpose: to provide a comprehensive portrait of the state-of-the-art on the link between executive functions and writing, from theoretical, methodological, and developmental viewpoints; and to identify gaps in the literature that can inspire and stimulate researchers to deepen our knowledge in the topic through well-designed empirical research. To that end, we gathered a diverse group of internationally recognized scholars—coming from complementary areas in Psychology (e.g. Cognitive, Educational, Neuropsychology, Developmental, Experimental, School, Health) as well as from equally relevant research fields (such as Neuroscience or Medicine)— and to whom we are deeply grateful for making this volume possible. According to their area of expertise, authors were invited to produce specific chapters organized into four sections (besides the current, introductory one), which are further detailed in what follows.
Overview of the Current Volume Section II. Models of Executive Functions and Writing
This section comprises two chapters addressing theoretical issues related to the conceptualization of executive functions and written language. In Chapter 2, Willoughby and Hudson provide an overview on the concept of executive functions. They start by presenting the neurobiological grounding of executive functions, with an eye on the precursors and correlates of these skills. This is followed by methodological considerations concerning performance-vs. questionnaire- based measurements of executive functions (see Chapter 4 of this volume for a thorough discussion on this). Willoughby and Hudson then provide a review of relevant theoretical models of executive functions, with the goal of showing the variation in scope and breadth of executive processes considered. After discussing the seminal models from Lezac (1995), Anderson (2002) and Zelazo, Carter, Reznick, and Frye (1997), they discuss the dimensionality of executive functions, grounded on empirical, factor-analytic approaches. Afterwards, they put forward a set of considerations regarding the development of executive functions, which are particularly useful to prepare readers for the chapters included in Section IV of this volume. The chapter ends with reflections 1 The M2S Project, ‘Mindfulness to students’ success (M2S): relating executive functions and writing through a mindfulness app to promote children’s cognitive, social, and health-related outcomes’, was funded through the Operational Programme for Competitiveness and Internationalization, supported by FEDER and national funds allocated to the Portuguese National Foundation for Science and Technology (NORTE-01-0145-FEDER-028404). More information on the project can be consulted at m2s.up.pt and its activities can be followed at https://www.facebook.com/M2S.project/
6 1. Relationship Between EFs and Writing on the characterization of executive functions as a joint function of trait and state influence and a discussion on the conceptual similarity between concepts such as executive functions, error monitoring, metacognition, and uncertainty monitoring (all assumed to contribute to self-regulation). As intended by Willoughby and Hudson, the many inconsistencies and discrepancies in the field brought to light in the chapter provide a comprehensive framework for readers to adopt a critical position while going through subsequent chapters in the volume. In Chapter 3, Graham presents the Writer(s)-within-Community model of writing (WWC; Graham, 2018a; Graham, 2018b), which merges the sociocultural and cognitive perspectives prevalent in the field of writing research. The WWC model includes two main components: the writing community where writing occurs, and the cognitive resources and capabilities of its members, which involve a set of control mechanisms to regulate the mental and physical processes used to produce text that draw on long-term memory resources. Adopting the term executive control (instead of executive functions), the author describes contextual and individual factors in writing and exemplify how these interact to shape and constrain the use of executive control in writing. Specifically, grounded on the WWC model, Graham describes common features of writing communities (e.g. purposes, members, tools) and discusses how these may shape and bind executive control. Subsequently, he delves into the cognitive architecture of the members of the community, namely writers, their collaborators (including mentors and teachers), and the intended audience (readers). Supported by illustrative examples depicting varying writing situations, the author describes the role of executive control in writing, viewed by the WWC as a multidimensional set of control mechanisms, including executive processes, working memory, and attention. In the second part of the chapter, Graham presents four tenets underlying the operation of the WWC model: (a) interactive effects between a writing community and its members; (b) simultaneous effects of community and individual capacity; (c) simultaneous effects of variability in a writing community and its members; and (d) simultaneous effects of community and member development. Illustrative examples of how these four tenets can potentially influence executive control are provided. The chapter ends with a summary of eight assumptions about executive control and writing within the WWC and future indications to empirically test them.
Section III. Methods for Assessing Executive Functions and Writing
The third section of the volume includes two chapters that discuss methodological matters concerning the measurement of executive functions and writing. In Chapter 4, St. Clair-Thompson and Wen provide an overview on two broad approaches to measure executive functions mainly in children (viz, cognitive measures and behavioural rating scales), with the ultimate goal of helping readers in choosing executive measures in an informed and justified way. They start with a brief description of several cognitive tasks typically used to measure each of the three core dimensions of executive functions, namely, inhibition, shifting, and updating working memory (Miyake et al., 2000). Subsequently, St. Clair-Thompson and Wen discuss a
Introduction 7
set of four factors that should be considered when selecting a task to assess executive functions: (a) degree to which the task is developmentally appropriate for children, including those with disabilities (e.g. in terms of task difficulty, complexity of instructions, type of stimuli); (b) extent to which there are indicators that the measure is reliable (including alternate forms); (c) whether the task actually measures the cognitive processes that it is intended to assess; and (d) degree to which the task measures more than one executive function (also known as the ‘task impurity problem’). A useful table discussing these considerations in reference to the measures described earlier is also presented. In the second part of the chapter, St. Clair-Thompson and Wen discuss another approach to the measurement of executive function, that of using behavioural rating scales. They specifically focus on the Behavior Rating Inventory of Executive Function (Gioia, Isquith, Guy, & Kenworthy, 2000), one of the most commonly measures used, and discuss indicators of validity and reliability of the instrument. The chapter ends with a valuable reflection on the similarities and differences between using cognitive measures or rating scales to measure executive functions, followed by a flowchart intended to guide the decision-making processes when choosing a suitable measure of executive function. In Chapter 5, Dockrell and Connelly discuss the measurement of writing, recognizing that one of the challenges in assessing writing is the lack of consensus on the meaning of writing proficiency at different developmental points. The chapter is organized around the measurement of two complementary aspects of writing: the outcome achieved (product) and the process that led to it (process). Concerning the assessment of the writing product, authors discuss the use of holistic and analytic scores as well as of the focus on specific dimensions of the written product (e.g. writing at the word, sentence, and text levels vs. productivity, complexity, and quality of writing). Turning to assessment of the writing process, Dockrell and Connelly present and discuss the measurement of key processes underlying text production, including planning, translating (in which they include the use online measures of writing to gauge bursts of written language), and revising, along with other dimensions, such as metacognitive control and communication. The subsequent discussion delves into three aspects worthy of considering when choosing a writing measure: (a) the number of samples to be collected and the duration of the writing task; (b) the degree to which genre influences the process and the product to be assessed; and (c) the possibility of using automated writing evaluation systems. Dockrell and Connelly also acknowledge the importance of adopting a framework that considers not only proximal factors (e.g. spelling) but also distal factors (e.g. oral language) that support writing. These latter underpin the production of writing and should be considered in a broader conceptualization of the assessment of writing. They additionally provide an illustration on how the previous remarks concerning the measurement of writing can be put into practice in empirical research. The conclusion of this chapter provides a thorough discussion on the challenges involved in the measurement of writing, including less targeted ones, as the language in which the text is produced.
8 1. Relationship Between EFs and Writing
Section IV. Executive Functions and Writing Across the Lifespan
This section gathers five chapters focusing on the relationship between executive functions and writing throughout lifespan development. In Chapter 6, Hooper et al. delve into the link (or lack of) between executive functions and writing in child and adolescent writers, from a developmental point of view. The authors start by describing several key models (i.e. Psychological Models, Problem-Solving Models, Working Memory Models) with potential applications to writing. They then provide a brief overview on the development of executive functions and writing skills, with the acknowledgement that the degree to which the development of those skills is related (inclusively in a bidirectional way) is still unclear. In what follows, Hooper et al. address the link between key components of executive functions and writing in novice writers. Studies providing empirical evidence on the association between inhibitory control, cognitive flexibility, working memory, and planning are reviewed. This first part of the chapter sets the basis for its second part, in which they discuss the associations and dissociations of executive functions and written expression. The discussion is grounded on an interesting viewpoint, concerning the situations in which intact executive functions are coupled with intact writing skills, or when impaired executive functions are coupled with impaired writing skills (associations); and when intact executive functions coexist with impaired writing skills, or vice versa (dissociations). Hooper et al.’s considerations become more intricate when they consider the issue of associations and dissociations between executive functions and writing over the course of development. The chapter ends recognizing the lack of research into these associations and dissociations, mainly through longitudinal methodologies. Hooper et al. provide relevant avenues for future research aimed to deepen our knowledge not only about the contribution of executive functions to writing, but also about the influence of written composition on executive functions. In Chapter 7, Filipe raises the question of how executive functions may influence writing in individuals with neurodevelopment disorders. As she noted, writing can be especially difficult for those people. In part, that can be related to the importance of executive functions in writing associated with the executive impairments frequently observed in neurodevelopment disorders. Three clinical conditions are addressed: autism spectrum disorder, attention-deficit/hyperactivity disorder, and specific learning disorder (e.g. dyslexia). For each of these neurodevelopmental disorders, Filipe provides a definition of the condition and presents its fundamental characteristics, with a focus on the executive functions mostly impaired, which is then associated with the specific writing profile of these individuals. Overall, she proposes that the writing difficulties observed in autism spectrum disorders may be mainly associated with problems in cognitive flexibility, whereas the problems in writing observed in attention-deficit/hyperactivity disorders may be mostly related to working memory deficits, which may also underlie a great part of the difficulties faced by writers with specific learning disorders. Throughout the chapter, Filipe provides several examples aimed at illustrating how the impaired executive functions may constrain key aspects of text production, from handwriting to revising in response to
Introduction 9
feedback. The chapter ends with useful implications for practitioners and educators, including indications for writing assessment, which should be tailored to the specific needs of individuals with neurodevelopmental disorders; as well as recommendations for developing and implementing writing interventions capable of helping them to overcome their executive impairments and diminish their difficulties in writing. In Chapter 8, Mason and Brady provide a thorough discussion concerning how and why the teaching of writing should target executive functions, mainly through the inclusion of instructional components targeting self-regulation. They start by addressing the promotion of executive functions in the context of writing sentences, including compound and complex sentences, via the evidence-based methods of sentence combining. Afterwards, they focus on the promotion of writing processes (e.g. planning), through the well-known Self-Regulated Strategy Development (SRSD) model (Harris et al. 2018). This is a widely used and effective evidence-based approach that, among other key writing ingredients (such as knowledge or beliefs) targets several executive functions in the context of text production. Mason and Brady provide a description of the main steps of this model (i.e. develop and activate knowledge, discuss it, model it, memorize it, support it, and independent performance) and how each one can be implemented to support executive functions. They also present the SRSD for quick-writes (i.e. brief response to a prompt during a short time period), including additional tips to help the promotion of executive functions. Grounded on the effectiveness of strategy instruction, authors provide readers with a set of evidence-based writing strategies in the form of mnemonics that support several executive functions called for when producing a text (e.g. planning, working memory). In what follows, Mason and Brady discuss the power of technology (coupled with self-regulation) to support executive functions and improve writing. A set of studies describing technology-based writing interventions is briefly presented. Some of these studies showed the effectiveness of using technology to help students to plan via computer-based graphic organizers. The chapter ends by acknowledging the potential of joining strategies, self-regulation, and self-regulatory prompting with technology as a means to develop executive functioning in writing. In Chapter 9, Olive focuses on the link between executive functions and writing in skilled writers, whose empirical grounds are admittedly scarce. Stemming from analytical or theoretical descriptions of the cognitive demands of writing along with indirect empirical findings, he presents a set of arguments to support the involvement of executive functions in skilled writers. He then critically presents the componential model of working memory in writing (Kellogg, 1996) and the capacity model of working memory in writing (McCutchen, 1996). Despite not fully specifying the role of executive functions in writing, these models have the advantage of addressing the role of a key executive function in skilled writers (working memory, which is likely the most researched executive function in this population). In what follows, Olive presents a set of empirical studies that indirectly addressed the role of executive functions in skilled writing, in particular, by measuring the cognitive effort involved in the highly demanding writing processes (viz., planning, translating, revising, transcription),
10 1. Relationship Between EFs and Writing seen as an indicator of the engagement of executive functions. Next, he presents a set of initial proposals about the executive functions required by writing processes, either when enacted in sequence or concurrently. In general, Olive claims that the concurrent coordination of writing processes typically observed in skilled writers requires strong executive supervision particularly for monitoring process switching, information flow, and the related processing and short-term storage demands. Olive ends the chapter issuing a challenge to the research community targeting skilled writers, that of gathering empirical evidence on the role played by the multiple executive functions in the major cognitive processes of writing, and on how and to which extent does that role depends upon different writing tasks and situations, as well as skilled writers’ interindividual differences. In Chapter 10, Castro and Abreu focus on the ageing writer in health and disease. They explore whether executive functions take part in the age-related changes observed in writing and whether writing can influence executive functioning in older people. Indeed, the chapter is grounded on the interesting claim that writing can be both an expression and an enhancer of cognitive functioning. Castro and Abreu began with a characterization of cognition in older ages, which is progressively narrowed to a characterization of writing aspects. They draw a thorough profile of the ageing writer, focused on the main age-related characteristics of writing in terms of content- related levels (i.e. lexical, syntactical, and discourse) as well as in terms of production processes (i.e. handwriting and typing). Recognizing the lack of empirical studies directly examining how executive functions impact writing in older years, they present a set of models to support their claim that executive functions can partly explain some age-related changes in writing. To continue substantiating the link between executive functions and writing in older ages, Castro and Abreu detail the many writing-related changes typically observed in dementia (relevant for screening and diagnosing purposes), which are however clearly distinguishable from those observed in healthy ageing. In the subsequent part of the chapter, they focus on the benefits of writing- based interventions in older people, mainly in socioemotional dimensions. Despite the scarce research evidence on this topic, they succeed in gathering evidence on the beneficial effects of autobiographical life review programmes (either in speaking or writing modalities), writing group interventions, learning a challenging calligraphy, and daily log of personal experiences. To conclude, Castro and Abreu present useful remarks concerning the still-open questions in the field (e.g. are the writing-related changes observed in healthy ageing progressive or sudden?), hoping for more research into the cognitive and socioemotional dimensions of the ageing writer.
Section V: Conclusions and Future Directions
The last section of the volume provides a set of three commentary chapters on the link between executive functions and writing, including insightful reflections on the topic and indications for future research. In Chapter 11, McCloskey comments on each section of the volume. To emphasize the importance of adopting a multidimensional perspective on executive functions, he presents the Holarchical Model of Executive
Conclusion 11
Control that includes multiple tiers of executive control (McCloskey, Gilmartin, & Stanco-Vitanza, 2014). Then, the author discusses issues related to the assessment of executive functions and writing, and describes the cascading production analysis methodology, illustrated with writing-related assessment tasks. Finally, McCloskey reflects on how to strengthen the use of executive functions in varying contexts and presents the executive control intervention continuum (McCloskey, Gilmartin, & Stanco-Vitanza, 2014). In Chapter 12, Georgiou notes the reduced attention given to a higher-order executive function (at least in comparison to the three core functions of inhibition, shifting, and updating in working memory), that of cognitive planning. This process is labelled by the author as the ‘common denominator’ of both executive functions and writing. Georgiou also provides several empirically grounded considerations regarding the conceptualization of cognitive planning, which are then used to fit this process into existing models of writing and to present a writing task that operationalizes cognitive planning (cold executive functions), including an affective component (hot executive functions). In Chapter 13, Goldstein and McGoldrick open their commentary with a series of questions concerning future challenges raised by globalization and technology development. The authors do not have answers for those challenges, but they claim that educational settings do certainly need to prepare children to deal with them. As they suggest, developing students’ executive functions can be a means not only to prepare them for the unknown time to come, but also to facilitate the current acquisition of key academic skills, such as writing. Given the central role that executive functions play inside and outside school and work contexts, promote them is contributing to develop citizens ready for new current and future challenges.
Conclusion This volume itself provides a thorough answer to the question raised in the title of this chapter: Why should we be looking at the relationship between executive functions and writing? In this introductory chapter, we risk a clear-cut, perhaps simplistic, response to that query, which can be put as: because executive functions are essential to produce good writing and, if we want good writers, we need to know more about how this link operates in childhood, adulthood, and elderly years. As well illustrated through the volume, the relationship between executive functions and writing is more than a theoretical claim. There is now an emerging body of evidence showing the importance of those top-down mental processes to produce good writing at any age. Still, this volume showed that this evidence is neither consistent nor abundant. It is still not clear the conditions that determinate why one component of executive functions may be more important to writing than another. Moreover, the amount of studies aiming to deepen our knowledge about the contribution of executive functions to writing throughout the lifespan is reduced (the older the writer, the less evidence seems to
12 1. Relationship Between EFs and Writing exist). Also, the methodologies used across available studies barely match, which impedes sound comparisons and productive synthesis to support strong theories. By providing a complete state-of-the-art on the theoretical and empirical bases relating executive functions and writing, while at the same time calling readers attention to the numerous gaps in these bases and giving them suggestions to overcome them, we believe this volume is an innovative and valuable contribution to the field of writing research and adjacent areas of inquiry. Additionally, given the coverage of the topic—presenting theoretical viewpoints, discussing methodological considerations, and targeting developmental issues from childhood to old age, this volume can be seen as a reference and essential reading among researchers and graduate students interested in understanding the cognitive underpinnings of writing throughout the writer lifespan. The applied focus adopted in Section IV looking at executive functions and writing in children, adolescents, adults, and elders, also turns this volume into a useful tool for educators and practitioners interested in better understanding how to foster the mastery of writing throughout the lifespan. Though many individuals struggle to master written language, its value in contemporary nations is irrefutable. The information generated by research is a catalyst for nurturing citizens’ capabilities to use that key skill. The body of knowledge here thoroughly presented and critically discussed can contribute to fulfil that goal. As editors, this was our intention when crafting the proposal of the current volume. Now that it is finished, we believe that the collection of works here gathered do represent a powerful knowledge asset for researchers and educators embarking the long and demanding journey of improving citizens writing skills.
References Abbott, R.D., & Berninger, V.W. (1993). Structural equation modeling of relationships among developmental skills and writing skills in primary-and intermediate-grade writers. Journal of Educational Psychology, 85, 478–508. Anderson, P. (2002). Assessment and development of executive function (EF) during childhood. Child Neuropsychology, 8, 71–82. Berninger, V.W., & Winn, W. (2006). Implications of advancements in brain research and technology for writing development, writing instruction, and educational evolution. In C.A. MacArthur, S. Graham, & J. Fitzgerald (Eds.). Handbook of Writing Research (1st ed., pp. 96– 114). New York, NY: Guilford Press. Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64, 135–68. Gioia, G.A., Isquith, P.K., Guy, S.C., & Kenworthy, L. (2000). Test review behavior rating inventory of executive function. Child Neuropsychology, 6, 235–38. Graham, S. (2018a). A revised writer(s)-within-community model of writing. Educational Psychologist, 11, 258–79. Graham, S. (2018b). A writer(s) within community model of writing. In C. Bazerman, V. W. Berninger, D. Brandt, S. Graham, J. Langer, S. Murphy, P. Matsuda, D. Rowe, & M. Schleppegr (Eds.). The Lifespan Development of Writing (pp. 272–325). Urbana, IL: National Council of English.
References 13 Harris, K.R., Graham, S., Mason, L., McKeown, D., & Olinghouse, N.G. (2018). Self-regulated strategy development in writing: a classroom example of developing executive function processes and future directions. In L. Meltzer (Ed.). Executive Function in Education: From Theory to Practice (pp. 326–56). New York, NY: The Guilford Press. Hayes, J.R. (1996). A new framework for understanding cognition and affect in writing. In C.M. Levy & S. Ransdell (Eds.). The Science of Writing: Theories, Methods, Individual Differences, and Applications (pp. 1–27). Mahwah, NJ: Lawrence Erlbaum Associates. Hayes, J.R. (2012). Modeling and remodeling writing. Written Communication, 29(3), 369–88. Hayes, J.R., & Flower, L. (1980). Identifying the organization of writing processes. In L.W. Gregg & E.R. Steinberg (Eds.). Cognitive Processes in Writing (pp. 3–29). Hillsdale, NJ: Lawrence Erlbaum Associates. Hayes, J.R., & Nash, J.G. (1996). On the nature of planning in writing. In C.M. Levy & S. Ransdell (Eds.). The Science of Writing: Theories, Methods, Individual Differences, and Applications (pp. 29–55). Mahwah, NJ: Lawrence Erlbaum Associates. Huizinga, M., Baeyens, D., & Burack, J.A. (2018). Editorial: executive function and education. Frontiers in Psychology, 9, 1357. Kellogg, R.T. (1996). A model of working memory in writing. In C.M. Levy & S. Ransdell (Eds.). The Science of Writing (pp. 57–71). Mahwah, NJ: Lawrence Erlbaum Associates. Kellogg, R.T., & Whiteford, A.P. (2009). Training advanced writing skills: the case for deliberate practice. Educational Psychologist, 44, 250–66. Kim, Y.G., & Schatschneider, C. (2017). Expanding the developmental models of writing: a direct and indirect effects model of developmental writing (DIEW). Journal of Educational Psychology, 109, 35–50. Lezac, M.D. (1995). Neuropsychological Assessment (3rd ed.). New York, NY: Oxford University Press. Lezac, M.D., Howieson, D.B., Bieglerr, E.D., & Tranel, D. (2012). Neuropsychological Assessment. New York, NY: Oxford University Press. McCloskey, G., Gilmartin, C., & Stanco-Vitanza, B. (2014). Interventions for students with executive skills and executive functions difficulties. In J.T. Mascolo, V.C. Alfonso, D.P. Flanagan (Eds.). Essentials of Planning, Selecting, and Tailoring Interventions for Unique Learners (pp. 314–56). New York, NY: Wiley. McCutchen, D. (1996). A capacity theory of writing: working memory in composition. Educational Psychology Review, 8, 299–325. Meltzer, L. (2018). Executive Function in Education: From Theory to Practice. New York, NY: The Guilford Press. Miyake, A., Friedman, N.P., Emerson, M.J., Witzki, A.H., Howerter, A., & Wager, T.D. (2000). The unity and diversity of executive functions and their contributions to complex ‘frontal lobe’ tasks: a latent variable analysis. Cognitive Psychology, 41, 49–100. Olive, T. (2014). Toward a parallel and cascading model of the writing system: a review of research on writing processes coordination. Journal of Writing Research, 6, 173–94. Zelazo, P.D., Carter, A., Reznick, J.S., & Frye, D. (1997). Early development of executive function: a problem-solving framework. Review of General Psychology, 1, 198–226.
II
MODELS OF EXECUTIVE FUNCTIONS AND WRITING
2 Current Issues in the Conceptualization and Measurement of Executive Function Skills Michael Willoughby and Kesha Hudson
Introduction and Chapter Objective Over the last three decades, interest in executive functions has continued to grow. For example, a search of the term ‘executive function’ as a topic in the Web of Science identified 1385, 9792, and 30,787 papers that were published during the 1990–1999, 2000–2009, and 2010–2019 time periods, respectively. These numbers only convey interest in executive functions in the published peer-reviewed literature and ignore growing interest in executive function skills in the popular press and clinical applications (e.g. tutoring, life coaches). The widespread interest in executive functions spans multiple disciplines including psychology, cognitive neuroscience, education, and public policy. Multidisciplinary interest in executive function skills stems from the central role that executive functions play in influencing other aspects of cognition and behaviour, as well as evidence that executive functions, and the neural substrates that support them, are sensitive to positive and negative life experience. Indeed, Diamond (2013) described executive functions as the ‘canary in the coal mine’. We begin by providing an oft repeated definition of executive function (EF) for which there is broad consensus in the field. EF is a set of domain general cognitive processes that collectively facilitate goal-directed behaviour and problem solving. Following Zelazo, Blair, and Willoughby (2016), we refer to cognitive processes that are attributed to EF as ‘skills’ to underscore the idea that they are malleable and susceptible to experience. EF skills are considered ‘domain general’ because they are applicable to a wide range of contexts and content areas, which is one of the reasons that they are so widely studied. In contrast to automatic processes, EF skills are presumed to involve effort, intentionality, and conscious awareness, which support ‘goal- directed’ behaviour. More colloquially, EF skills are understood to be engaged when individuals find themselves in situations where they cannot function on ‘auto-pilot’. Notably, activities that initially require EF skills during a learning phase may subsequently be automatized once mastery has been achieved (e.g. learning to drive a Michael Willoughby and Kesha Hudson, Current Issues in the Conceptualization and Measurement of Executive Function Skills In: Executive Functions and Writing. Edited by: Teresa Limpo and Thierry Olive, Oxford University Press. © Oxford University Press 2021. DOI: 10.1093/oso/9780198863564.003.0002
18 2. Conceptualization and Measurement of EF skills car). EF is routinely described as an ‘umbrella term’, which conveys the idea that multiple cognitive processes are implicated in identifying, directing, and achieving goal- directed actions. A final idea common to most consensus definitions is that EF skills represent ‘top-down’ cognitive processes that act on ‘lower-order’ aspects of cognition. EF skills are attentional processes that can inhibit, augment, bias, or otherwise influence other aspects of cognition or motoric actions. Despite the widespread adoption of this general definition of EF, a close reading of the research literature reveals numerous definitional, conceptual, and measurement complications that collectively impede systematic research. The overarching objective of this chapter is to selectively highlight some of these issues. Inspired by Hughes (2011) selective review of 20 years of research related to changes and challenges in research on the development of EF, we provide a broad-brushstroke consideration of salient issues related to the conceptualization and measurement of EF skills. While we make no claims about how to resolve points of disagreement or confusion, we hope that drawing attention to these issues will provide readers a useful vantage for critically evaluating other chapters of this volume.
Neurobiological Basis The origins of EF as a psychological construct emerged from the clinical observations of neuropsychologists who treated adult patients with frontal lobe lesions or impairments (Petrides & Milner, 1982; Shallice, 1982). Individuals with frontal lobe impairments were observed to exhibit a wide range of changes in personality, demeanour, behaviour, and cognitive performance that were distinct from crystallized aspects of cognition. Early clinical presentations of patients with frontal lobe lesions informed ideas about the role and function of frontal lobes, which were subsequently elaborated through systematic research with animals (Chudasama, 2011; Stuss, 2011; Stuss & Alexander, 2000). Modern neuroimaging studies have dramatically improved our understanding of the neural networks that support EF skill development. Early efforts to localize EF impairments to frontal lobes have been replaced by more nuanced characterizations of the highly segmented nature of the frontal lobes which support specific EF skills (Jurado & Rosselli, 2007; Stuss, 2011), as well as neural networks that support EF skills and related cognitive processes more generally (Fiske & Holmboe, 2019; Fjell et al., 2012; Petersen & Posner, 2012). In addition to informing our understanding of EF skill development across the lifespan, neurobiologically informed studies have also informed our understanding of precursors and correlates of EF skills. For example, economic strain and poverty in childhood, as well as the experience of scarcity in adulthood are associated with EF impairments (Hackman, Farah, & Meaney, 2010; Shah, Mullainathan, & Shafir, 2012). These empirical associations were buttressed by well-established linkages between the prefrontal cortex (PFC) and subcortical structures involved in the appraisal of threat, the processing of emotion, and the management of stress (Arnsten, 2014,
Measurement Considerations 19
2015). We are increasingly able to delineate the ways in which the experience of poverty impairs EFs through intermediate effects on neural development (Hackman & Farah, 2009; Noble et al., 2015). As another example, EFs are intimately related to motor skills, including motor coordination and planning, as well as general athletic competence (McClelland & Cameron, 2019; van der Fels et al., 2015; Vestberg et al., 2012). Moreover, children and adults with movement-based disorders often evidence EF impairments (Weierink, Vermeulen, & Boyd, 2013; Wilson et al., 2013). The co- occurrence of EF skills and motor competence is consistent with linkages between the PFC and areas of the brain that control motor development, including the motor cortex and the cerebellum (Koziol, Budding, & Chidekel, 2012; Leisman, Moustafa, & Shafir, 2016). The neurobiological grounding of EF skills is a key distinguishing factor from conceptually similar psychological constructs for which the neurobiological basis is less well established or simply inferred (e.g. self-control, ego control, delay of gratification). Although early research routinely conflated EF skills and ‘frontal lobe functions’ as interchangeable terms, modern research has moved away from inferring a one-to-one correspondence between EF skills and neural activity. Herein lies one of the challenges in the current literature. On the one hand, there are well-established cognitive paradigms to measure EF skills that are known to depend on the function and structural integrity of PFC (including neural networks that involve the PFC). In this way, EF tasks have long served as an indirect indicator of PFC activity. However, not all assessments that purport to measure EF skills necessarily engage PFC activity.
Measurement Considerations Decisions about how to measure EF skills reflect implicit assumptions about the nature of the construct of EF. Moreover, differences in measurement contribute to heterogeneity in the extant evidence base. Beginning with clinical neuropsychological work that involved adults, performance-based tasks have long been considered the gold-standard method for assessing EF skills. Summaries of performance-based tasks that have been used for research purposes are provided elsewhere (Carlson, 2005; Chan, Shum, Toulopoulou, & Chen, 2008; Nyongesa et al., 2019). Norm-referenced and standardized batteries of performance-based tasks are also in wide use for clinical purposes (Delis, Kaplan, & Kramer, 2001; Korkman, Kirk, & Kemp, 1998). Performance-based tasks use well-established cognitive paradigms that are designed to engage one or more subdomains of EF that are understood to rely on the PFC. In cases where the emphasis is on the identification of functional impairment (e.g. psychoeducational or neuropsychological assessments), EF task performance is intended to serve as an indirect proxy for structural or functional impairment of PFC (Grodzinsky & Diamond, 1992; Hynd et al., 1995; Taylor et al., 1996). As interest in EF skills has broadened to include typically developing youth (Hughes, 2011), EF task
20 2. Conceptualization and Measurement of EF skills performance is also intended to serve as an indirect proxy for the efficiency of the PFC and to document individual differences in normative cognitive development. Critics of performance-based tasks have emphasized that the highly structured, emotionally neutral, one-on-one context in which EF assessments are administered (which derive from clinical applications) poorly approximate the ‘everyday’ contexts in which EF skills are typically required (e.g. classroom or recess settings). Concerns about the ecological validity of performance-based EF tasks was a major impetus for the development of questionnaire-based assessments of EF skills, including the Behavioral Rating Inventory of Executive Function which is among the oldest and most widely used EF questionnaire (Gioia, Espy, & Isquith, 2003; Gioia et al., 2000; Roth, Isquith, Gioia, & Widows, 2005). EF questionnaires were designed to measure real-world behaviours that were presumed to directly reflect EF skills. For example, the Childhood Executive Functioning Inventory (CHEXI) is a freely distributed EF questionnaire that has parent and teacher versions (Thorell & Nyberg, 2008). Parents and teachers rate the frequency of behaviours that are presumed to index specific cognitive processes. For example, individual differences in children’s difficulty stopping an activity after being told to do so is presumed to index inhibitory control. Similarly, individual differences in children’s ability to follow multistep instructions without becoming distracted is presumed to index working memory. The number of questionnaire-based assessments of EF skills continues to grow (e.g. Bennett, Ong, & Ponsford, 2005; Naglieri & Goldstein, 2004–2015; Nilsen, Huyder, McAuley, & Liebermann, 2017; Vallat-Azouvi, Pradat-Diehl, & Azouvi, 2012). Advocates of EF questionnaires emphasize three comparisons with performance- based assessments (Isquith, Roth, & Gioia, 2013). First, whereas performance-based assessments represent performance at a single point in time in a highly structured setting, parents and teachers are privy to a broad sampling of children’s observed behaviours in naturalistic settings. EF questionnaires take advantage of adult perspectives of children’s EF-related behaviours in naturalistic settings. Second, questionnaire- based assessments can be achieved in shorter time and at less cost than performance- based assessments, both of which make them more easily scalable than individual performance-based assessments. Third, questionnaire-based assessments have well- established reliability and validity and have been useful in planning and evaluating interventions (Isquith, Roth, Kenworthy, & Gioia, 2014). In sum, proponents argue that EF questionnaires index the manifestation of EF skills in naturalistic contexts, with minimal burden, and that they provide information that facilitates assessment and intervention monitoring. Despite the purported benefits of questionnaires, numerous concerns have been raised about their use. Most troubling is the fact that EF questionnaires are weakly correlated with performance-based tasks. In a summary of 20 studies that included child and adult samples in clinical and non-clinical contexts, Toplak and colleagues reported that only 24% of all correlations between questionnaire and performance- based measures were statistically significant, and the median correlation between questionnaire and performance- based assessments of the same construct was
Measurement Considerations 21
r = 0.19 (Toplak, West, & Stanovich, 2013). They concluded that questionnaires and performance-based tasks measure different phenomena. Although EF questionnaires are often proposed as complementary to performance-based tasks, the weak associations routinely result in discrepant information that are difficult to reconcile at the level of individual children (Silver, 2014). Notably, EF questionnaires are more strongly associated with other aspects of behaviour (e.g. attention deficit hyperactivity disorder symptomatology; conscientiousness) than they are with the cognitive processes (e.g. working memory, cognitive flexibility, inhibitory control) that they are intended to measure (Buchanan, 2016; Castellanos, Kronenberger, & Pisoni, 2018; McAuley et al., 2010; Spiegel, Lonigan, & Phillips, 2017). These results suggest that method variance is more prominent than construct-related variance, which raises fundamental concerns about what EF questionnaires are measuring. EF questionnaires are predicated on the strong assumption that individual differences in observed behaviour necessarily reflect corresponding differences in cognitive processes and the neural substrates that support them. To the extent that observed behaviours are multiply determined, the implicit assumptions of EF questionnaires are questionable. This is not to suggest that EF questionnaires do not reliably index individual differences in observable behaviour, that they do not exhibit criterion and predictive validity especially for other aspects of behaviour, or that they do not inform treatment planning (they do in all cases). However, EF questionnaires can be both conceptually appealing and practically useful while still measuring different phenomenon than do performance-based tasks. Although the development of questionnaires has been the dominant approach for attending to the ecological validity problem of performance-based assessments, other strategies have also been considered. Burgess and colleagues described how many performance-based tasks are vestiges of early clinical and experimental paradigms, and they emphasized the value in developing a new generation of tasks that yielded more generalizable and practically useful information for clinicians (Burgess et al., 2006). Functional assessments of EF skills seek to address the same shortcomings that spawned the development of questionnaires (ecological validity) while retaining some of the benefits of performance-based task (standardization). Functional measures, such as the Multiple Errands Test (Shallice & Burgess, 1991), attempt to emulate real-world activities in which EF skills would be required, thereby improving their ecological validity and clinical utility. For example, clinical patients are presented with various scenarios that require them to complete tasks, such as planning and completing a shopping trip. Participants are instructed to complete the task while adhering to certain rules, such as staying on budget, not purchasing more than a certain number of items, or avoiding visiting the same area twice. Participant behaviour is observed and performance is evaluated based on the total number of errors committed (e.g. inefficiencies, rule breaks, task failures) and the time it took to complete the assessment (Alderman, Burgess, Knight, & Henman, 2003; Rand, Katz, & Weiss, 2007; Shallice & Burgess, 1991). Although early applications of functional EF assessments were relatively rare, technological improvements in virtual and augmented
22 2. Conceptualization and Measurement of EF skills reality have created new interest in these approaches (Negut, Matu, Sava, & David, 2016; Parsons, 2015; Parsons, Duffield, & Asbee, 2019). Although beyond the scope of this chapter, it is noteworthy that functional assessments adopt a profoundly different conceptualization of EF skills than do traditional performance-based assessments, in that they are less focused on construct-related variance and more on functional behavioural outputs that represent a confluence of EF skills. Given the groundswell of interest in EF as a construct, standardized assessment tools are increasingly available for research purposes. For example, the NIH Toolbox and the NIH Examiner represent major efforts to develop standardized performance- based assessments of EF skills that are appropriate for lifespan research (Kramer, 2014; Weintraub et al., 2013). Efforts are currently underway to develop the NIH ‘Baby Toolbox’ that will facilitate the measurement of EF skills and their precursors in toddlerhood and early childhood. Although performance-based tasks are frequently criticized for having low ecological validity, it is not clear that alternative efforts that purport to measure EF skills are necessarily measuring the same construct. Efforts to develop classroom observational systems for measuring EF skills are also underway (McCoy, 2019), though it remains unclear how they will overcome limitations of questionnaire-based approaches. Innovations in game-based assessments, as well as virtual or augmented reality platforms, hold promise for the development of new assessment methods that leverage the strengths of standardized performance- based assessments while also attending to concerns related to poor ecological validity (Lumsden et al., 2016; Parsons, 2016).
Theoretical Models Theoretical models of EF were developed to help explain the wide range of cognitive and behavioural impairments that were attributable to EF impairments and frontal lobe dysfunction. Early theoretical models emphasized a supervisory system or central executive, which were presumed to derive primarily from frontal lobe activity, as a framework for understanding working memory and cognitive control (Norman & Shallice, 1986). Although heuristically useful, these initial ideas were subsequently updated with more nuanced models that considered a broader array of cognitive processes and that emphasized variations in the functions of frontal lobes, as well as their interconnections with other areas of the brain (Andres, 2003; Baddeley, 1998; Shallice & Burgess, 1996). Although a comprehensive review of EF models is outside of the scope of this chapter, we selectively highlight a few models to highlight similarities and to illustrate the variation in scope and breadth of executive processes that were considered. Lezak (1995) presented an EF framework that consisted of four domains including volition, planning, purposive action, and effective performance. In this framework, volition refers to the conscious decision to carry out a goal-directed action or future-oriented behaviour. Once a goal is specified, planning is necessary to achieve
Theoretical Models 23
the desired outcome. Planning involves identifying a sequence of steps and requires additional cognitive processes including impulse control, working memory, and sustained attention. The initial execution and continued maintenance of the planned actions, which includes modifying the sequences of action as necessary, is referred to as purposive action. Mental flexibility underlies the ability to modify behaviour in response to task demands in order to achieve goals. The final executive process in Lezak’s framework is effective performance, which refers to the capacity to monitor, self-correct, and regulate behaviour. Effective performance is dependent on adequate monitoring to identify and revise mistakes. Similar to Lezak (1995), Anderson (2002) described an executive control system that included four domains including attentional control, cognitive flexibility, goal- setting, and information processing. Although the labels Anderson (2002) used are different than Lezak (1995), closer inspection reveals substantial overlap between the two models. In Anderson’s (2002) model, attentional control refers to the ability to focus attention for prolonged periods as well as the capacity to selectively attend to certain stimuli and inhibit prepotent responses. Moreover, Anderson notes that attentional control involves the monitoring and regulation of actions, which aligns closely with Lezak’s notion of purposive action. Similarly, Anderson’s (2002) description of cognitive flexibility shares considerable overlap with Lezak’s effective performance. Further commonalities are evident between Anderson’s (2002) goal-setting and Lezak’s (1995) volition and planning processes. Anderson includes planning actions in advance and approaching tasks in an efficient and strategic manner under the domain of goal-setting, whereas Lezak makes a more explicit distinction between the ability to formulate a goal (i.e. volition) and the capacity to identify and organize the necessary actions for achieving a goal (i.e. planning). The final domain in Anderson’s model is information processing, which refers to the efficiency and speed of output. Unlike the other three domains, information processing is not reflected in the Lezak’s (1995) framework. A third example of an early theoretical model of EF includes Zelazo’s problem- solving framework (Zelazo, Carter, Reznick, & Frye, 1997). Rather than describing specific domains of EF, Zelazo and colleagues emphasized four distinct phases of problem solving including problem representation, planning, execution, and evaluation. Despite taking a more functional approach than the models described earlier, the executive processes that support each phase of Zelazo’s problem-solving framework share many similarities with the broad domains identified by Lezak (1995) and Anderson (2002). For example, the execution phase of Zelazo’s framework involves maintaining an appropriate sequence of steps in memory in order to perform those steps as specified during the planning phase. These cognitive processes closely resemble what Lezak (1995) referred to as planning and purposive action. In his review of theoretical models of EF, Barkley (2012) counted 33 different constructs that had been described under the rubric of EF. He emphasized that the idiosyncratic use of terminology created confusion regarding similarities and differences that existed between models (e.g. the breadth or relative importance of cognitive
24 2. Conceptualization and Measurement of EF skills processes being considered). Moreover, he spurned the overly descriptive nature of most theoretical models of EF, which he maintained have undermined efforts to test their relative utility. For our purposes, it is noteworthy that theoretical models of EF resulted in a proliferation of heuristics and terminology that were not easily integrated. As a counterpoint to the plurality of ideas that stemmed from theoretical models of EF, the contemporary EF literature has prioritized the use of factor analytic methods and increasingly focused on a narrower set of cognitive processes that are more consistently applied across studies.
Dimensionality of Executive Functions Beginning with the seminal work of Miyake and colleagues, factor analytic techniques have ascended as the dominant approach for testing the dimensionality or structure of EF (Miyake et al., 2000). Factor analytic studies typically involve the administration of a battery of performance-based tasks to (relatively) large samples of participants. The selection of tasks is informed by the number and nature of subdomains of EF that are of interest. For example, Stroop, go/no-go, and flanker tasks may be administered as specific instantiations of the construct of inhibitory control, while N-back, backward digit span, and sentence span tasks may be administered to represent working memory skills. Consistent with measurement theory, factor analytic studies implicitly assume that EF constructs are latent variables that cannot be directly measured but can be inferred based on the shared variation across a set of tasks (e.g. a child’s inhibitory control is manifested by their performance across Stroop, go/no-go, and flanker tasks). Factor analytic methods (and latent variable models more generally) can be used to test whether and when (in development) subdomains of EF can be reliably distinguished from each other, as well as to empirically define subdomains of EF. Karr and colleagues recently conducted a systematic review and re-analysis of 46 studies that used confirmatory factor models to test the dimensionality of EF (Karr et al., 2018). Consistent with previous individual studies (e.g. Lee, Bull, & Ho, 2013; Shing et al., 2010), Karr and colleagues concluded that EF skills were largely undifferentiated in early childhood (unidimensional structure) but that they become increasingly well differentiated (multidimensional structure) across development, with inhibitory control, working memory, and cognitive flexibility emerging as dissociable but correlated subdomains. The age or developmental period in which EF skills become differentiated is not yet clear and inconsistencies in the order or timing during which differentiationoccurs abound. Methodological variations across studies (e.g. the number and ages of participants; the number and nature of tasks for each subdomain that were included) undoubtedly contribute to these differences in conclusions. The important point is that that factor analytic studies have become the de facto standard for defining subdomains of EF and testing their structure. A relatively recent development in the factor analytic literature of EF tasks has involved the introduction of bifactor and hierarchical models. Miyake and Friedman
Dimensionality of Executive Functions 25
(2012) published a highly influential manuscript in which they proposed a ‘unity and diversity’ framework for understanding EF. Specifically, they fit a bifactor confirmatory factor model to a battery of performance-based EF tasks, such that individual tasks loaded onto a general EF factor, as well as specific factors that represented subdomains of EF (i.e. updating, shifting, and inhibition). They proposed that the general factor represented the ‘unity’ of EF, which was defined as that variance that was shared across all updating, shifting, and inhibitory control tasks. They proposed that the specific factors represented the ‘diversity’ of EF, which were defined by the variation that was shared among the updating (working memory), inhibitory control, and shifting factors (net of the variance that was common across all tasks). It is noteworthy that the current conceptualization of EF skills is increasingly directly informed by factor analytic and other latent variable models. We see two problems with the current emphasis on factor analytic models of EF skills. First, we have raised statistical concerns about the appropriateness of using factor analytic methods with EF task data (Willoughby, Holochwost, Blanton, & Blair, 2014; Willoughby, 2014; Willoughby, Blair, & Family Life Project, 2016). Although we do not repeat those concerns here, the crux of the problem has to do with consistently weak correlations between performance-based tasks that purportedly measure the same construct. When EF tasks are weakly associated, this undermines efforts to define latent constructs on basis of shared variation. Doing so can result in nonsensical results, including implausible large stability estimates (see e.g. Willoughby et al., 2017). Second, factor analytic studies require that multiple (ideally three or more) performance-based tasks be administered for each subdomain of interest. Practically, this means that nine or more tasks should be administered to test questions about whether updating, shifting, and inhibitory control are distinct constructs. If finer grained distinctions are of interest, more tasks are required (e.g. ideally six tasks would be required to empirically distinguish visual-spatial from verbal subdimensions of working memory). The ability to test these distinctions using factor analytic methods requires an extensive number of tasks, which rapidly becomes infeasible due to time and cost constraints, as well as test burden for participants (especially for young children). Constraints on the number of tasks that can be administered similarly limit the breadth of constructs that can be considered. Despite these concerns, one of the potential benefits of factor analytic studies has been to facilitate a common parlance and unified empirical approach for representing EF skills. The tripartite model of EF (inhibitory control, working memory/ updating, and cognitive flexibility) that emerged from factor analytic studies has become widely adopted in the field, which overcomes earlier criticisms of theoretical models that perpetuated differing terminology. A potential limitation of this work has been the narrowing in scope of the cognitive processes that are considered part of EF. The tripartite model of EF has become reified to the point that many consider these subdomains as the totality or at least primary domains of EF. The tripartite model of EF does not represent the breadth of cognitive processes that were initially attributed to EF (e.g. Anderson, 2002; Lezak, 1995; Zelazo et al., 1997). As we elaborate next, the
26 2. Conceptualization and Measurement of EF skills narrowing of the scope of EF skills has complicated efforts to clarify how EF is related to conceptually related constructs (e.g. metacognition).
Developmental Considerations Questions related to the development of EF skills have taken multiple forms. As described earlier, one set of questions focused on developmental changes in the organization ordimensionality of EF skills. Most, but not all, studies have concluded that EF skills are undifferentiated in early childhood but become increasingly differentiated in middle childhood and adolescence (Karr et al., 2018). The inconsistency in results about when EF skills become differentiated complicates a clear summary. The most common explanation for why EF skills become differentiated with advancing age is a developmental shift from more diffuse to more focal cortical activity, as well as changes in the specialization of neural networks to support specific cognitive processes (Durston et al., 2006; Rubia et al., 2006; Wang et al., 2019). Although conceptually appealing, we are not aware of any specific empirical studies that have directly related developmental changes in the structure of EF skills to corresponding changes in neural network organization. The most frequently asked developmental questions are related to age-related improvements in EF skills. These studies were initially conceptualized as investigations of ‘maturation changes in frontal lobe functions’, and the emphasis was on delineating age-graded improvements in EF task performance (e.g. Levin et al., 1991; Welsh & Pennington, 1988). A meta-analytic summary of early studies documented pronounced developmental differences in EF task performance between younger children, older children, and adolescents (Romine & Reynolds, 2005). Similar conclusions related to the general functional form of improvement emerged from large- sample studies that focus on age-based differences in performance on specific EF tasks (e.g. Conners, Epstein, Angold, & Klaric, 2003; Weintraub et al., 2013). Studies that involve repeated measures designs and that involve performance-based assessments have been less common and generally limited to shorter periods of time. However, these studies have tended to reinforce the idea that EF skills are rapidly improving during distinct developmental periods and have contributed new information regarding the rank order stability of EF skills across time (i.e. the relative position of individuals on EF assessments across measurement occasions), which is moderately strong (e.g. Boelema et al., 2014; Lensing & Elsner, 2018; Wiebe, Sheffield, & Espy, 2012; Willoughby et al., 2016). Developmental improvements in EF task performance are presumed to reflect corresponding changes in brain activation in the neural networks that support EF skills (Jurado & Rosselli, 2007; Ordaz, Foran, Velanova, & Luna, 2013). In addition to changes in the differentiation of EF skills and increased efficiency of specific cognitive processes, the development of EF skills also involves the increased capabilities on the part of children to set goals, flexibly adapt to varied task demands,
Developmental Considerations 27
and develop and employ strategies that are optimally suited to accomplishing goals or responding to task demands. Although less frequently discussed, these more qualitative changes in EF skill are essential for understanding EF skill development. Munakata and colleagues described three qualitative shifts in the development of EF skills (Munakata, Snyder, & Chatham, 2012). Underlying each of the transitions is the developing capacity to actively maintain increasingly robust and abstract goal representations. The first transition, which occurs in early childhood, is marked by the emerging ability of children to avoid perseverating and overcome habits. Improvements in the ability to maintain goal-relevant information supports increasingly flexible goal-oriented behaviours, instead of habitual responses, that can be generalized to meet novel task demands (e.g. sorting objects based on a new abstract rule when instructed). The second transition, which occurs during the transition from early to middle childhood, is marked by a shift towards increasingly proactive control in response to anticipated challenges. Rather than responding on an as-needed basis, children begin to prepare for future challenges by adopting proactive strategies, such as planning in advance, that support performance in the face of delay or distraction. The third transition, which occurs in late childhood and adolescence, is marked by an increase in self-initiated and self-directed activities. The development of abstract representations facilitates the transition from exogenous to endogenous control by guiding the selection and switching processes that support self-directed behaviour (e.g. sorting cards on the basis of a self-generated abstract rule or switching among self-generated categories). Chevalier (2015) similarly described the development of EF not simply as quantitative increases in greater control strategies but rather as the emergence of more optimal control strategies. His work and that of his colleagues has leveraged thoughtful experimental manipulations and multimethod assessment approaches to help reveal qualitative changes in EF skill development that would not otherwise be obvious (e.g. Chevalier, Blaye, & Maintenant, 2014; Chevalier, Chatham, & Munakata, 2014; Chevalier, Huber, Wiebe, & Espy, 2013; Chevalier et al. 2014). Chevalier and colleagues have described how an expanded repertoire of EF skills and control strategies become matched to an understanding of specific task demands and personal state variables. From this vantage, developmental improvements in EF skills reflect a growing ability on the part of children to recognize internal states and external task demands and to flexibly use EF skills in situationally specific and personally advantageous ways (see Chrysikou, Weber, & Thompson-Schill, 2014). A final developmental question has focused on the staged nature of EF skill acquisition. For example, Garon and colleagues described a progression of cognitive processes across the first five years of life. Specifically, they proposed that fundamental developments of attention precede the emergence of rudimentary forms of EF skills (working memory: holding a simple idea in mind; inhibitory control: simple delayed responding), which in turn precede and contribute to more nuanced EF skills (working memory: manipulating information in mind; inhibitory control: inhibiting prepotent responses; cognitive flexibility: maintaining and shifting attentional focus)
28 2. Conceptualization and Measurement of EF skills that are increasingly used in concert (Garon, Bryson, & Smith, 2008). Romine and Reynolds’ (2005) meta-analysis of studies that spanned middle childhood and adolescence indicated that whereas inhibitory control and attentional perseverance skills exhibited appreciable improvements in middle childhood but plateaued in adolescence, fluency and planning skills continued to improve throughout adolescence. Similarly, in a conceptual summary of lifespan studies, De Luca and Leventer (2008) illustrated the different time courses and sequences of EF skill acquisition and decline. Related to ideas about the staged progression of EF skills is the idea that EF skills are hierarchically organized. The notion that EF is hierarchically organized has been used to convey a few distinct ideas. In some cases, the emphasis is on how rudimentary forms of EF skills precede and ‘give rise’ to the emergence of more complex forms of these same skills (e.g. Garon et al., 2008). In other instances, hierarchical organization refers to the idea that different aspects of EF skills become integrated and used together to better address a particular problem or challenges (Chevalier, 2015). In still other cases, hierarchical organization refers to the idea that developmental improvements in foundational EF skills (i.e. inhibitory control, working memory, and cognitive flexibility) facilitate the emergence of higher order cognitive processes that are distinct from EF, including fluid intelligence, reasoning, and problem solving (see Diamond, 2013, especially Figure 4). Although we do not try to adjudicate these differences, questions about the hierarchical organization of EF skills have clear implications for how narrowly or broadly one construes the construct of EF. Whereas the earliest conceptualizations of EF skills did not consider nascent forms of attentional processes as relevant to the construct (cf. Garon et al., 2008), they did consider problem solving and fluid reasoning skills as aspects of EF (cf., Diamond, 2013).
Conceptual Considerations In our experience, it is common for researchers to assume that EF skills are a stable attribute of an individual at a point in time, similar to other aspects of cognition (e.g. IQ, receptive vocabulary). Although EF skills are malleable, EF assessments are presumed to index individual differences in trait-level variation. However, the test-retest reliability of EF tasks is often more variable than other types of cognitive assessments (Calamia, Markon, & Tranel, 2013). Moreover, individual EF tasks routinely exhibit poor-to-modest retest reliability, regardless of the age at which they are assessed (Ettenhofer, Hambrick, & Abeles, 2006; Karalunas, Bierman, & Huang-Pollock, 2016; Lowe & Rabbitt, 1998; Muller, Kerns, & Konkin, 2012; Willoughby & Blair, 2011). The consistent observation of modest test-retest reliability for individual EF assessments across the lifespan may signify that EF assessments are capturing a combination of state and trait-level variation. Whereas trait-level variation would be expected to be stable and contribute to stronger test-retest reliability, state level variation would be expected to be variable and contribute to weaker test-retest reliability.
Conceptual Considerations 29
Notably, EF task performance is understood to depend on an individual’s motivational and emotional state, as well as variation in their physiological reactivity. For example, Blair and Raver (2015) described a non-linear association between physiological reactivity and EF. Consistent with the Yerkes-Dodson law, increases in physiological reactivity enhance EF task performance up to a point, after which further increases begin to impair performance. The threshold for the point at which increased physiological reactivity begins to impair EF performance is person (and time) specific. The biological explanation for this phenomenon is based on changes in neurotransmitters (i.e. catecholamines) that modulate PFC activity (Arnsten, 2015; Arnsten, 2009; Datta & Arnsten, 2019). Briefly, Arnsten described how exposure to low (manageable) levels of stress result in increases in catecholamines that support and augment PFC activity (low levels of challenge foster a ‘reflective’ state). In contrast, exposure to high (uncontrollable) levels of stress result in elevated levels of catecholamines that impair PFC activity but support sensory and emotional networks (high levels of challenge foster a ‘reflexive’ state). A related line of research has described the interdependence of executive control (which supports EF skills) and alerting (which supports attentional arousal or vigilance) networks, such that variations in one’s alertness or vigilance can directly impact executive control and by extension EF task performance (Nieuwenhuis & de Kleijn, 2013; Roca, Garcia-Fernandez, Castro, & Lupianez, 2018; Rosenberg et al., 2018). The important point is that individual differences in EF skills partially reflect situational factors that contribute to children’s current attentional and/or emotional state. Situational factors can be as varied as social anxiety related to testing, fatigue related to insufficient sleep, irritability related to hunger, or excitement related to recent peer interactions. The characterization of EF skills as a joint function of trait and state influence is consistent with theoretical ideas about the bidirectional influence of EF skills with other aspects of cognition and emotional state. The dynamic nature in which EF skills both exert top-down influence and simultaneously react to bottom-up influences are part of what makes EF skills functionally important. Although conceptually rich, the dynamics of EF skills do not align well with traditional approaches to psychological measurement. Both questionnaire and performance-based assessment paradigms seek to minimize state variation and maximize trait variation. Moreover, the widespread use of factor analytic techniques defines EF skills as the common variation across tasks (or items), which represents trait-level variation (state level variation is assumed to be measurement error). EF skills contribute to an children’s developing self-regulatory abilities, which are of widespread interest given their contribution to important life outcomes (Mischel et al., 2011; Moffitt et al., 2011). Researchers from different disciplines have emphasized a variety of different cognitive processes that contribute to individual’s self- regulatory capacity. An ongoing struggle in the field involves understanding the similarities and differences in the competing conceptualizations and measurement of cognitive processes that contribute to self-regulation (Bailey & Jones, 2019; Morrison & Grammer, 2016). Lyons and Zelazo (2011) described four conceptually similar
30 2. Conceptualization and Measurement of EF skills domains of cognitive development that contribute to self-regulation, including EF skills, error monitoring, metacognition, and uncertainty monitoring. Despite being conceptually similar, these four domains are studied from different disciplines, rely on different measurement approaches, and represent cognitive processes that operate on different time scales. For example, error monitoring is studied by cognitive neuroscientists and refers to an approach for detecting when a participant becomes aware that they made an error during a cognitive task (typically operationalized as the error related negativity, which is an electrical brain signal that is generated by the anterior cingulate cortex 100–200 milliseconds after an error is made). In contrast, metacognition is studied by cognitive psychologists and educational researchers and refers to the ability to both maintain awareness of and to modify one’s thinking (typically operationalized by self-report questionnaires). Lyons and Zelazo (2011) proposed that developmental improvements in all four domains derived from increases in self- awareness, which permits more explicit opportunities to reflect, plan, monitor, and make course corrections in the service of self-directed activities. Disciplinary differences in measurement approaches, in the time scale at which cognitive processes operate, and in the degree to which individuals are consciously aware of their cognitive processes are all important features for discerning how EF skills compare to related constructs. For example, Roebers recently considered the conceptual overlap between EF skills and metacognition (Roebers, 2017; Roebers & Feurer, 2016). Similarities included shared neurobiological basis (emphasis on PFC contributions), their developmental time course (rapid improvements from early childhood into adolescence), and their contributions to academic performance. Monitoring was identified as a key differentiating feature between EF skills and metacognition. Whereas monitoring is an explicit component of metacognition, it is more implicit in modern conceptualizations of EF. Roebers (2017) proposed that EF skills and metacognition jointly facilitate the broader goals of cognitive self-regulation (i.e. they collectively afford individuals with an increasing capacity to observe, reflect, and alter their own thinking to meet internally and externally defined goals). Whereas EF skills are faster acting, more prominent in early and middle childhood, and less overtly conscious, metacognitive skills are slower acting, more prominent in late childhood and adolescence, and more overtly conscious. In order to be maximally useful, efforts to establish the conceptual similarities and differences between EF skills and related constructs will benefit from empirical scrutiny. Efforts to empirically test conceptual ideas are vulnerable to the jingle-jangle fallacy (Kelley, 1927). The ‘jingle fallacy’ refers to a situation in which two different phenomena are labelled equivalently, which promotes a widespread misunderstanding that these phenomena are conceptually similar. Conversely, the ‘jangle fallacy’ refers to a situation in which two similar (or identical) phenomena are labelled differently, which promotes widespread misunderstanding that these phenomena are conceptually distinct. The jingle-jangle fallacy has been perpetuated in many areas of psychological research (Block, 1995; Marsh et al., 2019; Schnitker, Ratchford, & Lorona, 2019; Weidman, Steckler, & Tracy, 2017)—including, in our opinion, research
References 31
on EF skills. As we noted earlier, performance-based measures of EF skills are weakly associated with questionnaire measures of EF skills (Toplak et al., 2013), yet both approaches are routinely used interchangeably as indicators of EF skills. This is an instance of the jingle fallacy. Alternatively, the Behavior Rating Inventory of Executive Function (BRIEF) combines items to form a Metacognition Index. Similarly, the Metacognitions Questionnaire, which is a widely used behavioural inventory that has child, adolescent, and adult versions, was derived from the Self-Regulatory Executive Function Model (Myers, Solem, & Wells, 2019). Instances of EF questionnaires that include metacognition subscales, and metacognition questionnaires that are informed by models of EF are potential instances of the jangle fallacy. We see clear merit in efforts to integrate conceptually similar constructs and to develop a more standardized taxonomy (e.g. Roebers [2017] efforts to integrate EF skills and metacognitive processes). However, we are not optimistic that these efforts will be useful until the field resolves more fundamental issues regarding the strong role of method variance.
Conclusion For nearly 30 years, researchers from varied disciplines have had interest in EF skills, and multiple disciplinary interest continues to grow. The origins of EF skills were borne out of clinically oriented work among neuropsychologists who served adult patients. Over time, interest has broadened, such that EF skills are now considered an individual differences variable that contributes to adaptive behaviour across the lifespan. The evolution of interest in and thinking about EF skills has resulted in a large literature that is not internally consistent. The neurobiological grounding of EF skills distinguishes them from many conceptually similar constructs that are primarily psychological conventions (e.g. self-control, grit, twenty-first century learning skills). However, varied approaches to measurement and differential objectives for measurement have impeded a shared understanding of what EF skills are and why they are important. We have highlighted key theoretical, conceptual, methodological, and developmental variations in EF skills that are salient in the current literature. We hope that our summary of these issues will facilitate a critical reading of the chapters in this volume.
References Alderman, N., Burgess, P.W., Knight, C., & Henman, C. (2003). Ecological validity of a simplified version of the multiple errands shopping test. Journal of the International Neuropsychological Society, 9(1), 31–44. Anderson, P. (2002). Assessment and development of executive function (EF) during childhood. Child Neuropsychology, 8(2), 71–82. Andres, P. (2003). Frontal cortex as the central executive of working memory: time to revise our view. Cortex, 39(4–5), 871–95.
32 2. Conceptualization and Measurement of EF skills Arnsten, A. (2014). Stress and age impair prefrontal cortical executive function. Biological Psychiatry, 75(9), 279. Arnsten, A.F. (2015). Stress weakens prefrontal networks: molecular insults to higher cognition. Nature Neuroscience, 18(10), 1376–85. Arnsten, A.F.T. (2009). Stress signalling pathways that impair prefrontal cortex structure and function. Nature Reviews Neuroscience, 10(6), 410–22. Baddeley, A. (1998). The central executive: a concept and some misconceptions. Journal of the International Neuropsychological Society, 4(5), 523–6. Bailey, R., & Jones, S.M. (2019). An integrated model of regulation for applied settings. Clinical Child and Family Psychology Review, 22(1), 2–23. Barkley, R.A. (2012). Executive Functions: What They Are, How They Work, and Why They Evolved. New York, NY: Guilford Press. Bennett, P.C., Ong, B., & Ponsford, J. (2005). Measuring executive dysfunction in an acute rehabilitation setting: using the dysexecutive questionnaire (DEX). Journal of the International Neuropsychological Society, 11(4), 376–85. Blair, C., & Raver, C.C. (2015). School readiness and self-regulation: a developmental psychobiological approach. Annual Review of Psychology, 63(66), 711–31. Block, J. (1995). A contrarian view of the five-factor approach to personality description. Psychological Bulletin, 117(2), 187–215. Boelema, S.R., Harakeh, Z., Ormel, J., Hartman, C.A., Vollebergh, W.A.M., & van Zandvoort, M.J.E. (2014). Executive functioning shows differential maturation from early to late adolescence: longitudinal findings from a TRAILS study. Neuropsychology, 28(2), 177–87. Buchanan, T. (2016). Self-report measures of executive function problems correlate with personality, not performance-based executive function measures, in nonclinical samples. Psychological Assessment, 28(4), 372–85. doi:10.1037/pas0000192 Burgess, P.W., Alderman, N., Forbes, C., Costello, A., Coates, L.M.A., Dawson, D.R., . . . & Channon, S. (2006). The case for the development and use of “ecologically valid” measures of executive function in experimental and clinical neuropsychology. Journal of the International Neuropsychological Society, 12(2), 194–209. Calamia, M., Markon, K., & Tranel, D. (2013). The robust reliability of neuropsychological measures: meta- analyses of test- retest correlations. Clinical Neuropsychologist, 27(7), 1077–105. Carlson, S.A. (2005). Developmentally sensitive measures of executive function in preschool children. Developmental Neuropsychology, 28(2), 595–616. Castellanos, I., Kronenberger, W.G., & Pisoni, D.B. (2018). Questionnaire-based assessment of executive functioning: psychometrics. Applied Neuropsychology-Child, 7(2), 93–109. Chan, R.C.K., Shum, D., Toulopoulou, T., & Chen, E.Y.H. (2008). Assessment of executive functions: review of instruments and identification of critical issues. Archives of Clinical Neuropsychology, 23(2), 201–16. Chevalier, N. (2015). The development of executive function: toward more optimal coordination of control with age. Child Development Perspectives, 9(4), 239–44. Chevalier, N., Blaye, A., & Maintenant, C. (2014). Goal representation in children’s executive control. Psychologie Francaise, 59(1), 5–20. Chevalier, N., Chatham, C.H., & Munakata, Y. (2014). The practice of going helps children to stop: the importance of context monitoring in inhibitory control. Journal of Experimental Psychology-General, 143(3), 959–65. Chevalier, N., Huber, K.L., Wiebe, S.A., & Espy, K.A. (2013). Qualitative change in executive control during childhood and adulthood. Cognition, 128(1), 1–12. Chevalier, N., James, T.D., Wiebe, S.A., Nelson, J.M., & Espy, K.A. (2014). Contribution of reactive and proactive control to children’s working memory performance: insight from
References 33 item recall durations in response sequence planning. Developmental Psychology, 50(7), 1999–2008. Chrysikou, E.G., Weber, M.J., & Thompson-Schill, S.L. (2014). A matched filter hypothesis for cognitive control. Neuropsychologia, 62, 341–55. Chudasama, Y. (2011). Animal models of prefrontal- executive function. Behavioral Neuroscience, 125(3), 327–43. Conners, C.K., Epstein, J.N., Angold, A., & Klaric, J. (2003). Continuous performance test performance in a normative epidemiological sample. Journal of Abnormal Child Psychology, 31(5), 555–62. Datta, D., & Arnsten, A.F.T. (2019). Loss of prefrontal cortical higher cognition with uncontrollable stress: molecular mechanisms, changes with age, and relevance to treatment. Brain Sciences, 9(5), 113. De Luca, C.R., & Leventer, R.J. (2008). Developmental trajectories of executive functions across the life span. In V. Anderson, R. Jacobs, & P.J. Anderson (Eds.). Executive Functions and the Frontal Lobes (pp. 22–56). New York, NY: Taylor & Francis. Delis, D.C., Kaplan, E., & Kramer, J.H. (2001). Delis-Kaplan Executive Function System (D- KEFS). San Antonio, TX: The Psychological Corporation. Diamond, A. (2013). Executive functions. Annual Review of Psychology, 63(64), 135–68. Durston, S., Davidson, M.C., Tottenham, N., Galvan, A., Spicer, J., Fossella, J.A., & Casey, B.J. (2006). A shift from diffuse to focal cortical activity with development. Dev Sci, 9(1), 1–8. Ettenhofer, M.L., Hambrick, D.Z., & Abeles, N. (2006). Reliability and stability of executive functioning in older adults. Neuropsychology, 20(5), 607–13. Fiske, A., & Holmboe, K. (2019). Neural substrates of early executive function development. Developmental Review, 52, 42–62. Fjell, A.M., Walhovd, K.B., Brown, T.T., Kuperman, J.M., Chung, Y., Hagler, D.J., Jr., . . . & Genetics, S. (2012). Multimodal imaging of the self-regulating developing brain. Proceedings of the National Academy of Sciences of the United States of America, 109(48), 19620–5. Garon, N., Bryson, S.E., & Smith, I.M. (2008). Executive function in preschoolers: a review using an integrative framework. Psychological Bulletin, 134(1), 31–60. Gioia, G.A., Espy, K.A., & Isquith, P.K. (2003). The Behavior Rating Inventory of Executive Function-Preschool version (BRIEF-P). Odessa, FL: Psychological Assessment Resources. Gioia, G.A., Isquith, P.K., Guy, S.C., Kenworthy, L., & Baron, I.S. (2000). Test review: behavior rating inventory of executive function. Child Neuropsychology, 6(3), 235–8. Grodzinsky, G.M., & Diamond, R. (1992). Frontal lobe functioning in boys with attention- deficit hyperactivity disorder. Developmental Neuropsychology, 8(4), 427–45. Hackman, D.A., & Farah, M.J. (2009). Socioeconomic status and the developing brain. Trends in Cognitive Sciences, 13(2), 65–73. Hackman, D.A., Farah, M.J., & Meaney, M.J. (2010). Socioeconomic status and the brain: mechanistic insights from human and animal research. Nature Reviews Neuroscience, 11(9), 651–9. Hughes, C. (2011). Changes and challenges in 20 years of research into the development of executive functions. Infant and Child Development, 20(3), 251–71. Hynd, G.W., Morgan, A.E., Edmonds, J.E., Black, K., Riccio, C.A., & Lombardino, L. (1995). Reading disabilities, comorbid psychopathology, and the specificity of neurolinguistic deficits. Developmental Neuropsychology, 11(3), 311–22. Isquith, P.K., Roth, R.M., & Gioia, G. (2013). Contribution of rating scales to the assessment of executive functions. Applied Neuropsychology-Child, 2(2), 125–32. Isquith, P.K., Roth, R.M., Kenworthy, L., & Gioia, G. (2014). Contribution of rating scales to intervention for executive dysfunction. Applied Neuropsychology-Child, 3(3), 197–204. Jurado, M.B., & Rosselli, M. (2007). The elusive nature of executive functions: a review of our current understanding. Neuropsychology Review, 17(3), 213–33.
34 2. Conceptualization and Measurement of EF skills Karalunas, S.L., Bierman, K.L., & Huang-Pollock, C.L. (2016). Test-retest reliability and measurement invariance of executive function tasks in young children with and without ADHD. Journal of Attention Disorders, 24(13), 1891–904. Karr, J.E., Areshenkoff, C.N., Rast, P., Hofer, S.M., Iverson, G.L., & Garcia-Barrera, M.A. (2018). The unity and diversity of executive functions: A systematic review and re-analysis of latent variable studies. Psychological Bulletin, 144(11), 1147–85. Kelley, E.L. (1927). Interpretation of Educational Measurements. Yonkers, NY: World. Korkman, M., Kirk, U., & Kemp, S. (1998). NEPSY: A Developmental Neuropsychological Assessment Manual. San Antonio, TX: Psychological Corporation. Koziol, L.F., Budding, D.E., & Chidekel, D. (2012). From movement to thought: executive function, embodied cognition, and the cerebellum. Cerebellum, 11(2), 505–25. Kramer, J.H. (2014). Special series introduction: NIH EXAMINER and the assessment of executive functioning. Journal of the International Neuropsychological Society, 20(1), 8–10. Lee, K., Bull, R., & Ho, R.M. (2013). Developmental changes in executive functioning. Child Dev, 84(6), 1933–53. Leisman, G., Moustafa, A.A., & Shafir, T. (2016). Thinking, walking, talking: integratory motor and cognitive brain function. Frontiers of Public Health, 4, 94. Lensing, N., & Elsner, B. (2018). Development of hot and cool executive functions in middle childhood: Three-year growth curves of decision making and working memory updating. Journal of Experimental Child Psychology, 173, 187–204. Levin, H.S., Culhane, K.A., Hartmann, J., Evankovich, K., Mattson, A.J., Harward, H., . . . & Fletcher, J.M. (1991). Developmental-changes in performance on tests of purported frontal- lobe functioning. Developmental Neuropsychology, 7(3), 377–95. Lezak, M. (1995). Neuropsychological Assessment (3rd Ed.). New York, NY: Oxford University Press. Lowe, C., & Rabbitt, P. (1998). Test/re-test reliability of the CANTAB and ISPOCD neuropsychological batteries: theoretical and practical issues. Neuropsychologia, 36(9), 915–23. Lumsden, J., Edwards, E.A., Lawrence, N.S., Coyle, D., & Munafo, M.R. (2016). Gamification of cognitive assessment and cognitive training: a systematic review of applications and efficacy. JMIR Serious Games, 4(2), e11. Lyons, K.E., & Zelazo, P.D. (2011). Monitoring, metacognition, and executive function: elucidating the role of self-reflection in the development of self-regulation. Advances in Child Development and Behavior, 40, 379–412. Marsh, H.W., Pekrun, R., Parker, P.D., Murayama, K., Guo, J., Dicke, T., & Arens, A.K. (2019). The murky distinction between self-concept and self-efficacy: beware of lurking jingle- jangle fallacies. Journal of Educational Psychology, 111(2), 331–53. McAuley, T., Chen, S., Goos, L., Schachar, R., & Crosbie, J. (2010). Is the behavior rating inventory of executive function more strongly associated with measures of impairment or executive function? Journal of the International Neuropsychology Society, 16(3), 495–505. McClelland, M.M., & Cameron, C.E. (2019). Developing together: The role of executive function and motor skills in children’s early academic lives. Early Childhood Research Quarterly, 46, 142–51. McCoy, D.C. (2019). Measuring young children’s executive function and self-regulation in classrooms and other real-world settings. Clinical Child and Family Psychology Review, 22(1), 63–74. Mischel, W., Ayduk, O., Berman, M.G., Casey, B.J., Gotlib, I.H., Jonides, J., . . . & Shoda, Y. (2011). ‘Willpower’ over the life span: decomposing self-regulation. Social Cognitive and Affective Neuroscience, 6(2), 252–6. Miyake, A., & Friedman, N.P. (2012). The nature and organization of individual differences in executive functions: four general conclusions. Current Directions in Psychological Science, 21(1), 8–14.
References 35 Miyake, A., Friedman, N.P., Emerson, M.J., Witzki, A.H., Howerter, A., & Wager, T.D. (2000). The unity and diversity of executive functions and their contributions to complex ‘frontal lobe’ tasks: a latent variable analysis. Cognitive Psychology, 41(1), 49–100. Moffitt, T.E., Arseneault, L., Belsky, D., Dickson, N., Hancox, R.J., Harrington, H., . . . & Caspi, A. (2011). A gradient of childhood self-control predicts health, wealth, and public safety. Proceedings of the National Academy of Sciences of the United States of America, 108(7), 2693–8. Morrison, F.J., & Grammer, J.K. (2016). Conceptual clutter and measurement mayhem: proposals for cross disciplinary integration in conceptualizing and measuring executive function. In J. Griffin, L. Freund, & P. McCardle (Eds.). Executive Function in Preschool Age Children: Integrating Measurement, Neurodevelopment and Translational Research (pp. 327– 348). Washington DC: American Psychological Association Press. Muller, U., Kerns, K.A., & Konkin, K. (2012). Test-retest reliability and practice effects of executive function tasks in preschool children. Clinical Neuropsychology, 26(2), 271–87. Munakata, Y., Snyder, H.R., & Chatham, C.H. (2012). Developing cognitive control: three key transitions. Current Directions in Psychological Science, 21(2), 71–7. Myers, S.G., Solem, S., & Wells, A. (2019). The metacognitions questionnaire and its derivatives in children and adolescents: a systematic review of psychometric properties. Frontiers in Psychology, 10, 1871. Naglieri, J.A., & Goldstein, S. (2004–2015). Comprehensive Executive Function Inventory. Multi-Health Systems. Available at: https://storefront.mhs.com/collections/cefi Negut, A., Matu, S.A., Sava, F.A., & David, D. (2016). Virtual reality measures in neuropsychological assessment: a meta-analytic review. Clinical Neuropsychology, 30(2), 165–84. Nieuwenhuis, S., & de Kleijn, R. (2013). The impact of alertness on cognitive control. Journal of Experimental Psychology: Human Perception and Performance, 39(6), 1797–801. Nilsen, E.S., Huyder, V., McAuley, T., & Liebermann, D. (2017). Ratings of Everyday Executive Functioning (REEF): a parent-report measure of preschoolers’ executive functioning skills. Psychological Assessment, 29(1), 50–64. Noble, K.G., Houston, S.M., Brito, N.H., Bartsch, H., Kan, E., Kuperman, J.M., . . . & Sowell, E.R. (2015). Family income, parental education and brain structure in children and adolescents. Nature Neuroscience, 18(5), 773–8. Norman, D.A., & Shallice, T. (1986). Attention to action: willed and automatic control of behaviour. In R.J. Davidson, G.E. Schwartz, & D. Shapiro (Eds.). Consciousness and Self- Regulation: Advances in Research and Theory. (pp. 1–18). New York, NY: Plenum Press. Nyongesa, M.K., Ssewanyana, D., Mutua, A.M., Chongwo, E., Scerif, G., Newton, C., & Abubakar, A. (2019). Assessing executive function in adolescence: a scoping review of existing measures and their psychometric robustness. Frontiers in Psychology, 10, 311. Ordaz, S.J., Foran, W., Velanova, K., & Luna, B. (2013). Longitudinal growth curves of brain function underlying inhibitory control through adolescence. Journal of Neuroscience, 33(46), 18109–24. Parsons, T.D. (2015). Virtual reality for enhanced ecological validity and experimental control in the clinical, affective and social neurosciences. Frontiers in Human Neuroscience, 9, 660. Parsons, T.D. (2016). Clinical Neuropsychology and Technology: What’s New and How We Can Use It. Cham, Switzerland: Springer. Parsons, T.D., Duffield, T., & Asbee, J. (2019). A comparison of virtual reality classroom continuous performance tests to traditional continuous performance tests in delineating ADHD: a meta-analysis. Neuropsychology Review, 29(3), 338–56. Petersen, S.E., & Posner, M.I. (2012). The attention system of the human brain: 20 years after. Annual Review of Neuroscience, 35, 73–89. Petrides, M., & Milner, B. (1982). Deficits on subject-ordered tasks after frontal-and temporal- lobe lesions in man. Neuropsychologia, 20(3), 249–262.
36 2. Conceptualization and Measurement of EF skills Rand, D., Katz, N., & Weiss, P.L. (2007). Evaluation of virtual shopping in the VMall: comparison of post-stroke participants to healthy control groups. Disability and Rehabilitation, 29(22), 1710–19. Roca, J., Garcia-Fernandez, P., Castro, C., & Lupianez, J. (2018). The moderating effects of vigilance on other components of attentional functioning. Journal of Neuroscience Methods, 308, 151–61. Roebers, C.M. (2017). Executive function and metacognition: towards a unifying framework of cognitive self-regulation. Developmental Review, 45, 31–51. Roebers, C.M., & Feurer, E. (2016). Linking executive functions and procedural metacognition. Child Development Perspectives, 10(1), 39–44. Romine, C.B., & Reynolds, C.R. (2005). Model of the development of frontal lobe functioning: findings from a meta-analysis. Applied Neuropsychology, 12(4), 190–201. Rosenberg, M.D., Hsu, W.T., Scheinost, D., Todd Constable, R., & Chun, M.M. (2018). Connectome-based models predict separable components of attention in novel individuals. Journal of Cognitive Neuroscience, 30(2), 160–73. Roth, R.M., Isquith, P.K., Gioia, G.A., & Widows, M. (2005). Development of the behavior rating inventory of executive function-adult version. Archives of Clinical Neuropsychology, 20(7), 906. Rubia, K., Smith, A.B., Woolley, J., Nosarti, C., Heyman, I., Taylor, E., & Brammer, M. (2006). Progressive increase of frontostriatal brain activation from childhood to adulthood during event-related tasks of cognitive control. Human Brain Mapping, 27(12), 973–93. Schnitker, S.A., Ratchford, J.L., & Lorona, R.T. (2019). How can joy escape jingle-jangle? Virtue and telos conceptualizations as alternative approaches to the scientific study of joy. Journal of Positive Psychology, 15, 44–8. Shah, A.K., Mullainathan, S., & Shafir, E. (2012). Some consequences of having too little. Science, 338(6107), 682–5. Shallice, T. (1982). Specific impairments of planning. Philosophical Transactions of the Royal Society B: Biological Sciences, 298(1089), 199–209. Shallice, T., & Burgess, P. (1996). The domain of supervisory processes and temporal organization of behaviour. Philosophical Transactions of the Royal Society B: Biological Sciences, 351(1346), 1405–12. Shallice, T., & Burgess, P.W. (1991). Deficits in strategy application following frontal lobe damage in man. Brain, 114 (Pt 2), 727–41. Shing, Y.L., Lindenberger, U., Diamond, A., Li, S.C., & Davidson, M.C. (2010). Memory maintenance and inhibitory control differentiate from early childhood to adolescence. Developmental Neuropsychology, 35(6), 679–97. Silver, C.H. (2014). Sources of data about children’s executive functioning: review and commentary. Child Neuropsychology, 20(1), 1–13. Spiegel, J.A., Lonigan, C.J., & Phillips, B.M. (2017). Factor structure and utility of the behavior rating inventory of executive function-preschool version. Psychological Assessment, 29(2), 172–85. Stuss, D.T. (2011). Functions of the frontal lobes: relation to executive functions. Journal of the International Neuropsychological Society, 17(5), 759–65. Stuss, D.T., & Alexander, M.P. (2000). Executive functions and the frontal lobes: a conceptual view. Psychological Research-Psychologische Forschung, 63(3–4), 289–98. Taylor, H.G., Schatschneider, C., Petrill, S., Barry, C.T., & Owens, C. (1996). Executive dysfunction in children with early brain disease: Outcomes post Haemophilus influenzae meningitis. Developmental Neuropsychology, 12(1), 35–51. Thorell, L.B., & Nyberg, L. (2008). The Childhood Executive Functioning Inventory (CHEXI): a new rating instrument for parents and teachers. Developmental Neuropsychology, 33(4), 536–52.
References 37 Toplak, M.E., West, R.F., & Stanovich, K.E. (2013). Practitioner review: do performance-based measures and ratings of executive function assess the same construct? Journal of Child Psychology and Psychiatry, 54(2), 131–43. Vallat-Azouvi, C., Pradat-Diehl, P., & Azouvi, P. (2012). The Working Memory Questionnaire: a scale to assess everyday life problems related to deficits of working memory in brain injured patients. Neuropsychological Rehabilitation, 22(4), 634–49. van der Fels, I.M., Te Wierike, S.C., Hartman, E., Elferink-Gemser, M.T., Smith, J., & Visscher, C. (2015). The relationship between motor skills and cognitive skills in 4–16 year old typically developing children: a systematic review. Journal of Science and Medicine in Sport, 18(6), 697–703. Vestberg, T., Gustafson, R., Maurex, L., Ingvar, M., & Petrovic, P. (2012). Executive functions predict the success of top-soccer players. PLoS One, 7(4), e34731. Wang, C., Hu, Y., Weng, J., Chen, F., & Liu, H. (2019). Modular segregation of task-dependent brain networks contributes to the development of executive function in children. Neuroimage, 206, 116334. Weidman, A.C., Steckler, C.M., & Tracy, J.L. (2017). The jingle and jangle of emotion assessment: Imprecise measurement, casual scale usage, and conceptual fuzziness in emotion research. Emotion, 17(2), 267–95. Weierink, L., Vermeulen, R.J., & Boyd, R.N. (2013). Brain structure and executive functions in children with cerebral palsy: a systematic review. Research in Developmental Disabilities, 34(5), 1678–88. Weintraub, S., Bauer, P.J., Zelazo, P.D., Wallner-Allen, K., Dikmen, S.S., Heaton, R.K., . . . & Gershon, R.C. (2013). I. Nih Toolbox Cognition Battery (Cb): introduction and pediatric data. Monographs of the Society for Research in Child Development, 78(4), 1–15. Welsh, M.C., & Pennington, B.F. (1988). Assessing frontal lobe functioning in children: views from developmental psychology. Developmental Neuropsychology, 4, 199–230. Wiebe, S.A., Sheffield, T.D., & Espy, K.A. (2012). Separating the fish from the sharks: a longitudinal study of preschool response inhibition. Child Development, 83(4), 1245–61. Willoughby, M., & Blair, C. (2011). Test-retest reliability of a new executive function battery for use in early childhood. Child Neuropsychology, 17(6), 564–79. Willoughby, M., Holochwost, S.J., Blanton, Z.E., & Blair, C.B. (2014). Executive functions: formative versus reflective measurement. Measurement: Interdisciplinary Research and Perspectives, 12(3), 69–95. Willoughby, M.T. (2014). Formative versus reflective measurement of executive function tasks: response to commentaries and another perspective. Measurement: Interdisciplinary Research and Perspectives, 12(4), 173–8. Willoughby, M.T., Blair, C.B., & Family Life Project, I. (2016). Measuring executive function in early childhood: a case for formative measurement. Psychological Assessment, 28(3), 319–30. Willoughby, M.T., Kuhn, L.J., Blair, C.B., Samek, A., & List, J.A. (2017). The test-retest reliability of the latent construct of executive function depends on whether tasks are represented as formative or reflective indicators. Child Neuropsychology, 23(7), 822–37. Wilson, P.H., Ruddock, S., Smits- Engelsman, B., Polatajko, H., & Blank, R. (2013). Understanding performance deficits in developmental coordination disorder: a meta- analysis of recent research. Developmental Medicine and Child Neurology, 55(3), 217–28. Zelazo, P.D., Blair, C.B., & Willoughby, M.T. (2016). Executive Function: Implications for Education. Washington, DC: U.S. Department of Education. Available at: https://files.eric. ed.gov/fulltext/ED570880.pdf Zelazo, P.D., Carter, A., Reznick, J.S., & Frye, D. (1997). Early development of executive function: a problem-solving framework. Review of General Psychology, 1(2), 198–226.
3 Executive Control and the Writer(s)- Within-Community Model Steve Graham
Cognition and Executive Control It is commonly assumed, but not always directly stated by those who view writing through a cognitive lens, that the brain acts to direct and manage the process of writing, while concurrently taking into account contextual demands and making adjustments for them. This implies (see Harris et al., 2018) that writers exert conscious and deliberate control over writing by employing mental operations involving analysis (e.g. sizing up the demands of the writing task, audience, and context), problem solving (e.g. determining the best way to present specific information), decision- making and planning (e.g. selecting or devising a plan of action that meets personal and context goals for writing), reasoning (e.g. considering what information the intended audience will need in order to understand the text), attentional control (e.g. focusing and maintaining attention as well as inhibiting interfering behaviours), and self-regulation (e.g. the flexible application of cognitive resources to meet desired goals and address changing situations as text is produced or new contextual constraints/directions arise). I used the term executive control in this chapter instead of executive functioning. I think this term better represents the combination of executive functioning and self- regulation strategies writers use to exert conscious and deliberate control over writing and its contextual demands. The degree of executive control writers apply varies depending on multiple factors, including the writing task, its importance to the writer, and the writer’s competence (Graham, 2018a, 2018b; Hayes, 1996; Zimmerman & Risemberg, 1997). Take for example the executive control processes applied by a skilled writer such as Irving Wallace when writing a novel (Wallace, 1977). He indicated he applies a variety of mental strategies to help him orchestrate the writing of such a book, including making outlines in his head and on paper, detailing the sequence of the story, developing scenes and fleshing out characters, underlining parts of the text that needed additional work, keeping a detailed chart of progress, instituting revisions in his plans and text, and rereading and modifying his story again and again to make it better. Steve Graham, Executive Control and the Writer(s)-Within-Community Model In: Executive Functions and Writing. Edited by: Teresa Limpo and Thierry Olive, Oxford University Press. © Oxford University Press 2021. DOI: 10.1093/oso/9780198863564.003.0003
Context and Executive Control 39
In contrast, writing can appear relatively simple, involving little executive control, as when we write a note to remember to pick up the laundry. Even when writing appears to be simple, it is not. It requires the use and orchestration of a variety of skills and knowledge (Hayes, 2012), some of which have been automatized by more experienced writers. It also requires decision-making, analyses, and attentional control. For the note to ‘remember to pick up the laundry’, the author must decide what to say and how to say it (decision-making). The idea must be crafted into a grammatically correct statement, with the author selecting words that appropriately convey the idea (decision-making and attentional control). The statement must then be transcribed into text, and the author of the message may examine it to determine if the words are legible enough and spelled correctly enough so the message can be read later (analysis). While the level of executive control exercised in producing this note does not approach the deliberate and conscious control applied by Irving Wallace as mentioned, executive control is still an essential part of writing even when the goal is to create a simple message. Writers can purposefully seek to minimize executive control when writing. For instance, writers can decide to devote little attention and mental effort to writing a text, as can happen when they do not value the writing task (Graham, 2018a, 2018b). Likewise, writers may deliberately forgo analysis and evaluation as they apply a technique like free-writing (Elbow, 1998), writing down whatever comes to mind. Executive control may further be limited because writers have little experience or competence in using such procedures (Scardamalia & Bereiter, 1986), or the use of executive control overtaxes writers’ processing capacity, as can happen with young beginning writers who find virtually all aspects of writing demanding (McCutchen, 1988). Even so, many writing tasks, especially more substantive ones like writing an argument or creating a report, require considerable planning, decision- making, reasoning, monitoring, evaluation, judgement, attentional control, and flexible responding (Harris et al., 2018). Writers can and do exert agency and conscious control over the writing process. They drive and shape what is written, as they decide if they will write, how much effort to commit, what they plan to do, what cognitive resources are applied, what writing tools are used, and how the writing task will proceed (Zimmerman & Risemberg, 1997).
Context and Executive Control Writers’ agency as enacted through executive control is not the only force that influences what is written and how it is composed (Graham, 2018a). Writing is also shaped and constrained by the communities in which it takes place (Graham, 2018b), including how writers apply self-control mechanisms when writing. For example, determining the purpose of a specific writing task (i.e. analysis) depends on the goals, values, norms, and identity privileged by the community in which it is produced. How
40 3. Executive Control and Writer(s)-Within-Community the resulting text is crafted (i.e. decision-making and planning) is influenced by the practices that the writing community commonly applies when composing (Russell, 1997). Consideration of what information is needed by readers (i.e. reasoning) is determined by the audience that is the object of the community’s intentions. The ability of the author to focus and maintain attention while writing (i.e. attentional control) may be enhanced and/or impeded by the social and physical environment of the community (Brandt, 2001). The author’s willingness to adjust initial writing plans and goals (i.e. flexible application of cognitive resources) to meet community writing goals can be affected by the author’s commitment to the community (Bazerman, 2016). How communities that engage in writing influence their members use of executive control when composing varies depending on their purposes, tools for writing, typified actions for creating text, physical and social environments, and collective histories (Graham, 2018a). Take for instance two seventh grade science classes. In one class, students used 10-minute quick writes to generate what they know about a specific science topic. Quick writes typically involve writing about content information for a short period of time. This only took place when a new topic was introduced. There were three rules students must follow (i.e. they must stay on topic, write for the full 10 minutes, and create a single draft). The text they produced, however, was not directly shared with the teacher or other classmates. Further, there were no guidelines or norms for what is considered an acceptable quick write. The teacher’s rationale for these 10-minute quick writes was that they served as a warm-up to get students ready for the new topic being introduced, but this was not directly stated to the students. The second science class also used 10-minute quick writes with the same three rules as mentioned, but the quick writes were used for more than one purpose. This included determining what students know about a new topic (same as in the first class earlier), exploring common misunderstandings in science, and reflecting on what had been learned and still needed to be learn about a topic. For all three of the quick write in the second science class, the teacher shared with students its purpose, modelled how to do it, and provided students with practice applying it as modelled. Once students completed a quick write, they shared what they wrote with another student, who provided them with feedback. The teacher in the second science class also read her students’ quick writes and provided constructive feedback on at least one issue in each quick write and praise on another. In the first science classroom, there are only a few mechanisms that are likely to shape or constrain how students use executive control when creating their quick writes. This is limited to the three rules established (stay on topic, write for 10 minutes, and create a single draft). In the second science class, there are many more features of the community that are likely to impact executive control. For instance, when students are asked to conduct a quick write in the second classroom, they have to determine which type of quick write to apply and why (i.e. analysis, reasoning, and decision-making), whereas options in the first classroom are limited to a single quick write type. Likewise, students in the second classroom are provided with schemas for
Purpose of This Chapter 41
how to construct each type of quick write (i.e. a guide or plan), but students in the first class are only guided by the three rules. Students in the second class are likely to pay attention to the needs of an external audience (i.e. evaluation and reasoning), as they share their quick writes with a peer and the teacher. Such sharing did not occur in the first classroom. It is also important to highlight that features of a community that shape and constrain how executive control is used to accomplish writing goals interact with individual members’ agency, resources, and capabilities. To illustrate, members of a community will differ in their familiarity with how the community operates in terms of writing. Further, some member may purposefully operate against one or more of these operations. Still other members may not have the capabilities to carry out the executive demands for writing sanctioned by the community (Bazerman & Prior, 2005; Swales, 1990).
Purpose of This Chapter The premise that writing, including executive control, involves an interaction between social context and the mental and physical actions of writers has mostly been ignored in conceptualizations of writing (Graham, 2006; Perry, 2012). The current chapter addresses this interactive premise as it applies to executive control in writing. I present a model, the Writer(s)-within-Community model of writing (WWC; Graham, 2018a, 2018b), that proposes that the community in which writing takes place and the cognitive capabilities and resources of those who create it simultaneously and reciprocally influence writing. In presenting this model, I expand the definition and functioning of executive control in it. Most importantly, I explore multiple ways in which context and individual capabilities interact to shape and constrain the use of executive control in writing. I begin my exploration of executive control in the WWC model by presenting its two basic organizing structures: writing community and writers and their collaborators. The WWC model situates writing and the use of executive control in specific writing communities. It is assumed that context influences how writers use executive control, and executive control in turn provides writers with the agency needed to purposefully shape the writing context. It is also assumed that executive control is used by writers to manage cognitive, motivational, and physical resources to meet desired writing goals, and executive control in turn is influenced by the capabilities and resources available to writers. I also present four tenets underlying the operation of the WWC model. These tenets provide an even broader lens for considering how executive control operates in writing communities, as it is assumed that context and writers’ capabilities interact to influence executive control, and executive control is further influenced by the capacity, variability, and development within both the writing community and its members. In the final section of the chapter, I consider implications of the model for future research on executive control.
42 3. Executive Control and Writer(s)-Within-Community The WWC model defines executive control in writing as involving the conscious, deliberate, and thoughtful activation and coordination of intentions (goals for writing), plans (actions to achieve goals), evaluations (monitoring and judging the impact of intentions and plans), and reactions (modifying intentions, plans, and evaluations as needed). This involves exerting control over cognitive functions, emotions, or both, as writers activate, orchestrate, evaluate, and adjust the use of writing skills, processes, knowledge, motivations, and emotions in order to achieve desired writing outcomes and actions (Graham, 2018a). Executive control in writing draws on mental behaviours including reasoning (e.g. inferring what the audience needs to know), problem solving (e.g. determining what voice an audience will respond to best), decision-making (e.g. deciding how to best present information to the audience), analysis (e.g. judging if text is written so that the audience will understand it), and intuition (e.g. immediate understanding of the audience needs without conscious reasoning). Executive control is facilitated by writers’ ability to maintain information in mind as it is acted upon (i.e. working memory), establish attentional control over cognitive and emotional functions (e.g. focusing and maintaining attention as well as inhibiting interfering behaviours), and flexibly shift attentional control as context and task requirements change (Graham, 2018b).
The Writer(s)-Within-Community Model The WWC model (Graham, 2018a, 2018b) assumes that writing is inherently a social enterprise, situated within specific writing communities. This is consistent with previous conceptualizations that view writing as a socialized activity (Barton, 1991; Hull & Schultz, 2001) involving multiple participants, including, writers, collaborators, mentors, teachers, and readers. More specifically, a writing community is a group of people who share a basic set of goals and assumptions and use writing to achieve their purposes. The purposes and assumptions underlying different writing communities are quite varied, and can be clearly expressed or implicitly implied, understood or misunderstood, and emerging, changing, or relatively stable. Each of these scenarios can exist in the same community, as some purposes and assumptions may be articulated and others are not; some members of the community may understand or not understand all of them; and some may be changing, others emerging, and still others unchanged. Examples of writing communities include a senior customer service agent who is mentoring new hires on how to handle email responses from disgruntled customers; a grandparent and grandchild who write stories together; an online website where writers provide support and feedback to each other; and a second grade class where students learn to write. A writing community must include one or more persons engaged in writing and one or more readers. Activities other than writing can occur, and may even be more central to the purpose of the community. As an example, the primary purpose of the
The Writer(s)-Within-Community Model 43
two science classes described earlier was not writing, but members of this community were mutually engaged in using writing to accomplish a desired purpose, making it a writing community as well as a science learning community. As a result, a writing community involves writers (and possibly mentors, teachers, and collaborators) who are accomplishing one or more goals by creating text which is read by one or more persons (real or imaginary). This definition extends to situations where a single writer serves as both author and reader, as when a person writes a personal diary. Writing communities are not enduring bodies. They can exist for a brief period of time, as when two people communicate with each other for two weeks on Facebook, or they can be more durable like the Royal Society of London for Improving Natural Knowledge founded in 1660. Moreover, a single person can and is likely to be a member of many different writing communities. Despite the differences that can exist between writing communities, they share a common set of characteristics which are described here.
Organizing Structure One: Common Features of a Writing Community Purposes. A writing community uses writing to accomplish one or more of its purposes, and these purposes can be quite varied (Freedman, Hull, Higgs, & Booten, 2016). For example, an online fan fiction website provides members a community in which they can use writing to connect with other like-minded individuals, whereas the primary purpose of a workshop for aspiring professional writers is to help them improve their writing. Purposes of a writing community encompass the goals writing is intended to achieve (a tool to facilitate and assess learning in a high school civics course), the value of writing to the community (a local newspaper views their publication as essential because it provides readers with news about their neighbourhoods), and the norms for writing within the community (accuracy in writing is valued in reports written by police officers). It also includes the social practices writing supports (students create a written list of classroom rules) as well as the audience that is the object of the community’s intentions (a graphic comic book created to inspire boys with dyslexia). Purposes further involve motivations for writing created by the community (a third grade teacher sets a positive tone for writing by posting students’ writing on the walls within the classroom), and the stance/identity the community wants to project (Mad Magazine established an identity for humour and sarcasm). Purposes for writing in a community can be relatively simple, as when an adolescent is required to inform parents about his whereabouts by texting them by 9:00pm at night if he is not home yet. They can also be quite complex, as is the case for a national newspaper that establishes goals to report daily events, shape local opinion, entertain readers, and present a left-of-centre perspective. The purposes of writing
44 3. Executive Control and Writer(s)-Within-Community communities are subject to change over time as new conditions arise, whereas the purpose of other writing communities may cease to exist. Members. Writing communities include people who create text (writers and collaborators) and people who serve as an audience for it (Cameron, Hunt, & Linton, 1996). In some writing communities, one or more persons (mentors or teachers) may help other members acquire the knowledge, skills, strategies, dispositions, and modes of action needed to achieve a community’s writing purposes. Membership in writing communities varies from a limited number of participants, such as a couple who writes love notes to each other, to scores of participants, like an influencer who has thousands of twitter followers. Some writing communities restrict who can belong, as is commonly done in a graduate-level writing course, whereas others have few or no restriction on membership (e.g. Scribophile). Members also differ in how frequently they participate in a writing community, their familiarity with its purposes and practices, and their alignment and commitment to the community. Further, members of a writing community differ in their identities as writers and readers as well as their presumed value to the community (Freedman et al., 2016). Members of a community assume different roles and responsibilities (Kalman, 1996). In some instances, members may serve multiple roles, as when they act as a writer, collaborator, mentor, and reader. These same roles may be served by multiple community members, as when several people act as mentors for others. Members can differ in how much power they exercise (Bazerman, 2016), as a community can be organized hierarchical (e.g. classrooms where an adult acts as the teacher), or more horizontally (e.g. writers voluntarily come together to give each other feedback). The way in which power is distributed can impact how a community operates as well as the motivation of members to carry out community writing goals (Moje & Lewis, 2007). Tools. Writing communities use one or more tools to accomplish their purposes. This includes paper and pencil, word processors, and speech to text synthesizers, to identify some common tools (Gabrial, 2008). Newer writing tools may allow community members to create multimodal compositions that contain text, written text, pictures, drawings, videos, narration, emojis, GFFs, and so forth. Other tools like books, journals, and the internet provide resources writers and their collaborators use to acquire information for writing. Digital writing tools further make it possible for community members to seek help from others and share what they write more broadly. The use of writing tools varies within and between writing communities (Yancey, 2009). For example, a writing community composed of a child and parent may use just paper and pencil for some writing tasks, but employ construction paper and crayons for others. Similarly, a chemistry class may use paper and pencil for notetaking, but apply an electronic journal to record observations during an experiment. Writing communities may use tools that assist writers and collaborators in specific ways. This can include word processing programmes that contain software programs that help writers and collaborators with spelling, grammar, word choice, or planning (Morphy & Graham, 2012), or it might include digital tools that provide writers
The Writer(s)-Within-Community Model 45
with feedback on other aspects of writing such as organization and ideation (Shermis et al., 2016). Actions. Actions are the typified practices a writing community develops and uses over time to achieve its purposes (Russell, 1997). This includes the preferred routines members of a community commonly apply to structure the writing environment, distribute responsibility, carry out the process of composing, and facilitate reading of the resulting products. Typified actions also include routines commonly used to manage the physical, social, emotional, and motivational aspects of writing (including negotiating disagreements among community members) as well as to adhere to the goals, norms, values, and stance/identity of the community. The typified actions applied by writing communities are best viewed as temporary and subject to change as new needs and circumstances arise (Many, Fyfe, Lewis, & Mitchell, 1996). To illustrate, a member of a writing community may suggest a new approach or routine, such as making data in a report more visual, which members of the community adopt as a standard practice. Moreover, making a change in some basic aspect of a writing community can lead to changes in the actions commonly used to achieve writing goals. For example, upgrading writing tools from paper and pencil to digital forms of composing can influence multiple aspects of writing in a community, including procedures for providing feedback (e.g. written text is placed in Dropbox where a text can be revised by multiple community members). As a result, the typified actions a community uses to meet its writing purposes are not sealed shut. Instead, they are permeable and flexible. Written products. Writing communities produce products that are written, digital, and/or multimodal. This includes completed and not fully completed writing products as well as artefacts that are used or created when composing. Examples includes plans, notes, drawings, model text, and earlier drafts as well as source material like books, articles, pictures, film, and interviews (Moje, 2009). Within a writing community, these written products can be stored in one or more locations including an office, a computer, or the cloud. Some of a writing community’s products may be viewed as temporary and retained only briefly (a first draft), whereas others may be viewed as more permanent (a final draft) and preserved for longer periods of time. Depending on how the community is structured and its purposes, access to written products and their artefacts may be open to all members or restricted in some way. Physical and social environments. Writing communities are situated in a physical space and a social context (Jones, 1998). The physical space in which writing communities operate include almost any location where people congregate (e.g. classrooms, offices, and homes), digital locales, or both (Johnson, 2001). Where writing takes place influences the work of a writing community in multiple ways (Stedman, 2003). It can impact how a community conceptualizes its writing purposes (e.g. a digital locales make it possible to reach a large audience), how many community members can be present at any given time (e.g. physical locales create structural limits to the number of members that can be present at a time), the form that writing takes (e.g. multimodal text are easier to produce in a digital environment), and how writing
46 3. Executive Control and Writer(s)-Within-Community is enacted (e.g. digital environments make it easier to receive feedback from multiple collaborators). The social context of a community involves the relationships among its members (writers, collaborators, readers, teachers, and mentors). The writing work of community members can be enhanced or impeded by social relationships (Allodi, 2007), sense of belonging and affiliation (Brandt, 2001), stereotypical beliefs about other community members (Kwok, Ganding, Hull, & Moje, 2016), and how power and autonomy are perceived and enacted (Bazerman, 2016). The social context can be supportive, neutral, or hostile; pleasant or unpleasant; cooperative or competitive; and self-governing or controlling. It is commonly believed that writing is facilitated when the social context is pleasant, supportive, cooperative, and encouraging of choice and agency (Graham, Harris, & Santangelo, 2015). The social context can also shape motivation within a writing community (Hidi & Boscolo, 2007). If members of a community view the writing it undertakes as meaningful, socially important, and a collective endeavour, this is likely to create a shared sense of purpose and engagement versus a social context where community members feel disconnected and question the value of the writing undertaken. Collective history. How writing is enacted in a community is shaped by its collective history (Schultz & Fecho, 2000). As writing communities function over time, their business becomes codified (Brandt, 2001; Greeno & Engeström, 2014). To Illustrate, specific writing purposes may become increasingly privileged in a community over time as their value becomes more evident, whereas the importance of other writing purposes may decline or even be eliminated if they are viewed as less valuable. For instance, a history teacher may increasingly incorporate writing tasks into the classroom that promote analysis and interpretation of historical events and issues, while at the same time decreasing the use of writing tasks that operate at a more surface-level, such as completing a journal entry specifying what was learned. In this case, the purpose of writing in this community shifts from a focus on remembering what was learned by identifying it in writing to understanding what happened by analysing it and committing this analysis to text. Collective history creates a writing community where members know how to participate in the same shared writing practices. It impacts all aspects of the community, including purposes, actions, tools, physical and social context, membership, and ultimately what is written. Even so, the collective history of a writing community is not cast in stone. It is open to change from forces inside and outside the community (Dyson, 1999; McCarthy, 1994). Social, cultural, institutional, political, and historical forces. The nature, structure, and collective history of writing communities are moulded by external forces. This includes members’ experiences in other socially-derived communities (Moll, 1990). A writing community is built by individuals who draw on their experiences in other communities, as happens when parents create a writing community at home with their children by appropriating practices occurring at school (Morrow & Young, 1997).
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Writing communities are further influenced by macro-level factors. This includes culture, as illustrated in how the purpose of writing is viewed in Chinese classrooms (i.e. to shape and educate a student’s mind) and classrooms in the United States (i.e. as a means for self-discovery and expression; Li, 1996). It includes institutional and political forces. For instance, writing in classrooms in the United States was shaped by professional institutions such as the Committee of Ten and the National Council of Teachers of English (Sperling & DiPardo, 2008), whereas edicts and mandates from local, state, and federal agencies provide specific guidance on how writing is to proceed in these same classrooms (Graham, Hebert, & Harris, 2011). Finally, historical events impact the purposes and operation of writing communities. With the creation of new writing tools, for instance, writing communities have evolved to take on new purposes (see Hendrix, 2016 and the invention of the printing press). Relationships between the characteristics of a writing community. How the features of a writing community operate in tandem are presented in Figure 3.1. The centre of this figure provides a diagram illustrating how a community’s writing purposes are accomplished through the use of writing tools and the actions of members of the community to create the desired written product. Community members include writer(s) and possible collaborators (this can involve mentors and teachers) who create the written product as well as readers who are the audience for it. Members of
cially-derived Commun ities er So h t O of the Writing Comm uni oses p r ty Pu
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Figure 3.1 Basic components of a writing community.
48 3. Executive Control and Writer(s)-Within-Community the writing community are represented as writers and collaborators in the first ring moving outward from the centre of the figure. When multiple community members are involved in writing, accommodation and coordination are required (indicated by directional arrows between writers and collaborators in the first ring from the central circle of Figure 3.1). To illustrate, when a writer seeks feedback on a composition from a community member, then the author must be willing to accommodate this feedback and consider possible alternatives as well as challenges to the text produced so far. For the feedback to be useful, it must be given in a clear and timely manner. How writers and collaborators achieve the desired purpose(s) of writing via tools and actions depends on multiple interactions among and between the purposes, members, physical/social environment, and collective history of the writing community. The second ring from the centre circle in Figure 3.1 represents these interactions. The arrows show the reciprocal relationships among these variables. The writing that is created by community members reflect one or more of the community’s central purposes for writing. The actualization of these purposes and the resulting written product are influenced by the types of writing the community values, its audiences, as well as the norms, goals, social practices, motivations, and stance/ identity it aspires to achieve. Who creates the desired written products depends on the roles and responsibilities of community members, and their availability, willingness to complete the task, perceived capabilities, identities as writers or collaborators, and commitment to the community. Each of these influences can be mediated by how power is distributed among community members. The physical environment impacts the number of community members who can work on the writing task at a given time, the tools applied, and the form of the goals and resulting written product. The social environment further influences writers and collaborators in multiple ways. For example, the social climate of the community impacts the motivation, engagement, and commitment of community members to carry out the writing task and work together. Additionally, the collective history of the writing community determines its members, writing purposes, writing tools and actions, and physical and social dimensions. Finally, writing communities function in a larger context (see outer ring in Figure 3.1). This involves other socially derived communities, including other communities that write. These communities are interconnected to a greater or lesser degree, depending on their purposes and functions. As a result, the practices, and ongoing operation of a writing community are influenced by members’ experiences in other relevant communities. The functions and operations of a writing community are further impacted by other external forces involving culture, institutions, politics, and history. Writing communities shape and bind executive control. A basic premise underlying the WWC model is that the community in which writing takes place shapes and constrains writing (Graham, 2018b). For example, the goals, writing norms, values, and stance/identity of a writing community influences what individual’s and
The Writer(s)-Within-Community Model 49 WRITER Executive Control • Executive Processes - Intentions - Plans - Evaluation - Reaction • Working Memory • Attention Long-Term Memory Resources
Emotions
Production Processes • Conceptualization • Ideation • Translation • Transcription • Reconceptualization
Modulators Personality Traits
Written Product
Physical State
Figure 3.2 Cognitive mechanisms involved in writing.
their collaborators write and the form that it takes. Similarly, the types of writing tools available in a community impact the form writing takes (e.g. handwritten, digital, multimodal), but who reads it as well. Not only does a writing community shape what is written, but it influences how writers and their collaborators within a community apply executive control to accomplish writing purposes and goals. For instance, how writing is conceptualized within a community through its purposes (e.g. goals, norms, and values) not only provides direction, but constrains how members of the community determine their intentions (i.e. goals) for a particular writing project. The typified actions commonly used when writing influence how community members apply cognitive resources when writing, as some actions are privileged and others are not. The social context of a community impacts how well members can exert control over emotional responses when writing, as this is easier to do in a positive and supporting environment than a punitive and hostile one. The characteristics of community members, such as familiarity with a community’s practice of placing great store in the power of revising, can result in differential application of executive tools involving monitoring and evaluation.
Organizing Structure Two: Writers and Their Collaborators Writing in a community is accomplished by its members for its audiences. This includes writers, their collaborators (including mentors and teachers), and the intended audience (readers). The cognitive architecture of these individuals is presented in Figure 3.2. Only a single individual (the writer) is represented in this figure, but the members of a writing community, regardless of their roles, share the same basic
50 3. Executive Control and Writer(s)-Within-Community cognitive architecture. As a result, this representation applies to all members of the community, but not all of the cognitive processes and resources described apply to all members (e.g. readers do not use production processes unless they are using writing for a purpose like taking notes). Similarly, depending on their role, different community members draw on different forms of knowledge, beliefs, emotions, and executive control to carry out their specific roles. For example, a mentor or teacher draws on knowledge of their students or mentees, effective teaching practices, and how to arrange and manage the teaching environment. For the purpose of brevity, I refer only to writers when talking about cognitive capabilities and resources in this section of the chapter]. The WWC model not only proposes that context shapes and constrains writing, but stresses that writing is simultaneously shaped and bound by the agency, capability, and resources of those who produce it. This is achieved by writers consciously and deliberately establishing their own goals for their writing (usually in concert with community goals), and activating, orchestrating, and adjusting as needed writing production processes, knowledge, and beliefs to achieve these desired goals. These processes can further alter and be altered by an individual writer’s emotional responses, personality traits, and physiological states. Production processes. Writing involves production processes. These are the mental and physical operations writers apply to produce text. They include five processes. One process is conceptualization or the creation of a mental representation of the writing task (Hayes, 2012). This conceptualization is shaped by the writing community (e.g. its purposes), goals formed by the writer, or some combination of the two. This mental conceptualization can be represented in multiple ways (e.g. remembered goals, a written plan, diagrams, pictures, and text produced so far), and it acts as a guide for other production processes, providing a road map for what is intended and needs to be done. It is open to change at any point when writing. A second production process is ideation. It involves acquiring possible ideas or content for writing from long-term memory (LTM) or external sources within or outside of the writing community (Torrance, Thomas, & Robinson, 1996). Like conceptualization, ideas can take multiple forms (e.g. language, images, film, or abstract thoughts), and some ideas may undergo considerable scrutiny to determine if they are suitable, whereas others may receive only a cursory examination. With translation, another production process, writers take some or all of the ideas they view as pertinent for writing and turn them into acceptable sentences. This involves deciding which words and syntactic structures best convey the writer’s intended meaning for an idea, image, and so forth (Kaufer, Hayes, & Flower, 1986). When translating ideas, writers draw on their knowledge of grammar, sentence structure, usage, and vocabulary, and may also draw on external aids from the writing community such as a grammar checker, thesaurus, or a collaborator. Transcription, a fourth production process, involves converting the sentences a writer is forming into text, either on paper or digitally (Berninger, 1999). Writers can apply a variety of different tools to transcribe sentences into text, including
The Writer(s)-Within-Community Model 51
handwriting, typing, spelling, and speech synthesis. With multimodal texts, transcription further involves integrating one or more of the following into text: pictures, drawings, film, verbal dialogue, or images. The fifth production process is reconceptualization (Fitzgerald, 1987: Scardamalia & Bereiter, 1986). It applies to all aspects of writing, as writers can rethink and revise whatever is produced. Reconceptualization can involve transforming overall intentions when writing or they may be more localized as when writers make more minor revisions to make text more understandable. In their review of literature, Rijlaarsdam et al. (2012) noted that the use of these production processes is effortful and complex. Further, writers use these processes in different ways and combinations, and multiple amalgamations can lead to good and even similar quality of text. There is also a dynamic interaction between production processes, so that one activity is informed by information from the preceding activity, and this functional relationship between production processes changes during the course of writing. Production processes are initiated and coordinated, through the executive control processes a writer commands (Hayes, 1996). They draw on long-term memory resources like topic knowledge and one’s knowledge about how to write (Olinghouse, Graham, & Gillespie, 2015). The application of production processes further rests on the beliefs a writer holds about the writing task (e.g. they may minimize conceptualization and reconceptualization if the writing task is viewed negatively) as well as decisions made in the writing community (e.g. complete the writing task without revisions). Lastly, production processes are impacted by writing tools (Morphy & Graham, 2012). Reconceptualization, for instance, is more likely to take place when drafting text when writers use word processing versus paper and pencil (MacArthur & Graham, 1987). Long-term memory (LTM) resources. As writers carry out the production processes described earlier, they draw on LTM resources. This includes both knowledge and beliefs. While these LTM resources are not the only capital writers can draw on, as other assets are likely to be available (e.g. source material, model texts, or the expertise of collaborators), but what and how we write owes much to its richness to our LTM (Hayes, 1996; Mayer, 2012). LTM resources that writers use when composing include knowledge of oral language (e.g. phonological, semantic, syntactic, and pragmatic knowledge; Shanahan, 2006), listening (e.g. listen to text created as it is read aloud to determine how it sounds; Espin & Sindelar, 1988), reading (e.g. read directions for a writing task, read and critically analyse possible writing ideas from source material; Fitzgerald & Shanahan, 2000), and writing content (e.g. knowledge about the writing topic, discipline specific knowledge when using writing as a tool for learning; Olinghouse, Graham, & Gillespie, 2015). Writers also rely on the specialized writing knowledge they acquire as a result of their collective experiences in writing communities, including knowledge about transcription skills (e.g. handwriting, typing, keyboarding, and spelling; Berninger, 1999); written sentence construction (e.g. punctuation, capitalization, and
52 3. Executive Control and Writer(s)-Within-Community different types of sentences; Kaufer, Hayes, & Flower, 1986); text purposes and features (e.g. purposes for writing, features of different text; Fitzgerald & Teasley, 1986); processes and strategies for producing and revising text (e.g. schemas and strategies for planning and revising text; Graham & Harris, 2000); tools for writing (e.g. how to use a word processor; Rijlaarsdam et al., 2012); audience (e.g. what an intended audience will likely know about the writing topic; Bazerman et al., 2017); and schemas for controlling writing thoughts, emotions, personality traits, behaviours, inclinations, and the writing environment (Graham, 2018a; Zimmerman & Risemberg, 1997). A final, but equally important type of knowledge held in LTM is writers’ knowledge about their writing communities, including knowledge about a community’s purposes, members, actions, physical and social environment, and collective history. Writers also hold a variety of beliefs in LTM that affect whether they engage in writing, how much effort they commit, what actions and tools are apply, and how they interact with collaborators or other members of the community (Hidi & Boscolo, 2007). This includes beliefs about whether writing is a valid and useful activity as well as an interesting task (Hidi & Boscolo, 2007). It includes beliefs about why one engages in writing (Deci & Ryan, 2000), whether one likes to write (Ekholm, Zumbrunn, & DeBusk-Lane, 2018), and how we identify ourselves as a writer (Bazerman, 2016). Writers also form beliefs about their writing competence (Pajares, Johnson, & Usher, 2007), why they are successful or not successful when writing (Weiner, 1985), and how they value the communities in which they write (Graham, 2018b). Executive control.1 Even when members of a writing community write something that is tightly constrained by tradition, purpose, directions, genre, audience, or some combination of these factors, writers exercise some degree of agency as to what is written and how it is produced (Graham, 2018a). The fact that writing is structured and bound by the social context in which it occurs, does not mean that it is driven solely by a community’s regular practices, including how writing is conceptualized. Writers are also a driving force behind what is written. For example, a writer may make substantial changes in a community assigned writing task so that it is more interesting. Robert Benchley did this when he changed an examination question on issues surrounding international fisheries to creating his response from the point of view of the fish (Hendrickson, 1994). Writers exert agency over writing tasks and control over the process of writing using executive control. The control processes writers use allow them to initiate, plan and organize goal-directed behaviour as well as evaluate their effects and make 1 Several changes were made here to the previously revised version of the WWC model (2018b). This included changing the overarching label control mechanisms to executive control. As a result of this change, it became necessary to rename the processes involved in formulating intentions, plans, evaluations, and reactions to executive processes. These processes were labelled as executive control in the previous version of the WWC. I also reordered the elements of executive control so that its top-down nature was illustrated. Additional information on how executive control operates was provided in the current chapter. Finally, reciprocal arrows replaced unidirectional ones to show that modulators influence executive control, LTM, and production processes and vice versa. A bidirectional arrow was added between cognitive mechanisms and the written product to show the reciprocal relation between the two.
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adjustments as needed (Kassai, Futo, Demetrovics, & Takacs, 2019). They also make it possible for writers to control their actions, thoughts, and emotions (Karr et al., 2018). For example, a writer might seek to control anxiety through the use of strategies such as cognitive reappraisal (recognizing and reinterpreting their response to the writing situation) or by suppressing anxiety (Bridgett, Burt, Edwards, & Deater- Deckard, 2015) Executive control is conscious, effortful, controllable, relatively slow, limited by attentional and working memory resources, and involves serial processing (Karr et al., 2018). It is characterized by logical thought (often experienced as an internal dialogue), where writers apply reasoning, problem solving, decision-making, and analysis (intuition can also play a role). Executive control is most likely to be applied when confronting new and novel problems as well as tasks that require flexible responding, which characterize all writing tasks to some degree (Takacs & Kassai, 2019). It involves explicit processing of information, which requires that writers maintain information in mind so it can be acted upon, establish attentional control over cognitive and emotional functions (e.g. focusing and maintaining attention as well as inhibiting interfering behaviours), and the ability to flexibly shift attentional control as context and task requirements change (MacDonald, 2008). Executive control can further be used to control implicit processing, which is characterized by automatic, rapid, effortless, and parallel processing (Stanovich, 2004). For example, a writer who is able to type text without reflective consciousness might decide to type certain words in capitals to emphasize a point, requiring conscious attention to this process. As writers compose, they use control mechanisms that enable them to establish agency and ownership by making decisions about what to write and how to write it; direct, maintain, and switch attention as needed; regulate multiple aspects of writing (i.e. thoughts, beliefs, emotions, behaviours, writing tools, interactions with collaborators, and the arrangement of the writing environment); and evaluate, react, and make adjustments for all of these actions. Executive control in the WWC model is viewed as a multidimensional set of control mechanisms, including explicit processes, working memory, and attention. Executive processes. Executive processes are the mechanisms by which writers direct and establish agency over the process of writing (Jacob & Parkinson, 2015). They include formulating intentions (goals for writing), plans (actions to achieve goals), evaluations (monitoring and judging the impact of intentions and plans), and reactions (modifying intentions, plans, and evaluations as needed). As noted earlier, these mental actions involve the use of reasoning, problem solving, decision-making, analyses, and intuition. They can be applied to all aspects of the writing process (e.g. defining the writing assignment, developing writing plans, gathering possible writing content, organizing content, constructing sentences, transcribing sentences, integrating visual and verbal features into text, reading and rereading plans and text for evaluative purposes, reformulating plans or text based on these evaluations, managing emotions and dispositions while writing, interacting with collaborators, arranging the writing environment, navigating the writing community, and creating a polished
54 3. Executive Control and Writer(s)-Within-Community final written product). They further operate in conjunction with the purposes and functions of communities within which writing occurs. For example, college students in a science class may be assigned a specific writing topic (explain how the three laws of motion operate), but they use executive control to shape what is written, personalizing it in the process. Formulating intentions involves establishing goals for writing, and it can occur at any point during writing. Writers can formulate goals before starting to write (locate a quiet place to write; take control of my negative emotions about writing), when writing (use interesting ideas to make text more appealing; stay focused), or when analysing text produced so far (check to see if text is clear; stay on topic). Intentions can include broad goals, such as creating an unreliable narrator, or more narrow goals such as using more complex sentences. Writing commonly involves multiple intentions, which are hierarchically organized (see Hayes & Flowers, 1986). Writers’ goals are situated within context, and they may shift at any point during composing (Conway, 2005). To illustrate, a student may be asked to write a text about the potential effects of climate change (a community established goal). As students think about how they will achieve this goal, they are likely to formulate additional intentions addressing both sides of the topic, providing an opening which captures the topic and grabs the readers’ interest, using factual evidence to support their claims, and connecting each claim to a real-life example. While writing about the effects of climate change, new intentions or goals may surface such as the decision to bold each claim so that it stands out or offering personal asides to make their voice more evident. Previously established intentions may be eliminated, take a less prominent role, or never be acted upon. For example, the goal to offer personal asides may be eliminated if the writer has little personal experience with climate change. Once an intention or goal is formulated and the writer is ready to move forward with it, plans can be enacted to achieve it. Generating solutions for how to accomplish an intention can involve multiple approaches. For instance, the writer may draw on an already existing schema held in LTM that provides a reasonable solution for achieving the desired intention (Hayes, 2012), as when a writer decides to apply a schema that worked in the past to meet the intention to gather possible writing information (e.g. consult online sources like Wikipedia). A new plan can also be developed to meet this intention, as when a writer decides to ask what she already knows about the topic, what still needs to be learned, and how can this information be obtained and organized. Further, a plan can involve using an existing schema, but modifying it through problem solving (e.g. modifying the schema to consult online sources like Wikipedia to include conducting interviews and reading print sources material to obtain the needed information). A writer may also develop a vague plan for addressing an intention or fail to create a plan at all. For instance, a writer may formulate an intention to create text that is understandable. A plan for accomplishing this might involve rereading text to identify sentences that do not sound right and revising them so they do. While this may seem like a well-articulated plan, its operation will prove
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to be relatively vague in some instances. The writer will not know why some sentences are not fully understandable beyond that they simply do not sound right (Graham, 1997). Consequently, the author’s efforts to revise sentences will involve rewriting some of them without a clear idea on how to make them better (De La Paz, Swanson, & Graham, 1998). Another important phase in the executive control process is evaluation. This involves monitoring and evaluation the effectiveness of an intention, its plan(s), or both. This can occur at multiple points in the writing process including when an intention or plan is first conceptualized and acted upon, sometime after conceptualization or activation occurs, or repeatedly throughout the composing process. For instance, a writer composing a blog may decide that an overriding goal is to sound young and smart (intention) by using certain words and employing ideas that are likely to resonate with readers who are college educated and are 20 to 30 years of age (plan). The writer may evaluate the success of this goal and plans whenever one or the other are consciously applied. This could also happen periodically when the writer remembers to make such an evaluation, or when a schedule is created for doing so (e.g. once a page of text is produced). A collaborator could also be asked to assess the text produced so far to provide feedback on whether the intention and plans are being achieved. It is important to note that the criteria a writer applies during evaluation will not be the same for different goals, will vary by writing community, and may change as text is produced. The fourth executive control process, reaction, involves the writer’s reaction to the information collected during evaluation. This information may lead the writer to view the desired intention and plan as effective. It may result in the writer being unsure about its effectiveness (as when conflicting evidence is the result of the evaluation). Or the writer may question the value of the intention, plan, or both. When uncertainty or questions about the effectiveness or value of the intention and plan arise, the writer is faced with a decision. Make a change in the intention, plan, or both, or move on without taking any action. The examples here primarily focus on establishing a single intention, plan(s) to achieve it, evaluations of the success of the intention and plan(s), and reactions to them based on the evaluation data collected. The operation of these executive processes is almost always much more complicated. Writers typically have multiple intentions they are trying to achieve, with some taking a more prominent role than others, and some of them overlapping and even competing with other goals. This is one of the aspects of writing that makes it so difficult (Graham, 2018b). Working Memory. Working memory is a limited and temporary storage system where information is held and acted upon (Diamond, 2006). This is where the conscious mental work involved in executive control and writing occurs. Knowledge and beliefs from LTM and external information delivered through the senses are brought into working memory, processed, and acted upon in order to achieve writing intentions. It is also where mental operations involved in regulating attention; activating and orchestrating writing production processes; engaging and suppressing
56 3. Executive Control and Writer(s)-Within-Community motivational beliefs, emotions, and personality traits; and navigating the environmental and social situation in which writing takes place. Working memory consists of three storage systems (Baddeley, 2000). A phonological loop for temporarily holding verbal material. A visuospatial sketchpad for storing spatial, visual, and kinesthetic information. An episodic buffer, where information from the phonological loop and the visuospatial pad and LTM are bundled together to form integrated units of verbal, visual, and spatial information. This provides a writer with multiple, but integrated spaces, where they can act on different forms of data (verbal, symbolic, and visual) when writing. I provide several examples to illustrate the operation of working memory when writing. One, when generating an idea for writing, the writer must hold the idea or image in working memory while evaluating it to determine if it is appropriate for the paper. Two, if the idea or image is deemed to be appropriate, it must be retained in working memory, as the writer must transform it into an acceptable sentence (or sentence part) selecting the words and syntactic structure(s) that best convey the desired intended meaning. Three, the sentence (or sentence part) must be retained in working memory, as the writer transforms it into written text. Four, the writer may decide to evaluate the written sentence (or sentence part), holding it or part of it in working memory, as it is appraised and alternative solutions are created mentally if it is found lacking. Attention. Attentional processes (Jacob & Parkinson, 2015) allow writers to: (1) focus attention on selective or relevant aspects of writing (e.g. brainstorm ideas for a paper), (2) maintain attention on each aspect as needed (e.g. continue brainstorming until enough ideas are produced), (3) ignore distractions (e.g. suppress the urge to correct spellings of words when recording brainstormed ideas), (4) inhibit automatic responses (e.g. forgo evaluating brainstormed ideas as they are generated), and (5) switch attention (e.g. switching attention between mental generation of ideas when brainstorming and recording them on paper as they are generated). Focusing, maintaining, inhibiting, and switching attention, as well as ignoring distractions, occurs in all aspects of writing, including what a writer does alone or with others. I provide two examples next to illustrate the operation of these attentional processes when writing. One, when a teacher provides oral directions for a brief in class writing assignment, students must focus and maintain their attention on the teachers’ directions for writing, ignoring distractions and inhibiting their inclination to start writing as the teacher is still explaining the assignment. Once the teachers’ directions are completed, students must switch their attention to another task, such as writing their opening sentence. Two, as students create their lead sentence, they must focus their attention on conceptualizing an opening idea, switching their attention to translating this idea into an acceptable sentence, and switching attention again as they transcribe it into text. As they carry out these production processes, they must maintain their attention to the task at hand, ignore distractions from other students, and inhibit any impulse to change the idea until they see what it looks like in print.
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Modulators. A writer’s use of production processes, access to LTM, and executive control are moderated by emotions, personality traits, and physiological states (Graham, Schwartz, & MacArthur, 1993; Galbraith, 1999; Madigan, Linton, & Johnson, 1996). Emotions include primary emotions like surprise, joy, anger, sadness, fear, and disgust, as well as secondary emotions like hopefulness, hopelessness, guilt, disappointment, excitement, shame, embarrassment, pride, relief, anxiety, envy, annoyance, and gratefulness (Boekaerts, 2011). They influence what writers want to do (Pekrun, Frenzel, Goetz, & Perry, 2007), as when a person is deciding whether to write an opinion letter to a newspaper after reading another opinion piece that provoked an angry reaction. They also influence what a writer does, as when a writer experiences joy or pride when writing, resulting in greater effort and persistence. Writing can also activate anxiety, making it more difficult to start a writing task, focus attention on it, or manage the writing processes (Daly, 1985). Emotions can further influence a writer’s thinking processes, including problem solving and decision-making (Fridja, 1988), which are central to executive control. While emotions can moderate what a writer does, the collective emotions of community members can impact the mood and work of a writing community too (Graham, 2018a). Personality involves ‘relatively stable individual differences in behavioural dispositions that generalize across a range of environments’ (Zeidner & Matthews, 2012, p. 111). This includes multiple and relatively enduring traits that are not viewed as fixed, but probabilistically. Most of the work in this area has centred on the following five traits: openness to new experiences, conscientiousness, extraversion, agreeableness, and neuroticism (Matthews, Deary, & Whiteman, 2003). Just as emotions can influence a writing community as well as executive control, so can personality traits (Zeidner & Matthews, 2012). For example, Galbraith (1999) reported that students who present themselves in a pleasing way produce more new ideas while planning, whereas students who were less concerned with presenting a pleasing persona produced more new ideas while writing. Writers may be more or less hungry, stressed, tired, or healthy when writing. This matters, as too little sleep can reduce concentration and memory (Curcio, Ferrara, & De Gennaro, 2006); performance is negatively impacted when one is hungry (Kleinman et al., 2002); and stress affects decision-making as well as people working together toward a common goal (Dias-Ferreira et al., 2009). As a result, a writer’s physiological state can impact what is written and how it is created, just as the demands imposed by a writing community can influence one’s physiological state. Relationships between cognitive resources. Writers (and their collaborators), engage in a variety of physical and cognitive actions when writing. They exert agency over their writing, the process of writing, and the communities in which they write through executive control. These control processes are used to formulate, initiate, plan, organize, evaluate, adjust, and sustain goal-directed writing actions, thoughts, emotions, personality traits, and social interactions with collaborators. The conscious and deliberate mental work of writers occurs in working memory, a limited and temporary storage system, where information is acted upon. Not all of the mental
58 3. Executive Control and Writer(s)-Within-Community activities that writers undertake involve explicit processing, as some mental operations become automatized and effortless (e.g. handwriting and spelling). Even so, writers can and do exert effortful control over such mental or physical operations. This can involve taking conscious control over a writing behaviour like handwriting (e.g. purposefully concentrating on making every letter easily readable) or affectively charged responses like writing anxiety. The initiation and application of executive control processes is aided, hindered, or both by the writer’s ability to focus, maintain, inhibit, and switch attention, as well as ignore distractions. Executive control, including the actions and decisions made by writers, are fuelled at the individual level by beliefs about writing, including the value and utility of the writing assignment, perceptions of competence, and one’s beliefs, identity, and commitment to the community in which writing is situated. Such beliefs, in turn, fuel effort and provide the impetus for drawing on resources from LTM or elsewhere as well as initiating, directing, and sustaining the production processes needed to write. The various activities and actions a writer engages in when composing, including executive control, are moderated by psychological, physical, and biological factors including emotions, personality traits, and physical states. All of this is set within the context of a writing community, which also shapes what writers do. Executive control shapes and binds the writing community. A basic premise underlying the WWC model is that executive control allows members to exert some agency over communities in which writing is situated (Graham, 2018b). Executive control processes allow individual members to shape and bind writing within a specific community. Examples include members of a writing community changing or modifying writing assignments (e.g. changing the purpose or focus of a writing assignment by establishing new intentions for it); modifying the typified way that the writing community carries out writing activities (e.g. instead of using a privileged schema for carrying out writing creating a new schema for doing so); introducing new writing tools (e.g. community members agreeing to make speech synthesis a sanctioned tool for writing); and changing the social structure of the writing community (e.g. members decide to encourage collaborative writing and establish goals for doing so). Consequently, members of a writing community use executive control to not only direct and manage their own writing, but to influence the communities where they write. The WWC model (2018a, 2018b) further proposes that executive control provides writers with mechanisms for accomplishing their writing goals by consciously and purposefully managing the use of LTM resources (beliefs and knowledge), production processes, and modulators such as emotions. This includes using executive control to: decide how much effort to commit when writing; determine the level of ownership over the writing task; activate or suppress beliefs about writing; direct, maintain, and switch attention as needed when writing; obtain, cull, and organize needed knowledge from LTM and external sources; activate and orchestrate production processes; regulate thoughts, beliefs, emotions, behaviours, writing tools, interactions with collaborators; and monitor, react, and make adjustments for all of these actions.
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This is not a one-way street though, executive control is in turn influenced by the cognitive and motivational capabilities and resources writers bring to the writing task (Graham, 2018a, 2018b). Beliefs about writing, including the value and utility of the writing assignment and perceptions of competence, can determine the degree to which one draws on executive control mechanisms. Degree of knowledge about the writing topic and appropriate schemas for accomplishing it can impact the level of problem solving needed. Working memory can be overtaxed when transcription processes like handwriting and spelling still require considerable conscious attention. Emotions, personality traits, and physical states can facilitate or impede the use of executive control mechanisms.
Tenets Underlying the WWC Model There are four basic tenets underlying the WWC model (Graham, 2018b). Writing is shaped by: (1) interactions between where it takes place and the actions of community members who create it; (2) the capacity of the community in which it takes place and its members; (3) variability within the community and its members; and (4) ongoing development of the writing community and its members. Before providing examples of how these four tenets can potentially influence executive control, some clarifications are needed. Capacity of a writing community is determined by its purposes (e.g. Are they clear and well-established?), members (e.g. Are they familiar and dedicated to these purposes?), tools (e.g. Are needed writing tools and resources available and familiar to community members?), actions (e.g. Are typified practices for accomplishing writing purposes in place, accepted, effective, and modifiable to meet new challenges?), physical arrangements (e.g. Are adequate physical and digital space available? Is this space sufficient to achieve writing purposes?), social environment (e.g. Are the social attributes of the community pleasant, supportive, and encouraging? Are social relationships and identities positive?), and collective history (e.g. Are community members familiar with how to successfully participate in community writing activities? Is the community stable and open to change?). In contrast, capacity of a community member refers to the cognitive capabilities and resources each member possesses for carrying out the community writing purposes. This includes a writer’s mastery of writing production processes; facility with speaking, reading, and listening; accumulation of LTM resources for writing (e.g. topic, community, and specialized writing knowledge); development of beliefs that support writing success; competence in applying executive control processes; and ability to manage emotions, personality traits, and emotions when writing. Variability within a community refers to fluctuations in how a community carries out its writing purposes. There is not only variability in how different writing communities operate (Graham, 2018b), but in the day-to-day operation of a single community over time. This is due to the shear complexity of a community, the interaction of its components, and the differences in members’ commitment, participation,
60 3. Executive Control and Writer(s)-Within-Community familiarity, and unity. Variability of community members refers to how individuals within a community differ from each other (e.g. disparate views about writing purposes and individual differences in writing capabilities) as well as the variability that exists in each community member (e.g. a writer is not equally skilled at all writing processes and application of these processes are not fixed; Rijlaarsdam et al., 2012). Writing communities are not static structures. They undergo development as they are created, shaped, modified, sustained, and eventually brought to an end. Likewise, members of a writing community undergo change through their literacy experiences, resulting in growth, plateaus, and even regressions in their writing capabilities (Bazerman et al., 2017). Tenet 1: Interactive effects between a writing community and its members. The earlier description of the two organizing features of the WWC model (writing community and writers and their collaborators) provided examples of how community impacts executive control and how executive control provides community members with the agency and tools for changing the community. Next, I share four examples of how features of the community and the executive control capabilities of its members can potentially interact to shape and constrain writing. These are not the only conceivable examples, but they illustrate the complex relations between executive control and context. One, the process of conceptualizing a writing assignment involves an interaction between the purposes of writing within the community as well as the agency and degree of control that those who produce exert. For example, in an eighth grade history class, the teacher asked students to write a report, due in four weeks, on the Civil Rights Movement in the United States during the 1960s and 70s. The teacher directed students to concentrate on some changes in contemporary society caused by this movement (focusing attention). She also indicated they were to develop a plan and time-line for accomplishing this writing assignment (addressing working memory limitations). When presenting this task and its primary purposes to the class (intentions), a few students sought to establish some agencies over it by asking questions about whether it was permissible for them to focus on a specific influential person or group during this period such as Martin Luther King or the Black Power movement, respectively (evaluation and reaction). The teacher indicated that these were great ideas, making it possible for students to formulate their own intentions for their paper while simultaneously broadening the classroom assignment (reaction). As students formed their initial conceptualizations of the assigned tasks, they developed additional intentions for their paper (e.g. identify three changes, use quotes by people involved in the civil rights movement, connect the civil rights movement to other contemporary movements involving freedom). This helped them better define their intentions, establishing additional agency and ownership over the assignment. As they started to work on the assignment (applying attentional resources), several students petitioned the teacher for an additional week to complete it, arguing that this extra time would be needed if they were to meet the teachers’ and their own goals
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(evaluation). The teacher reluctantly agreed, making another change in the writing assignment (reaction). Two, writing takes place in specific physical environments where writers must focus and maintain their attention as well as ignore distractions. A physical environment that is relatively calm and quiet is more likely to make it possible for writers to deploy their attentional resources effectively versus an environment that is chaotic and loud. Because community members produce at least some of the noise and chaos, they can use their executive control capabilities to establish personal ways of dealing with it or to make changes in the writing community itself. To illustrate, the office where newspaper reporters work had an open floor plan, with people coming and going, constant and sometimes loud phone conversations taking place, and people yelling to each other across desks. This was so distracting for some reporters that they decided changes must be made (formulate intention) and devised approaches (plans) for reducing noise, including wearing ear plugs when writing, finding a different part of the building for writing, and constructing a temporary barrier around their desk to cut off some of the noise and visual chaos. As more and more of these plans were implemented, the Editor-in-Chief of the newspaper noticed, and in conjunction with the staff made a decision to change the open-floor plan so that all reporters had cubicles (intention and plan). Some of the reporters continued to wear ear plugs under the new conditions, as they judge this was still an effective strategy (evaluation) as not all noise was eliminated. Other ear plug wearers decided to discontinue their use (reaction), as they judge they were no longer needed. Three, over time each writing community develops its own typified actions for writing. These actions are not unchanging, as noted earlier, and can be impacted by the executive control processes of community members. For instance, a third grade language arts teacher set up her class so that the sanctioned approach to writing (or schema for carrying out the writing process) involved students choosing a writing topic with a peer, each pair of students planning the content for the paper, both students in the pair writing a separate paper and then receiving feedback from a third student in the class (focusing attention and addressing working memory limitations). Over the course of the first three months of class, multiple students experienced difficulty applying this schema. Some of the students could not easily pick a topic (formulate intentions). Other students could not agree on what to include in their paper (plan), whereas a few students wanted feedback from the teacher and not a peer (evaluation and reaction). Surreptitiously, a few students created solutions (plans) to address these issues. One pair of students asked peers setting next to them about their previous papers, and then made one of these topics the focus of their assignment. Another pair of students decided they would act as if they were planning together, but each actually created separate plans. Additionally, several students purposefully ignored feedback provided by a peer, and asked the teacher to react to their paper. In effect, students expanded the schemas for writing in the classroom. As the teacher noticed these deviations from the sanctioned approach to writing, a class discussion was held where it was decided that students could write alone or together, solicit feedback
62 3. Executive Control and Writer(s)-Within-Community from peers or the teacher, and choose or be assigned a writing topic, resulting in new typified schemas for writing in the classroom. Four, writing communities are shaped by cultural, social, historical, institutional, and political factors. These factors can also influence the interactions between context and executive control. Take for instance a middle school language arts teacher who wanted to provide culturally sensitive writing instruction in her class (intention). Ninety percent of her students were Hispanic. She had recently read that the strongest writing motivators for these students involved writing for social purposes and emotional regulation (Camping et al., 2020). As a result, she decided to emphasize two types of writing activities: one that made connections with friends and family, and a second that involved using a journal to record personal reactions to positive as well as trying events (plan). Initially, this appeared to be an effective strategy, but a month after putting it into play, the teacher noticed that her students stopped being as enthusiastic about these tasks (evaluation), as they complained that they wanted to do other types of writing too. As a result, the teacher decided to change the purposes writing served in her class (reaction). She had observed that students were relatively positive about the types of writing they did at home, so she established additional purposes for writing (intentions), making connections between the writing students did at home and school. This included asking students to take writing done at home and expanding it at school to address other writing motivators such as curiosity and involvement (plan). The teacher observed that students enjoyed the challenge of these new writing tasks (evaluation), and made a decision to continue their use (reaction), and in the process changed both the purposes and typified actions in her classroom. Tenet 2: Simultaneous effects of community and individual capacity. The WWC model not only postulates that context influences executive control and vice versa, but that the capacity of a writing community and the capacity of the cognitive resources and capabilities of its members together shape and constrain the use of executive control (Graham, 2018a, 2018b). To illustrate, some writing communities operate with greater capacity than others. In a community where there is a strong commitment, such as a newspaper supporting a particular political of view, members are likely to devote considerable effort and attention to meeting writing goals, planning, evaluating, and adjusting them as needed. This is less likely to happen in a community where writing purposes are not strongly valued or appreciated. Likewise, a writing community with an extended and successful history is more likely to have typified actions and schemas for how to accomplish its writing purposes in place than a community that is just several weeks old and is still in the process of determining how writing tasks are to be carried out. Writers in the less established community by necessity will be more reliant on devising their own solutions. Individual writers also operate at varying levels of capacity depending on the writing tasks (Bazerman et al., 2017). For instance, a writer had more or less experience with different types of writing, and was more knowledgeable about the purposes of some types of writing than others. As a result, this writer developed effective, efficient, and routinized schemas for completing these more practised writing tasks,
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reducing the likelihood of overtaxing attentional resources and working memory when completing such tasks (Paas & Sweller, 2014). This was not the case with the less familiar writing tasks. Not surprisingly, individual and community capacity do not operate separately or as simply as the examples mentioned imply. They interact with each other in complex ways. Consider, a community where virtually all members strongly support its writing purposes, and another community where many members do not. Similarly, members in the first community are mostly accomplished in conceptualizing, planning, and reworking papers to make them better, whereas members in the second community are more varied in these competencies. If both communities involve all of their members in meeting their writing purposes, how executive control operates at the community and individual level will operate differently as community and individual differences interact. Tenet 3: Simultaneous effects of variability in a writing community and its members. Variability operates within a writing community and among its members. According to the WWC model (Graham, 2018a, 2018b), a writing community uses writing to achieve its purposes, operates from a shared set of assumptions and goals, and involves multiple interacting characteristics (e.g. members, tools, actions, collective history). Within this community, contradictions, disparate elements, conflict, multiple voices, and heterogeneity are inevitable (Swales, 1990). Even though most members of this community share a common understanding of roles and responsibilities, how to operate within the physical and social confines of the community, and how specific tools and sanctioned forms of actions are used to achieve writing objectives, these understandings will not be consistent or uniform. Community members will differ in their familiarity with each of these factors and their acceptance of them, and this will fluctuate across situations and over time. Some community members may also passively or actively work against a community’s writing purposes and typified actions for achieving them. Consequently, a writing community is not a single thing, but multiple things (Bazerman, 2016), and a community’s preferred use of executive control mechanisms will vary. Just as writing communities vary in how they operate, individual members within the community differ as well (Freedman, Hull, Higgs, & Booten, 2016). For example, writers in a community will vary in their commitment to particular writing tasks as well as their familiarity with the tools, sanctioned actions, and specialized writing knowledge needed to accomplish it. There will be differences among community members about the value of writing and their identities as writers. Individuals will differ in their knowledge and beliefs about writing, emotional reactions to it, and their executive control capabilities (e.g. attentional control, working memory capacity, and mastery of executive processes). Consequently, there will be considerable variability among community members in how they apply executive control mechanisms to achieve desired writing goals. Variability in community and individual members’ capabilities can also interact to impact executive control. For instance, at the start of the school year, a third grade
64 3. Executive Control and Writer(s)-Within-Community language arts teacher tried out three different approaches for writing with her students. These approaches involved different combinations of planning, drafting, and revising (i.e. drafting and revising; planning, revising; drafting, and revising; drafting a quick first draft, planning, revising first draft). These schemas for writing meet with varying levels of success, as they were not equally effective with all students because there was considerable variability among students in their capabilities to apply them effectively. Tenet 4: Simultaneous effects of community and member development. A writing community and its members are not static entities (Graham, 2018a, 2018b). They are continually developing and emerging. A writing community, for example, is subject to internal change, as when a health clinic decided to use a new approach for transcribing information about patients, moving from a worksheet with specific questions to a written summary that provided information on changes in the patient’s health, implications of these changes, and recommended treatment and follow-up procedures. Changes in a writing community can also be a consequence of external forces, as demonstrated by a school implementing a new approach to writing to address poor performance on the State writing test. In this case, the principal directed teachers to move from a traditional writer’s workshop approach, which he viewed as ineffective, to the Self-regulated Strategy model (Harris & Graham, 2009) as a way of better teaching students’ strategies for planning, drafting, revising, and editing. In both of these examples, changes in the community influenced how executive control was used to meet writing objectives. Writers’ executive control also develops and become more efficient and sophisticated (Graham, 2018a). With age and more writing experience, for instance, developing writers gain better control over attention and executive processes, with some aspects of writing become more automatized, freeing up cognitive resources that can be used in other ways (Paas & Sweller, 2014). There are multiple processes that facilitate the development of executive control at the individual level. The executive control procedures sanctioned by a community can be acquired through participation in it (Greeno & Engeström, 2014). New executive control processes can be obtained by observing others write (Couzijn, 1999), through instruction provided by mentors or teachers (Graham, Harris, & Santangelo, 2015; Graham, Hebert, & Harris, 2015), and via deliberate agency, as when a writer creates a new schema for planning and drafting a composition (DiSessa, 2014). Further, executive control capabilities acquired in one writing community can transfer to another, as when a strategy learned at school is used at home (Morrow & Young, 1997). Developmental change in writers’ executive control is not a straightforward process, though, as it can be influenced by genetic, neurological, personal, and environmental factors. For example, genes contribution to individual development in writing is almost equal to environmental determinants (Erbelli, Hart, Kim, & Taylor, 2017). Neurological functioning impacts development in writing, as can happen when the brain is injured or a person suffers from a neurogenerative disorder like Parkinson’s disease (Graham & Weintraub, 1996). Physical factors such as age impact writing
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development, as cognitive functioning diminishes in old age (Ojede, Aretoul, Pena, & Schretlen, 2016). Finally, environmental factors such as wealth, especially for developing writers, have the potential to influence writing development (Graham, 2006). Children living in poverty, for instance, are likely to receive poorer writing instruction and experience conditions that hamper cognitive development (e.g. toxic-stress is more common for children experiencing poverty and can negatively impact brain development; Parrett & Budge, 2016).
Future Research and Implications for Writing The revised WWC model presented here provides a lens for understanding writing, emphasizing that ‘writing involves an interaction between the social context in which it occurs and the mental and physical actions writers are able to enlist and engage’ (Graham, 2018a, p. 304). This stands in contrast to previous models of writing that either focused on the social (e.g. Russell, 1997) or the cognitive aspects of writing (e.g. Hacker, 2018). Viewing writing from just a single perspective is overly restrictive and narrow, as it does not take into account how social context influences executive control and vice versa. Writing and executive control are multifaceted and interactive. The WWC model includes the following eight assumptions about executive control and writing: (1) writers use executive control to manage cognitive, motivational, and physical resources to meet desired writing goals; (2) the use of executive control processes are influenced by the capabilities and resources writers possess; (3) context influences how writers use executive control; (4) executive control makes it possible for writers to change the writing context; (5) context and the individual characteristics of writers interact to shape writer’s use of executive control; and executive control in writing is simultaneously and interactively influenced by the (6), capacity, (7) variability, and (8) development within both the writing community and its members.
Current and Future Research To date, research on executive control in writing has focused mostly on the first two assumptions here. Available studies established that executive control predicts writing (e.g. Cordeiro, Limpo, Olive, & Castro, 2020; Graham et al., 2019; Ransdell & Levy, 1996; Olive, Kellogg, & Piolat, 2008; Swanson & Berninger, 1996); executive control when writing is influenced by other cognitive capabilities and resources (e.g. Beilock, Rydell, & McConnell, 2007; Kellogg, 1987; Kim & Park, 2019; Limpo, Alves, & Connelly, 2017; Olive & Barbier, 2017; Vanderberg & Swanson, 2007; Wijekumar et al., 2019), and individual differences in executive control are related to how writers compose (e.g. Chuy, Alamargot, & Passerault, 2012). Other studies demonstrated
66 3. Executive Control and Writer(s)-Within-Community that providing developing writers with schemas for managing the writing process via strategy instruction (see the meta-analyses by Graham, Harris, & Santangelo, 2015; Graham & Perin, 2007) or procedural support (e.g. De La Paz, Swanson, & Graham, 1998; Graham, 1997; Scardamalia & Bereiter, 1985) enhances writing. While there is credible evidence supporting the first two propositions earlier (i.e. a writer uses executive control to meet desired objectives; executive control is influenced by a writer’s cognitive capabilities and resources), the other six propositions that involve the interaction of context and executive control must be viewed as speculative at this time. For example, I was unable to locate any studies examining the relationship between writing, context, and executive control (assumption number 3). This does not appear to be an anomaly specific to writing. Context plays a relatively muted role in recent reviews of research on executive functioning as well as self-regulation (e.g. Bridgett, Burt, Edwards, & Deater-Deckard, 2015; Karr et al., 2018; Kassai, Futo, Demetrovics, & Takacs, 2019; MacDonald, 2008; Takacs & Kassai, 2019). This does not mean that context and executive control are completely ignored in this literature. Martinez (2014) examined the relationship between executive control and cultural values, parenting, and SES among Hispanic preschoolers, whereas Darcy (2014) examined executive control in a specific environment: a preschool Montessori classroom. Similar studies could be replicated in writing and extended to other features of writing context (e.g. norms for writing, typified writing routines, or social arrangements when writing). In addition, these and other contextual variables can be systematically manipulated to determine if there are corresponding changes in how students apply executive mechanisms when writing. Future research examining the eight assumptions mentioned here will undoubtedly involve quantitative as well as qualitative research. For instance, initial research on assumption four (i.e. executive control makes it possible for writers to change the writing context), will likely involve qualitative studies that examine if and how writers or their collaborators purposefully change some aspect of their community. Assumption number seven (community and members simultaneously and interactively influence executive control) can be studied quantitatively by examining if variation in communities and its members cognitive capabilities and resources predict individual differences in members executive control as applied to writing. While I am hopeful that the WWC model will spur new research testing all eight of the assumptions mentioned here, the model also provides new focal points for examining executive control in writing in three important ways. One, the model extends current models of executive functioning in writing by making self-regulation part of the executive control process. This provides several new avenues for research, including studies designed to assess the validity of the combination proposed here, how these variables operate and develop over time, and whether instruction can foster the development of these processes. Two, most current studies that involve some aspect of executive control in writing do not provide an adequate description of context. In effect, context is treated as background noise to be ignored. This makes it very difficult to determine to whom and under what situations the findings from a study on executive control in writing can
Future Research and Implications for Writing 67
be applied. The WWC model provides a framework for describing the characteristics of the communities where future studies take place, making it possible to more fully contextualize the findings from future investigations. Three, the cognitive architecture proposed in the WWC model provides an expanded framework for considering how executive control in writing operates. For example, the three modulators (emotions, personality traits, and physical states) included in this model provide new avenues for research, as they can potentially influence executive control or be influenced by it. An obvious starting point for such research is to examine if these variables and executive control as well as writing performance are related, and if these relationships are unidirectional, bidirectional, and how they develop and change over time. More fine-grained analyses are also needed to determine more precisely how specific aspects of a modulator (e.g. anxiety) affect and are influenced by the interaction between executive control and writing. Such research will make it possible to conduct stronger theoretically-derived interventions studies that provide causal data on these linkages and practical, validated instructional procedures. For the interested reader, I would also recommend examining recommendations for research based on the WWC model for writing-to-learn in science (Graham, 2019) and instructional feedback in writing (Graham, 2018c). Implications for Practice. In other publications, my collaborators and I have provided several examples of how the WWC model can be applied to the teaching of writing. This includes using the WWC model as an organizing framework for creating a model of writing instruction for students with learning disabilities that was centred on the use of evidence-based writing practices (Graham & Harris, 2020). While this model of instruction focused on the teaching of writing broadly, it included the identification of evidence-based practices for (1) creating a conducive environment for executive control in writing, and (2) teaching students how to use and apply such processes. A second publication (Graham & Harris, 2018) applied the WWC model to anchor and illustrate the basic design features underlying a Self-regulated Strategy Development study (SRSD; Harris & Graham, 1988). SRSD was used in this study to enhance students’ executive control in writing (as well as their knowledge and motivations), whereas practice-based professional development (Harris et al., 2012) was used to create a classroom environment conducive to this instruction. In a third publication, Limpo and Graham (2019) applied the WWC model to handwriting, using it to illustrate how context influences the development and use of handwriting, and that handwriting must become automatized in the communities where it is applied if its interfering impact on other writing processes are to be minimized (Berninger, 1999). In this chapter, I extend these previous discussions by providing eight recommendations for promoting developing writers’ executive control based on the WWC model. These are included in Box 3.1, next. In closing, there has been considerable interest in recent years to determine if it is possible to improve through instruction students’ attention, working memory, or executive control. This provides a different approach to enhancing students’ executive control in writing than the ones proposed in Box 3.1, where efforts to enhance
68 3. Executive Control and Writer(s)-Within-Community
Box 3.1 Recommendations for enhancing developing writers’ executive control • Create a classroom where the purposes for writing are clearly specified and typified actions/routines for obtaining these purposes are crafted and instituted. This increases the capacity of the writing community to support and promote students’ use of executive control. The teacher needs to ensure that students are familiar and facile in the use of these procedures. • Make students a driving force behind what is written. Encourage them to set their own goals and purposes for writing as well as modify and extend existing routines for composing. Increasing students’ agency provides a sanctioned mechanism for them to expand as well as upgrade their executive control capacity in writing. • Provide students with social models for how to carry out executive functions when writing. One way this can be done is by modelling processes like goal setting, devising plans to achieve goals, evaluating the impact of goals and plans, and making modifications in them as needed. Schemas that guide the writing process can also be modelled as can the process of modifying an existing schema or devising a new one for a specific writing task. Such schemas typically break the writing process into smaller steps, addressing working memory limitations. Modelling can also emphasize how attention is directed, as teachers can use self- instructions while modelling to remind themselves to stay focused, ignore extraneous thoughts, and flexibly shift attention as needed (Harris & Graham, 1988). • Enhance students’ executive control by teaching them schemas (e.g. strategies for planning or drafting) and self-regulation procedures (e.g. goals setting, self- evaluation) they can use to guide the writing process (Harris & Graham, 2009). For example, students can be taught strategies (monitoring attention or monitoring productivity) that increases their attentiveness while writing (Harris, Danoff- Friedlander, Saddler, Frizzelle, & Graham, 2005). Similarly, they can be taught strategies that guide how they generate and organize information when planning (Graham & Harris, 2018). Teaching such strategies increases students’ executive control capacity for writing, and provides a mechanism for breaking the writing process into more manageable units (helping address working memory limitations). • Promote smart and flexible use of the purposes, writing routines, schemas, and executive functions that are sanctioned, privileged, modelled, and taught in the classroom as well as the one’s devised by students. For example, students can be asked to identify how they need to adapt an acquired schema or process (e.g. goals setting) to another situation in the classroom or to a setting outside of it, devise a plan for doing so, try it out, and reflect on what did and did not work (Harris, Graham, & Mason, 2006). As with the previous recommendation, efforts designed to increase transfer across tasks and writing communities increase students’ executive control capacity for writing. • Employ levers that are likely to enhance students’ use of executive control when writing. Examples included allowing students to make decisions about what and
Future Research and Implications for Writing 69 how they write, engaging students in writing projects that have real purposes and authentic audiences, and having students work together as they plan, draft, revise, edit, and publish their written work (Graham, Hebert, & Harris, 2015). • Reduce the impact of levers that are likely to interfere with students’ executive control when writing. This can include controlling contextual factors such as reducing noise (to assist with attention) or creating a supportive and positive writing environment where students feel free to try new approaches when writing. It can also include making students’ transcription skills more automatic (addressing working memory limitations), as they can require considerable cognitive resources, increasing the possibility that students’ will minimize their use of executive control when writing (Berninger, 1999). Addressing negative beliefs (increasing low writing self-efficacy via positive social feedback), debilitating emotions (decreasing writing anxiety by lowering the evaluative stakes), or interfering personality traits (helping less conscientiousness writers create a time-line) may also prove to be useful. • Recognize that variability exists within and between classrooms in how executive control in writing is supported and taught. This can make it more difficult for students to transfer executive control skills from one context to another or even apply them in the same context. Similarly, students in a classroom will differ in their mastery of executive control in writing, and even the same students will be more or less adept at applying executive control across writing assignments. Teachers can address unwanted contextual variability within a classroom by monitoring their teaching practices, and variability across classrooms can be addressed by bringing teachers together to decide how they want to collectively and commonly address executive control in writing. In terms of student variability in the mastery and use of executive control, teachers should consider how to differentiate their writing instructional practices to help all students make the best use of classroom supports and teaching procedures (see for example McKeown et al., 2019).
executive control were situated explicitly in writing. Is this alternative approach viable? Several recent meta-analyses suggest that it may not be a particularly productive avenue to address executive control in writing. In a meta- analysis involving studies conducted with children, Kassai, Futo, Demetrovics, and Takacs (2019) reported that there is evidence that specific aspects of executive control (e.g. working memory) can be improved through training, but this training did not impact other untrained components of executive control (e.g. inhibitory control). Moreover, in a second meta-analysis, Takacs and Kassai (2019) indicted that the benefits of such training did not maintain on follow-up assessments. This led the authors of these two reviews to question the value of training executive control in isolation. Moreover, Jacob and Parkinson (2005) in their meta-analysis found no compelling evidence that training executive control in isolation improved students’ academic skills. While the studies in their review did not involve writing (reading and math achievement were assessed), the finding from these three meta-analyses suggest
70 3. Executive Control and Writer(s)-Within-Community that such an approach to improving executive control in writing must be viewed as unsupported at the present time. In contrast, there is evidence that instructional efforts designed to improve specific aspects of students’ executive control in writing are effective (e.g. Graham, Hebert, & Harris, 2015; Graham & Perin, 2007).
References Allodi, M.W. (2007). Assessing the quality of learning environments in Swedish schools: development and analysis of a theory-based instrument. Learning Environments Research, 10(3), 157–75. Baddeley, A. (2000). The episodic buffer: a new component of working memory? Review article. Trends in Cognitive Sciences, 4(11), 417–23. Barton, D. (1991). The social nature of writing. In D. Barton & R. Ivanič (Eds.). Writing in the Community (pp. 1–13). Newbury Park, CA: SAGE. Bazerman, C. (2016). What do sociocultural studies of writing tell us about learning to write? In C.A. MacArthur, S. Graham, & J. Fitzgerald (Eds.). Handbook of Writing Research (2nd ed., pp. 11–23). New York, NY: Guilford Press. Bazerman, C. Applebee, A., Berninger, V., Brandt, D., Graham, S., Matsuda, P., . . . & Schleppegrell, M. (2017). Taking the long view on writing development. Research in the Teaching of English, 51, 351–60. Bazerman, C., & Prior, P. (2005). Participating in emergent socio-literate worlds: genre, disciplinarity, interdisciplinarity. In J. Green, R. Beach, M. Kamil, & T. Shanahan (Eds.). Multidisciplinary perspectives on literacy research (2nd ed., pp. 133– 78). Cresskill, NJ: Hampton Press. Beilock, S.L., Rydell, R.J., & McConnell, A.R. (2007). Stereotype threat and working memory: mechanisms, alleviation, and spillover. Journal of Experimental Psychology: General, 136(2), 256–76. Berninger, V. (1999). Coordinating transcription and text generation in working memory during composing: automatic and constructive processes. Learning Disability Quarterly, 22, 99–112. Boekaerts, M. (2011). Emotions, emotion regulation, and self-regulation of learning. In B.J. Zimmerman & D.H. Schunk (Eds.). Handbook of Self-regulation of Learning and Performance (pp. 408–25). New York, NY: Routledge. Brandt, D. (2001). Literacy in American Lives. New York, NY: Cambridge University Press. Bridgett, D., Burt, N., Edwards, E., & Deater-Deckard, K. (2015). Intergenerational transmission of self-regulation: a multidisciplinary review and integrative conceptual framework. Psychological Bulletin, 141, 602–54. Cameron, C.A., Hunt, A.K, & Linton, M.J. (1996). Written expression as recontextualization: children write in social time. Educational Psychology Review, 8(2), 125–50. Camping, A., Graham, S., Ng, C., Aitken, A., Wilson, J., & Wdowin, J. (2020). Writing Motivation of middle school emergent bilingual students. Reading and Writing: An Interdisciplinary Journal, 33, 2361–90. Chuy, M., Alamargot, D., & Passerault, J. (2012). Inference with prior knowledge while writing from source: effects of working memory capacity. Journal of Cognitive Psychology, 24, 815–28. Cordeiro, C., Limpo, T., Olive, T., & Castro, S. (2020). Do executive functions contribute to writing quality in beginning writers? A longitudinal study with second graders. Reading & Writing: An Interdisciplinary Journal, 33, 813–33.
References 71 Conway, M.A. (2005). Memory and the self. Journal of Memory and Language, 53(4), 594–628. Couzijn, M. (1999). Learning to write by observation of writing and reading processes: Effects on learning and transfer. Learning and Instruction, 9, 109–42. Curcio, G., Ferrara, M., & De Gennaro, L. (2006). Sleep loss, learning capacity and academic performance. Sleep Medicine Reviews, 10(5), 323–37. Daly, J.A. (1985). Writing apprehension. In M. Rose (Ed.). When a Writer Can’t Write: Studies in Writer’s Block and Other Composing- Process Problems (pp. 42– 82). New York, NY: Guilford Press. Darcy, A. (2014). Executive Function in Early Childhood: Qualitative and Quantitative Patterns of Development Among Students Within Montessori Classroom. Unpublished Doctoral Dissertation, Kennesaw State University, Kennesaw, GA. De La Paz, S., Swanson, P., & Graham, S. (1998). Contribution of executive control to the revising problems of students with writing and learning difficulties. Journal of Educational Psychology, 90, 448–60. Deci, E.L., & Ryan, R.M. (2000). The ‘what’ and ‘why’ of goal pursuits: human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227–68. Diamond, A. (2006). The early development of executive functions. In E. Bialystok & F.I.M. Craik (Eds.). Lifespan Cognition: Mechanisms of Change (pp. 70–96). New York, NY: Oxford University Press. Dias-Ferreira, E., Sousa, J., Melo, I., Morgado, P., Mesquita, A., Cerqueria, J., Costa, R., & Sousa, N. (2009). Chronic stress causes frontostriatal reorganization and affects decision making. Science, 31, 621–25. diSessa, A.A. (2014). A history of conceptual change research: threads and fault lines. In R.K. Sawyer (Ed.). The Cambridge Handbook of the Learning Sciences (2nd ed., pp. 88–108). Cambridge, UK: Cambridge University Press. Dyson, A. (1999). Coach Bombay’s kids learn to write: ‘Children’s appropriation of media material for school literacy’. Research in the Teaching of English, 33(4), 367–402. Elbow, P. (1998). Writing Without Teachers. Oxford, UK: Oxford Press. Ekholm, E., Zumbrunn, S., & DeBusk-Lane, M. (2018). Clarifying an elusive construct: a systematic review of writing attitudes. Educational Psychological Review, 30, 827–56. Erbelli, F., Hart, S., Kim, Y., & Taylor, J. (2017). The effects of genetic factors on writing development. Learning & Individual Differences, 59, 11–21. Espin, C., & Sindelar, P. (1988). Auditory feedback and writing: learning disabled and non- disabled students. Exceptional Children, 55, 45–51. Fitzgerald, J. (1987). Research on revision in writing. Review of Educational Research, 57, 481–506. Fitzgerald, J., & Shanahan, T. (2000). Reading and writing relations and their development. Educational Psychologist, 35, 39–50. Fitzgerald, J., & Teasley, A. (1986). Effects of instruction in narrative structure on children’s writing. Journal of Educational Psychology, 78, 424–32. Freedman, S.W., Hull, G.A., Higgs, J.M., & Booten, K.P. (2016). Teaching writing in a digital and global age: toward access, learning, and development for all. In D.H. Gitomer & C.A. Bell (Eds.). Handbook of Research on Teaching (5th ed., pp. 1389–450). Washington, DC: American Educational Research Association. Fridja, N.H. (1988). The laws of emotion. American Psychologist, 43(5), 349–58. Gabrial, B. (2008). History of writing technologies. In C. Bazerman (Ed.). Handbook of Research on Writing: History, Society, School, Individual, Text (pp. 23–34). New York, NY: Erlbaum. Galbraith, D. (1999). Writing as a knowledge-constituting process. In M. Torrance & D. Galbraith (Eds.). Knowing What to Write: Conceptual Processes in Text Production (pp. 139– 59). Amsterdam, Netherlands: Amsterdam University Press.
72 3. Executive Control and Writer(s)-Within-Community Graham, S. (2019). Writers in community model: 15 recommendations for future research in using writing to promote science learning. In V. Prain & B. Hand (Eds.). Theorizing the Future of Science Education Research Future (pp. 43–60). New York, NY: Springer. Graham, S. (2018a). A writer(s) within community model of writing. In C. Bazerman, V. Berninger, D. Brandt, S. Graham, J. Langer, S. Murphy, . . . & M. Schleppegrell (Eds.). The Lifespan Development of Writing (pp. 271–325). Urbana, IL: National Council of English. Graham, S. (2018b). The writer(s)- within- community model of writing. Educational Psychologist, 53, 258–79. Graham, S. (2018c). Instructional feedback in writing. In A. Lipnevich & J. Smith (Eds.). The Cambridge Handbook of Instructional Feedback (Cambridge Handbooks in Psychology, pp. 145–68). Cambridge: Cambridge University Press. Graham, S. (2006). Writing. In P.A. Alexander & P.H. Winne (Eds.). Handbook of Educational Psychology (pp. 457–78). Mahwah, NJ: Erlbaum. Graham, S. (1997). Executive control in the revising of students with learning and writing difficulties. Journal of Educational Psychology, 89, 223–34. Graham, S., & Harris, K.R. (2020). Writing and students with learning disabilities. A Martin, R. Sperling, & K. Newton (Eds.). Handbook of Educational Psychology and Students with Special Needs (pp. 487–509). NY: Routledge. Graham, S., & Harris, K.R. (2018). An examination of the design principles underlying aa self- regulated strategy development study. Journal of Writing Research, 10(2), 139–87. Graham, S., & Harris, K. (2000). Writing development: Introduction to the special issue. Educational Psychologist, 35, 2. Graham, S., Harris, K.R., & Santangelo, T. (2015). Research-based writing practices and the common core: meta- analysis and meta- synthesis. Elementary School Journal, 115(4), 498–522. Graham, S., Hebert, M., & Harris, K.R. (2015). Formative assessment and writing: a meta- analysis. Elementary School Journal, 115(4), 524–47. Graham, S., Hebert, M., & Harris, K.R. (2011). Throw ’em out or make ’em better? State and district high-stakes writing assessments. Focus on Exceptional Children, 44(1), 1–12. Graham, S., & Perin, D. (2007). A meta-analysis of writing instruction for adolescent students. Journal of Educational Psychology, 99, 445–76. Graham, S., Schwartz, S., & MacArthur, C. (1993). Knowledge of writing and the composing process, attitude toward writing, and self-efficacy for students with and without learning disabilities. Journal of Learning Disabilities, 26, 237–49. Graham, S., Wijekumar, K., Harris, K.R., Lei, P., Fishman, E., Ray, A., & Houston, J. (2019). Writing skills, knowledge, motivation, and strategic behavior predict students’ persuasive writing performance in the context of robust writing instruction. Elementary School Journal, 119, 487–510. Graham, S., & Weintraub, N. (1996). A review of handwriting research: progress and prospect from l980 to l993. Educational Psychology Review, 8, 7–87. Greeno, J.G., & Engeström, Y. (2014). Learning in activity. In Sawyer, R.K. (Ed.). The Cambridge Handbook of the Learning Sciences (2nd ed., pp. 128–47). Cambridge: Cambridge University Press. Hacker, D. (2018). A metacognitive model of writing: An update from a developmental perspective. Educational Psychologist, 53, 220–37. Harris, K.R., & Graham, S. (2009). Self-regulated strategy development in writing: premises, evolution, and the future. British Journal of Educational Psychology (monograph series), 6, 113–35. Harris, K., & Graham, S. (1988). Self-instructional strategy training: improving writing skills among educationally handicapped students. Teaching Exceptional Children, 20, 35–7.
References 73 Harris, K.R., Graham, S., Mason, L., McKeown, D., & Olinghouse, N. (2018). Self-regulated strategy development in writing: a classroom example of developing executive functioning processes and future directions. In L. Meltzer (Ed.). Executive Functioning in Education: From Theory to Practice (2nd Ed.; pp. 326–56). New York, NY: Guilford. Harris, K.R., Lane, K., Graham, S., Driscoll, S., Sandmel, K., Brindle, M., & Schatschneider, C. (2012). Practice-based professional development for strategies instruction in writing: a randomized controlled study. Journal of Teacher Education, 63, 103–19. Hayes, J.R. (2012). Modeling and remodeling writing. Written Communication, 29(3), 369–88. Hayes, J.R. (1996). A new framework for understanding cognition and affect in writing. In C.M. Levy & S. Ransdell (Eds.). The Science of Writing: Theories, Methods, Individual Differences, and Applications (pp. 1–27). Mahwah, NJ: Erlbaum. Hayes, J., & Flowers, L. (1986). Writing research and the writer. American Psychologist, 41, 1106–13. Hendrickson, R. (1994). The Literary Life and Other Curiosities (rev. ed.). San Diego, CA: Harvest Books. Hidi, S., & Boscolo, P. (2007). Writing and Motivation. Amsterdam: Elsevier. Hull, G., & Schultz, K. (2001). Literacy and learning out of school: a review of theory and research. Review of Educational Research, 71(4), 575–611. Jacob, R., & Parkinson, J. (2015). The potential for school-based interventions that target executive function to improve academic achievement: a review. Review of Educational Research, 85(4), 512–52. Johnson, C. (2001). A survey of current research on online communities of practice. Internet and Higher Education, 4, 45–60. Jones, I. (1998). Peer relationships and writing development: a microgenetic analysis. British Journal of Educational Psychology, 68(2), 229–41. Kalman, J. (1996). Joint composition: the collaborative letter writing of a scribe and his client in Mexico. Written Communication, 13(2), 190–220. Karr, J., Areshenkoff, N., Rast, P., Hofer, S., Iverson, G., & Garcia-Barrera, M.A. (2018). The unity and diversity of executive functions: a systematic review and re-analysis of latent variable studies. Psychological Bulletin, 144, 1147–85.Kassai, R., Futo, J., Demetrovics, Z., & Takacs, Z. (2019). A meta-analysis of the experimental evidence on the near-and far-transfer effects among children’s executive function in skills. Psychological Bulletin, 145, 165–88. Kaufer, D., Hayes, J., & Flower, L. (1986). Composing written sentences. Research in the Teaching of English, 20(2), 121–40. Kellogg, R.T. (1987). Effects of topic knowledge on the allocation of processing time and cognitive effort to writing processes. Memory and Cognition, 15(3), 256–66. Kim, Y., & Park, S. (2019). Unpacking pathways using the direct and indirect effects model of writing (DIEW) and the contributions of higher order cognitive skills to writing. Reading & Writing: An Interdisciplinary Journal, 32, 1319–43. Kleinman, R.E., Hall, S., Green, H., Korzec-Ramirez, D., Patton, K., Pagano, M.E., & Murphy, J.M. (2002). Diet, breakfast, and academic performance in children. Annals of Nutrition & Metabolism, 46(supplement), 24–30. Kwok, M.N., Ganding, E., Hull, G., & Moje, E.B. (2016). Sociocultural approaches to high school writing instruction: examining the roles of context, positionality, and power. In C.A. MacArthur, S. Graham, & J. Fitzgerald (Eds.). Handbook of Writing Research (2nd ed., pp. 257–71). New York, NY: Guilford Press. Li, X. (1996). ‘Good Writing’ in Cross Cultural Contexts. New York, NY: State University of New York Press. Limpo, T., Alves, R., & Connelly, V. (2017). Examining the transcription-writing link; Effects of handwriting fluency and spelling accuracy on writing performance and translating in middle grades. Learning & Individual Differences, 53, 26–36.
74 3. Executive Control and Writer(s)-Within-Community Limpo, T., & Graham, S. (2019). The role of handwriting instruction in writers’ education. British Journal of Educational Studies, 68(3), 311–29. MacArthur, C., & Graham, S. (1987). Learning disabled students composing under three methods of text production: handwriting, word processing, and dictation. Journal of Special Education, 21, 22–42. MacDonald, K. (2008). Effortful control, explicit processing, and the regulation of human evolved predispositions. Psychological Review, 115, 1012–31. Madigan, R., Linton, P., & Johnson, S. (1996). The paradox of writing apprehension. In C.M. Levy & S. Ransdell (Eds.). The Science of Writing: Theories, Methods, Individual Differences, and Applications (pp. 295–307). Mahwah, NJ: Erlbaum. Many, J.E., Fyfe, R., Lewis, G., & Mitchell, E. (1996). Traversing the topical landscape: exploring students’ self-directed reading-writing-research processes. Reading Research Quarterly, 31(1), 12–35. Martinez, M. (2014). Executive Control in Hispanic Children: Considering Linguistic and Sociocultural Factors. Unpublished Dissertation, University of Nebraska –Lincoln, Lincoln, NE. Matthews, G., Deary, I., & Whiteman, M. (2003). Personality Traits (PDF) (2nd ed.). Cambridge, UK: Cambridge University Press. Mayer, R.E. (2012). Information processing. In K.R. Harris, S. Graham, & T.C. Urdan (Eds.). APA Educational Psychology Handbook: Vol. 1. Theories, Constructs, and Critical Issues (pp. 85–100). Washington, DC: American Psychological Association. McCarthy, S.J. (1994). Authors, text, and talk: the internalization of dialogue from social interaction during writing. Reading Research Quarterly, 29(3), 201–31. McCutchen, D. (1988). ‘Functional automaticity’ in children’s writing: a problem of metacognitive control. Written Communication, 5(3), 306–24. McKeown, D., Brindle, M., Harris, K.R., Sandmel, K., Steinbrecher, T., Graham, S., Lane, K., & Oakes, W. (2019). Teachers’ voices: perceptions of effective professional development and classwide implementation of self-regulated strategy development in writing. American Educational Research Journal, 56, 753–91. Moje, E. (2009). Standpoints: a call for new research on new and multi-literacies. Research in the Teaching of English, 43, 348–62. Moje, E.B., & Lewis, C. (2007). Examining opportunities to learn literacy: the role of critical sociocultural research. In C. Lewis, P. Enciso, & E.B. Moje (Eds.). Reframing Sociocultural Research on Literacy: Identity, Agency, and Power (pp. 15–48). Mahwah, NJ: Erlbaum. Moll, L.C. (1990). Vygotsky and Education: Instructional Implications and Applications of Sociohistorical Psychology. Cambridge, UK: Cambridge University Press. Morphy, P., & Graham, S. (2012). Word processing programs and weaker writers/readers: a meta-analysis of research findings. Reading and Writing: An Interdisciplinary Journal, 25(3), 641–78. Morrow, L.M., & Young, J. (1997). A family literacy program connecting school and home: effects on attitude, motivation, and literacy achievement. Journal of Educational Psychology, 89(4), 736–42. Ojede, N, Aretoul, E., Pena, J., & Schretlen, D. (2016). Age differences in cognitive performance: a study of cultural differences in historical contexts. Journal of Neuropsychology, 10, 104–15. Olinghouse, N.G., Graham, S., & Gillespie, A. (2015). The relationship of discourse and topic knowledge to fifth graders’ writing performance. Journal of Educational Psychology, 107, 391–406. Olive, T., & Barbier, M. (2017). Processing time and cognitive effort of longhand note taking when reading and summarizing a structure of linear text. Written Communication, 34, 1–23. Olive, T., Kellogg, R., & Piolat, A. (2008). Verbal, visual, and spatial working memory demands during text composition. Applied Psycholinguistics, 29, 669–87.
References 75 Paas, F., & Sweller, J. (2014). Implications of cognitive load theory for multimedia learning. In R.E. Mayer (Ed.). The Cambridge Handbook of Multimedia Learning (2nd ed., pp. 27–42). Cambridge, UK: Cambridge University Press. Pajares, F., Johnson, M., & Usher, E. (2007). Sources of writing self-efficacy beliefs of elementary, middle, and high school students. Research in the Teaching of English, 42(1), 104–20. Parrett, W., & Budge, K. (2016). Turning high-poverty schools into high-performing schools. NY: ASCD. Pekrun, R., Frenzel, A.C., Goetz, T., & Perry, R.P. (2007). The control-value theory of achievement emotions: an integrative approach to emotions in education. In P.A. Schutz & R. Pekrun (Eds.). Emotion in Education (pp. 13–27). San Diego, CA: Academic Press. Perry, K. (2012). What is literacy? A critical overview of sociocultural perspectives. Journal of Language and Literacy Education, 8(1), 50–71. Ransdell, S., & Levy, C.M. (1996). Working memory constraints on writing quality and fluency. In S. Ransdell & C.M. Levy (Eds.). The Science of Writing: Theories, Methods, Individual Differences, and Applications (pp. 93–105). Hillsdale, NJ: Lawrence Earlbaum Associates. Rijlaarsdam, G., Van den Bergh, H., Couzijn, M., Janssen, T., Braaksma, M., Tillema, M., Van Steendam, E., & Raedts, M. (2012). Writing. In K.R. Harris, S. Graham, & T. Urdan (Eds.). APA Educational Psychology Handbook (Volume 3, pp. 189–227). Washington, DC: American Psychological Association. Russell, D.R. (1997). Rethinking genre in school and society: an activity theory analysis. Written Communication, 14(4), 504–54. Scardamalia, M., & Bereiter, C. (1986). Research on written composition. In M.C. Wittrock (Ed.). Handbook of Research on Teaching (3rd ed., pp. 778–803). New York, NY: Macmillan. Scardamalia, M., & Bereiter, C. (1985). Fostering the development of self-regulation in children’s knowledge processing. In S. Chipman, J. Segal, & R. Glaser (Eds.). Thinking and Learning Skills: Current Research and Open Questions (Vol. 2, pp. 563–77). Hillsdale, NJ: Erlbaum. Schultz, K., & Fecho, B. (2000). Society’s child: social context and writing development. Educational Psychologist, 35(1), 51–62. Shanahan, T. (2006). Relations among oral language, reading, and writing development. In C.A. MacArthur, S. Graham, & J. Fitzgerald (Eds.). Handbook of Writing Research (pp. 171– 83). New York, NY: Guilford Press. Shermis, M., Burnstein, J., Elliot, N., Miel, S., & Foltz, W. (2016). Automated writing evaluation. In C. Macarthur, S. Graham, & J. Fitzgerald (Eds.). Handbook of Writing Research (2nd ed., pp. 395–409). New York, NY: Guilford. Sperling, M., & DiPardo, A. (2008). English education research and classroom practice: new directions for new times. Review of Research in Education, 32, 62–108. Stanovich, K. (2004). The Robot’s Rebellion: Finding Meaning in the Age of Darwin. Chicago, IL: University of Chicago Press. Stedman, R.C. (2003). Is it really just a social construction? The contribution of physical environment to sense of place. Society and Natural Resources, 16(8), 671–85. Swales, J.M. (1990). Genre Analysis: English in Academic and Research Settings. Cambridge, UK: Cambridge University Press. Swanson, H.L., & Berninger, V.W. (1996). Individual differences in children’s working memory and writing skill. Journal of Experimental Child Psychology, 63(2), 358–85. Takacs, Z., & Kassai, R. (2019). The efficacy of different interventions to foster children’s executive functioning skills: a series of meta-analyses. Psychological Bulletin, 145, 653–97. Torrance, M., Thomas, G.V., & Robinson, E.J. (1996). Finding something to write about: strategic and automatic processes in idea generation. In C.M. Levy & S. Ransdell (Eds.). The Science of Writing: Theories, Methods, Individual Differences, and Applications (pp. 189–206). Mahwah, NJ: Erlbaum.
76 3. Executive Control and Writer(s)-Within-Community Vanderberg, R., & Swanson, L. (2007). Which components of working memory are important in the writing process. Reading & Writing: An Interdisciplinary Journal, 20, 721–52. Wallace, I. (1977). The Writing of One Novel. Richmond Hill, ON: Simon & Schuster. Weiner, B. (1985). An attributional theory of achievement motivation and emotion. Psychological Review, 92(4), 548–73. Wijekumar, K., Graham, S., Harris, K.R., Lei, P., Barkel, A., Aitken, A., Ray, A., & Houston, J. (2019). The roles of writing knowledge, motivation, strategic behaviors, and skills in predicting elementary students’ persuasive writing from source material. Reading & Writing: An Interdisciplinary Journal, 32, 1431–57. Yancey, K.B. (2009). Writing in the 21st Century: A Report from the National Council of Teachers of English. Urbana, IL, National Council of Teachers of English. Zeidner, M., & Matthews, G. (2012). Personality. In K.R. Harris, S. Graham, T.C. Urdan, S. Graham, J.M. Royer, & M. Zeidner (Eds.). APA Educational Psychology Handbook: Vol. 2. Individual Differences and Cultural and Contextual Factors (pp. 111–37). Washington, DC: American Psychological Association. Zimmerman, B.J., & Risemberg, R. (1997). Becoming a self-regulated writer: a social cognitive perspective. Contemporary Educational Psychology, 22(1), 73–101.
III
METHODS FOR ASSESSING EXECUTIVE FUNCTIONS AND WRITING
4 Assessment of Executive Functions in Children Helen St Clair-Thompson and Yunhong Wen
Introduction Executive functions (EFs) are a range of goal-directed cognitive abilities. There have been differing views about the nature of the structure of EFs, and researchers have therefore taken several different approaches to measuring these abilities (see Chapter 2 of this volume). This chapter aims to provide a review of two broad approaches; using cognitive measures and using behavioural rating scales. It will begin with a brief introduction to EFs, and then provide an overview of a range of cognitive assessments used to assess EFs in childhood, with a focus on inhibition, shifting, and updating of working memory. The measures will be considered in terms of their suitability for different purposes and in relation to their use with children of different ages and abilities. The chapter will also consider evidence for the measurement properties of these tools, including data relating to reliability and validity. There will then be a discussion about behavioural ratings of EFs, and a comparison of cognitive measures and behavioural ratings for assessing EFs. The chapter therefore aims to inform the choice of EF measures used in future research. There is a long history of research into EFs, with its origins in neuropsychological studies of patients with frontal lobe damage. Such patients tend to exhibit poor performance on complex frontal lobe or EF tasks (e.g. Shallice & Burgess, 1991). The tasks on which frontal lobe patients have displayed impaired performance have since become important tools for studying the organization and function of EFs. One important research question which has triggered considerable debate is whether EFs are unitary, reflecting the same underlying mechanism, or instead whether they are comprised of several dissociable functions. This is important because it has implications for our understanding of the development and training of these skills, as well as what the potential impact of deficits or damage to specific aspects of function might be and how these difficulties might be subsequently addressed through interventions. To address this question, Miyake et al. (2000) examined the separability of three functions; inhibition, shifting, and updating. Inhibition refers to the ability to inhibit pre-potent responses, shifting describes the ability to shift flexibly between tasks or mental sets, Helen St Clair-Thompson and Yunhong Wen, Assessment of Executive Functions in Children In: Executive Functions and Writing. Edited by: Teresa Limpo and Thierry Olive, Oxford University Press. © Oxford University Press 2021. DOI: 10.1093/oso/9780198863564.003.0004
80 4. Assessment of Executive Functions in Children and updating refers to the updating and monitoring of working memory. Following this approach, the term updating is often used interchangeably with that of working memory. Miyake et al. (2000) asked adult participants to complete a set of experimental tasks that are considered to assess each EF. Confirmatory factor analysis, a statistical technique which explores the associations between different variables or constructs, indicated that the three EFs were moderately correlated with one another, but clearly separable. The separability of inhibition, shifting, and updating has been since been further demonstrated in several empirical studies (e.g. Friedman et al., 2006; Friedman et al., 2008; Vaughan & Giovanello, 2010). Studies with children, however, have suggested that there is a gradual differentiation of EFs during development, with EFs transitioning from a single function to a group of diverse and interactive processes (e.g. Bardikoff & Sabbagh, 2017; Brydges, Fox, Reid, & Anderson, 2014; Karr, Hofer, Iverson, & García-Barrera, 2018). Researchers have also explored a variety of other EFs, including for example, planning, organization, self-regulation, and fluency (e.g. Packwood, Hodgetts & Tremblay, 2011). However, the tripartite model of EFs examined by Miyake et al. (2000) has become the commonly used approach in both cognitive and developmental psychology literature. A huge number of different tasks have been used to assess these EFs, but some are more frequently used than others. For example, Nyongesa et al. (2019) reviewed the measures of EFs that have been used in studies conducted among adolescents in the past 15 years. Ten measures were the most frequently used, accounting for nearly half of all reported measures. Putting aside questionnaire measures, which are discussed later in this chapter, and tasks assessing other functions (such as retrieval from long-term memory, selective attention, and visual memory), these frequently used tasks included Stroop tasks to assess inhibition, the Trail Making Test and the Wisconsin Card Sorting Test to assess shifting, and the digit span task to assess working memory. In the next section we therefore provide an overview of some well-known measures that have been used to assess each of these aspects of EFs, including the most popular tasks according to Nyongesa et al., before moving on to discuss some important issues that researchers should consider if intending to use these measures.
Cognitive Tasks In this section we offer a brief description of some of the most commonly used tasks for assessing inhibition, shifting, and updating working memory. Inhibition. One of the most commonly used tasks employed to assess inhibition in both adults and children has been the Stroop task (Stroop, 1935). In this task there are three conditions in which participants have to name the colour of the ink that stimuli are presented in. In the neutral condition the stimuli are strings of asterisks, in the congruent condition the stimuli are colour words and the ink colour and word are the same (e.g. ‘BLUE’ is presented in blue ink), and in the incongruent condition the
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stimuli are colour words that are different to the ink colour (e.g. the word ‘RED’ presented in blue ink). In this latter condition participants have to inhibit the tendency to read the word in order to name the ink colour. To control for colour naming speed researchers commonly use a score of the difference in time taken to complete the neutral and incongruous conditions (Brydges, Reid, Fox & Anderson, 2012; Brydges et al., 2014). In other popular inhibition tasks participants have to inhibit irrelevant stimuli. In the Eriksen flanker task (Eriksen & Eriksen, 1974) participants are presented with a target stimulus which is flanked by either congruent or incongruent stimuli. For example, participants are presented with arrows. A target arrow is flanked by four arrows pointing in the same direction (congruent condition) or by four arrows pointing in a different direction (incongruent condition). Participants are required to identify the direction of the target arrow as quickly and accurately as possible. The reaction time and accuracy for both congruent and incongruent conditions are recorded (e.g. Huizinga Dolan, & Van Der Molen, 2006), with the incongruent condition being the one that reflects inhibitory processes. Another task which assesses the ability to deal with incongruent information is the Simon task (Simon & Berbaum, 1990). In this task, red and green rectangles appear randomly on the left or right side of a computer screen. Participants are asked to press a button on the left when they see a red rectangle or press a button on the right when they see a green rectangle. Congruent conditions are when the stimulus and required response are on the same side (e.g. red triangle on the left), and incongruent conditions (requiring inhibition) are when the stimulus and required response are on opposite sides (e.g. green triangle on the left). Commonly, researchers record the number of correct responses and the reaction time for correct responses (RT) on incongruent trials (Engel de Abreu et al., 2014). Other inhibition tasks include stop-signal tasks, in which some trials encourage the development of a particular response, but on other trials this response has to be inhibited. For example, Van Boxtel, Van Der Molen, Jennings, and Brunia (2001) asked participants to respond as quickly as possible to a left or right pointing arrow using a left or right button press. The colour of the arrow changed from green to red on 20% of the trials, indicating that participants should suppress their response. Typically, the correct rate for inhibiting a response on stop trials is recorded (Huizinga et al., 2006). Similarly, go/no-go tasks (e.g. Durston et al., 2002) require participants to respond to ‘go’ signals, and make no response to ‘no-go’ signals, therefore requiring the inhibition of a response to no-go trials. The proportion of correct responses and RT to go and no-go signals are usually recorded (Brydges et al., 2014; Howard, Okely & Ellis, 2015). Some researchers have also assessed inhibition using the Tower of Hanoi (Simon, 1975; Welsh, Pennington, & Groisser, 1991) or the Tower of London (Shallice, 1982) tasks. In these tasks, participants have to move objects to reach a goal state in as few moves as possible, while following some predefined rules. It is, however, important to note that these tasks were originally considered as tests of planning and problem solving, although empirical evidence has supported the view that they are
82 4. Assessment of Executive Functions in Children instead inhibition tasks (Lehto, Juujärvi, Kooistra, & Pulkkinen, 2003). Later we will discuss such important issues surrounding the utility of EF measures. There are also additional inhibition tasks which have been designed and used particularly with young children. For example, the Statue task is a motor inhibition task from the Developmental Neuropsychological Assessment (NEPSY II; Brooks, Sherman, & Strauss, 2009), which requires children to stand in a statue pose for 75 seconds. The examiner attempts to distract children, for example by coughing or dropping a pencil. Successful performance therefore relies upon the ability to ignore these distractions. Another widely used task, modelled on the Stroop task, is the day–night task (Gerstadt, Hong, & Diamond, 1994). In this task children are shown pictures of daytime and night-time skies but asked to respond ‘day’ to the night-time pictures and ‘night’ to the daytime pictures. Like the Stroop task this therefore requires the inhibition of a dominant response associated with a perceptual stimulus. Correct responses and response times can be recorded. Shifting. One frequently used task of shifting is the Trail Making Task (McLean & Hitch, 1999; Reitan & Wolfson, 2004). This is a pen and paper task which usually has two parts. Part A requires participants to connect a set of irregularly located numbers (e.g. from 1 to 50), and part B requires participants to connect numbers (e.g. from 1 to 25) and letters (e.g. from A to Y). In the latter part participants need to connect 1 to A, then continue to 2 and B, and so on. This therefore requires them to shift between the two mental sets of numbers and letters. The scores awarded can be correct connections within a given time (van der Sluis, De Jong, & Van Der Leij, 2007); completion time for each part (Lehto et al., 2003); or difference between the time taken to complete Part A and Part B (Rose, Feldman, & Jankowski, 2011). Another commonly used measure of shifting is the Wisconsin Card Sorting Test (WCST; Grant & Berg, 1948). This requires participants to sort cards according to one of three dimensions: colour, shape, or number. Participants are not told the dimension, but they receive feedback regarding whether or not each card was correctly sorted. The dimensions change after ten consecutive trials, after which a participant needs to work out the new dimension that they should be matching for. The score is the number of perseverative errors, in which a participant does not change their categorization strategy even though the feedback indicated that their response was incorrect (Brydges et al., 2012; 2014); or the numbers of completed categories, which is the number of runs of ten correct responses (Arán-Filippetti, 2013). There has, however, been somewhat of a debate about what the WCST actually measures, with it being proposed as a measure or ‘mental set shifting’, ‘inhibition’, ‘cognitive flexibility’, ‘problem solving’, and ‘organization/categorization’, just to name a few suggestions (Greve et al., 2005; Miyake, Emerson, & Friedman, 2000). We will return to this issue later in the chapter. Another shifting task is the Intra-Extra Dimensional Set Shift task (ID/ED, Cambridge Cognition, 1996). This involves the presentation of stimuli formed of pink shapes and white lines. Initially stimuli are made up of just one dimension, e.g. two white lines that differ in shape, but later on compound stimuli are used, e.g. white
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lines overlaid on the pink shapes. Participants have to work out the rule that determines which stimuli are correct. After six correct responses, the stimuli and/or rule changes. The shifts in rule are initially intradimensional (i.e. the pink shapes remain the only relevant dimension) and then later extradimensional (i.e. white lines become the relevant dimension). The scores awarded reflect the number of errors made, the number of trials completed, the number of stages completed and reaction time (Cambridge Cognition, 1996). Similarly, shifting can be assessed using the Dimensional change card sort (DCCS, Zelazo, 2006), which has been widely used with pre-school aged children (Miller et al., 2012; Viterbori, Usai, Traverso, & De Franchis, 2015). Children are asked to sort two different types of cards (i.e. rabbit and boat) based on either colour or shape. The administrator presents and clarifies both dimensions for the children and chooses one dimension (i.e. colour) as the sorting rule for the pre-switch phase. After six pre- switch trials, post-switch trials are administered (i.e. shape). The administrator repeats the rule for each trial but does not provide feedback, and never presents the same type of card on more than two consecutive trials. The score for this task is the number of correctly sorted cards for all trials. Instead of relying on shifts between attentional sets, there are other tasks which require participants to shift their attention between different locations. For example, in the letter monitoring task (Duncan et al., 1996) children read stimuli from one side of a computer screen as they appear, while ignoring stimuli on the opposite side. On half of the trials, children are asked to shift their attention to the other side of the screen. Researchers are interested in the number of trials on which a child switches correctly. Updating working memory. Many theoretical approaches to working memory distinguish between storage and processing, or between short-term memory and the requirement for attentional-executive resources. For example, the most commonly used model of working memory was proposed by Baddeley and colleagues (e.g. Baddeley & Hitch, 1974; Baddeley 2000). This proposes that working memory is comprised of two domain specific storage systems; the phonological loop and visuospatial sketchpad, and a domain general central executive. Thus measures of working memory have been designed to assess both verbal and visuospatial domains, and to assess both storage and processing. Based around the multiple-component model of working memory (Baddeley & Hitch, 1974), tasks used to assess the phonological loop include those that require participants to recall verbal information in serial order, such as the digit span and word span tasks. However, a commonly used variant is the backwards digit span task, in which participants have to recall series of digits in reverse order. This is assumed to require executive resources in addition to the phonological loop. Tasks used to assess the visuospatial sketchpad require participants to remember visual or spatial information. For example, in the pattern recall task participants view two-dimensional grids consisting of filled and unfilled squares. The pattern disappears and the participant is asked to recreate the same pattern. In the Block recall test (sometimes called the Corsi Blocks task), the participant views cubes which are located randomly on a board.
84 4. Assessment of Executive Functions in Children The administrator taps a sequence of blocks and participants repeat the sequence in the same order. Tasks used to assess the central executive, often called complex span tasks, include tasks that require both the processing and storage of information. For example, in the listening recall test, the participant listens to a series of short sentences and is asked to judge the veracity of each sentence by responding ‘yes’ or ‘no’. Then the participant is required to recall the last word of each sentence in the same order that the sentences were presented. There are also equivalent tasks requiring the processing and storage of visuospatial information, for example, Shah & Miyake (1999) developed Symmetry Span, in which participants made symmetry judgements and remembered spatial locations. Typically, working memory tasks start with only one or two items to remember, increasing over successive trials if a participant is successful in recalling the information. The score awarded is often the maximum number of items that can be recalled (often termed memory span), although researchers have also used the number of trials on which items have been recalled correctly, and sometimes given partial credit for some correct items in a trial (e.g. Conway et al., 2005). Other tasks used to assess working memory, that perhaps more clearly assess the process of ‘updating’, include the N-back paradigm (Owen, McMillan, Laird, & Bullmore, 2005) and running memory span (Broadway & Engle, 2010). The N-back paradigm requires participants to monitor the identity or location of a series of verbal or non-verbal stimuli and to indicate when the currently presented stimulus is the same as the one presented in N trials previously. The N-back paradigm has been commonly used for assessing working memory in the field of neuroscience. The responses that participants provide are simple compared with other working memory tasks like the working memory span tasks described earlier, researchers can easily record both accuracy and reaction time, and the timing of stimulus presentation can be altered easily, as can the level of difficulty by changing the value of N. The paradigm is therefore well suited to neuroscience research. In the Running span task (Broadway & Engle, 2010), participants are asked to view a running sequence of letters or numbers, and are asked to recall the last N items when each sequence has ended. Thus, participants have to continually update the contents of working memory, discarding older items and replacing them with newer and more relevant items. The score awarded is the number of correct target items recalled in their correct place in the presented sequence. Sometimes versions of this task are referred to as keep-track tasks.
Important Considerations When Choosing Cognitive Tasks The previous section provided a description of several measures of EFs. But how does a researcher decide which measure(s) to use in their study? This section aims to present four key factors that researchers should consider; developmental appropriateness, reliability, validity, and task impurity.
Important Considerations When Choosing Cognitive Tasks 85
Developmental appropriateness. An important issue when using EF tasks with children is to consider the demands of a task in terms of whether it is developmentally appropriate. Choosing a task which is too easy or too difficult is of course likely to lead to ceiling effects or floor effects. For example, tasks that work well with preschoolers (e.g. the day–night task) are too simple for children older than 6 or 7 years, causing ceiling effects. Older children’s scores will cluster near the maximum possible, with little or no variability to detect individual differences or correlations with other variables of interest. Similarly, the ID/ED task is too easy for children over the age of 12 years, not discriminating between children of higher abilities (Syväoja et al., 2015). Conversely, many tasks that work well with older children are too difficult and demanding for younger participants. If working with young children, Hughes and Graham (2002) suggested that an important consideration when assessing EFs is language limitations. Complex task instructions may place demands upon non-EFs, and due to cognitive load this may effect overall task performance. In addition, tasks that themselves tap the domain of language may not assess the proposed EFs because fluent literacy emerges relatively late in childhood development. Take, for example, the Stroop task described earlier. It is assumed that this relies on the ability to inhibit the automatic prepotent response of reading the words rather than naming its colour. However, in young children reading may not yet be such an automatic process, therefore limiting the extent to which the task requires inhibition. Hughes and Graham therefore suggested using tasks which do not impose such verbal demands, such as the Day/Night task, or simple party games such as ‘Simon says’ (in which an action must only be performed if the instruction begins with the phrase ‘Simon says . . .’, e.g. Zelazo & Jacques, 1997). Additional considerations when working with young children include the type of stimuli used in a task and the length of time it takes for a task to be administered. For children to be engaged in a task it should use developmentally appealing and appropriate test stimuli, and of course tasks should be relatively short or comprised of multiple short tasks, in order to accommodate the limited attention span of young children. These issues were considered by Epsy, Kaufman, Glisky, and McDiarmid (2001), who adapted several tasks from the developmental psychology and neuroscience literature to employ with children from aged 30 months to 60 months. They concluded that their measures had been useful for examining EFs in preschool children. When considering developmental appropriateness, is it important to note that this does not just refer to children’s chronological age. EF is a topic of interest in relation to many disorders of development, including Autism and ADHD (e.g. Craig et al., 2016), Williams Syndrome and Down Syndrome (e.g. Carney, Brown, & Henry, 2013), Specific Language Impairment (e.g. Pauls & Archibald, 2016), and dyslexia (e.g. Moura, Simões, & Pereira, 2015). In many cases, autism, ADHD, Williams syndrome, and Down’s syndrome are accompanied by deficits in verbal and/or visuospatial abilities which need to be considered when choosing appropriate cognitive measures. In addition to the development of EFs relying on the maturation of associated brain regions it also relies on stimulation in the child’s social context, meaning
86 4. Assessment of Executive Functions in Children other important factors to consider are the home and school environment (Huizinga, Baeyens, & Burack, 2018) and socioeconomic status (John, Kibbe, & Tarullo, 2019; Last et al., 2018). There are therefore a range of issues to consider when determining the developmental appropriateness of an EF task. This has led many researchers to modify the stimuli, administration, and scoring of EF tasks when using them with young children. For example, McDermott, Pérez-Edgar, and Fox (2007) examined versions of the Eriksen flanker task in which flanker stimuli were congruent or incongruent with the target item in terms of colour or shape (rather than in terms of the direction of an arrow). Carver, Livesey, and Charles (2001) reduced the number of trials in a stop- signal task and also increased the length of stimulus presentation. Golden, Freshwater, and Golden (2003) designed a version of the Stroop task for young children to avoid issues that might arise as a result of applying adult scoring procedures to children’s data. Determining the suitability of an EF task for children of a certain age is therefore a tricky task, and should involve an examination of the previous literature but also an in-depth analysis of the task’s requirements. To aid future research, the minimum age of participants for each cognitive measure of EF described earlier in this chapter is shown in Table 4.1, supported by a relevant reference. However, due to the heterogeneity found in atypically developing groups, here we focus only on typically developing children. It is also important to note that versions of these tasks varying in stimuli, administration, and scoring may have been used with younger children, but here we focus on common practice. Reliability. Another important consideration when selecting EF tasks is of course their reliability. Surprisingly, only a small proportion of studies report reliability of the EF tasks employed. For example, Nyongesa et al. (2019) identified the most frequently used measures of EF within adolescence, and from 705 relevant studies only 48 reported the reliability and/or validity of their tasks. Several studies have actually demonstrated poor reliability of commonly used EF tasks. For example, Humes, Welsh, Retzlaff, and Cookson (1997) examined the reliability of the Tower of Hanoi and Tower of London tasks. Performance on the Tower of Hanoi task (across several trials of varying difficulty) resulted in a high split-half reliability of 0.87, however the Tower of London task showed a split-half reliability of only 0.19. Bowden et al. (1998) examined the reliability of alternate forms of the WCST, considering several performance indicators including perseveration errors and the number of categories achieved. Reliability ranged from 0.25 to 0.63, with an average of 0.43. Pelegrina et al. (2015) discussed the reliability of the N-back task. They suggested that reliability has varied greatly across studies, from r = 0.16 (Van Leeuwen, Van den Berg, Hoekstra, & Boomsma, 2007) to r = 0.91 (Friedman et al., 2008). Jaeggi, Buschkuehl, Perrig, and Meier (2010) suggested that the N-back task is not a useful measure of working memory, partly because of its insufficient reliability. Other studies have suggested more promising reliability of EF measures. For example, the day–night task appears to possess suitable internal reliability and test- retest reliability (e.g. Chasiotis, Kiessling, Winter, & Hofer, 2006; Rhoades, Greenberg,
Table 4.1 A summary of key considerations for cognitive measures Executive function
Task
Minimum age
Other important considerations
Inhibition
Stroop Task
Aged 5 (Golden et al., 2003)
Higher reliability may come from using reaction times rather than considering the difference between conditions.
Flanker Task
Aged 4 (McDermott et al., 2007)
Has been shown to be a reliable and valid measure, but researchers employing this measure should analyse reaction times, rather than considering the number of correct responses.
Simon Task
Aged 6 (Van der Ven, Kroesbergen, Boom, & Leseman, 2013)
Commonly used, and shown to have reasonable reliability.
Stop-Signal Task
Aged 4 (Carver et al., 2001)
Has been demonstrated to be reliable in a range of samples varying in ages and ability.
Go/No-go Tasks
Aged 3 (Wiebe, Sheffield, & Espy, 2012)
Have been shown to have reasonable reliability.
Tower Tasks
Aged 7 (Anderson, Anderson, & Lajoie, 1996)
May place demands upon planning and problem solving as well as inhibition. Research has also revealed weak correlations between scores on different tower tasks.
Statue Task
Aged 3 (Brooks et al., 2009)
Particularly useful for preschool children but likely to lead to ceiling effects in older children.
Day/Night Task
Aged 3 (Montgomery & Koeltzow, 2010)
Particularly useful for preschool children but likely to lead to ceiling effects in older children. Seems to have good reliability.
Trail Making
Aged 9 (McKinlay, 2011)
Is subject to practice effects which may warrant the use of alternative forms.
WCST
Aged 6 (Heaton et al., 1993)
Commonly used, but may also tap inhibition and working memory. Some studies have raised concerns about reliability.
ID/ED Task
Aged 6 (Abu-Akel et al., 2018)
Seems to have good reliability, but is not suitable for children aged 12 and above due to not discriminating between those of a higher ability.
Shifting
Continued
Table 4.1 Continued Executive function
Updating working memory*
Task
Minimum age
Other important considerations
Dimensional Change Sort Task
Aged 3 (Miller et al., 2015)
Particularly useful for preschool children due to its simplicity.
Letter Monitoring
Aged 4 (Towse et al., 2007)
A less commonly used task, and sometimes assumed to assess goal neglect rather than shifting.
Backwards Digit Recall
Aged 4 (Alloway, Gathercole, Kirkwood, & Elliott, 2008)
There have been numerous demonstrations of the reliability of complex span tasks in both children and adults, although in older children this task may place more demand upon storage than executive abilities.
Listening Recall
Aged 4 (Alloway, Gathercole, Kirkwood, & Elliott, 2008)
There have been numerous demonstrations of the reliability of complex span tasks in both children and adults.
Symmetry Span
Aged 8 (Gonthier, Aubry, & Bourdin, 2018)
There have been numerous demonstrations of the reliability of complex span tasks in both children and adults.
N-Back Tasks Aged 7 (Pelegrina et al., 2015)
Well suited to neuroscience research, but performance is only weakly correlated with that on complex span tasks, and concerns have been raised about reliability.
Running Aged 6 Memory Span (Van der Ven, Kroesbergen, Boom, & Leseman, 2012)
Has suitable reliability in both children and adults, although researchers should be cautious about making conclusions based on these measures due to the different strategies that can be used for task completion.
*Note: Here we focus only on measures assumed to assess working memory, not including measures only requiring the storage of information.
Important Considerations When Choosing Cognitive Tasks 89
& Domitrovich, 2009). The reliability of complex span tasks used to assess working memory is also well-established (Conway et al., 2005). However, it is important to remember that reliability also varies between children of different ages. For example, the test-retest reliability of the backwards digit recall test is 0.53 for children aged 5 to 7 years, and 0.71 for 9-to 11-year-old children (Gathercole, Pickering, Knight, & Stegmann, 2004). It is also important to establish reliability in particular populations, for example the stop-signal task has been shown to have reasonable test-retest reliability in healthy populations and various participant groups (Soreni, Crosbie, Ickowicz, & Schachar, 2009; but see Wöstmann et al., 2013). Reliability may also vary depending on the scoring method which is used for a particular task. For example, Strauss, Allen, Jorgensen, and Cramer (2005) suggested good reliability of reaction times on the Stroop task, but lower reliability for difference scores assumed to indicate inhibition cost. Wöstmann et al. (2013) found good reliability on the Eriksen flanker task when using reaction times, but poor reliability when considering the number of correct or incorrect responses (which was likely due to a ceiling effect). Miyake, Emerson, and Friedman (2000) discussed several potential explanations for findings of low reliability on EF tests. They suggested that people may adopt different strategies on different occasions, or even on different trials within an EF task. In addition, because the involvement of EFs is generally considered strongest when a task is novel, they suggested that repeated encounters with a task may reduce its effectiveness in assessing the target EF, leading to low correlations between performance when a task is novel and later performance when a task becomes more familiar (thus particularly effecting test-retest reliability). Novelty is an important issue; for example, studies have demonstrated significant improvements on both parts A and B of the trail making task when repeatedly administered, suggesting the need to consider using alternative forms (Wagner et al., 2011). There have also been additional discussions about the importance of strategies for executive function task performance. Although the running memory span task may have suitable test-retest reliability (Waters & Caplan, 2003), it can be completed using at least two very different strategies (Bunting, Cowan, & Saults, 2006). One is a less demanding strategy of monitoring the letters and then actively retrieving the final items, and the other a more demanding strategy of continually updating the contents of the working memory store. Therefore, it is suggested that when choosing EF measures researchers explore existing literature for reports of the reliability of EF measures in particular age groups, for particular scoring methods, but also seek to demonstrate reliability in their own samples. Validity. Another issue which is important to researchers when choosing EF tasks is validity; that a task accurately assesses the cognitive processes that it is intended to assess. Researchers have raised concerns about the validity of several well- known EF tasks. This issue can be clearly highlighted by considering the different types of working memory task discussed earlier in this chapter. The frequent use of two kinds of tasks; working memory span tasks and the N-back task, has led to researchers examining the relationship between scores on these measures. Kane,
90 4. Assessment of Executive Functions in Children Conway, Miura, and Colflesh (2007) reported weak correlations between working memory span and N-back scores, in the range of 0.20. Redick and Lindsey (2013) then conducted a meta-analysis and the estimated mean correlation was 0.20. The authors concluded that working memory tasks and N-back tasks must not be used interchangeably as indicators of a common working memory construct. The weak relationships between scores on these tasks may be due to several important differences between the N-back task and other measures of working memory. The N-back task relies on recognition processes whereas other working memory tasks require the retrieval of information. In addition, N-back tasks may depend on the inhibition of no-longer-relevant information as the contents of working memory is updated, and the formation of bindings between items and their temporal context (e.g. Oberauer, 2005; Kane et al., 2007). Research has also revealed only a weak relationship between scores on other EF tasks that are assumed to be tapping the same aspect of EF. Shilling, Cheywynd, and Rabbitt (2002) revealed that scores on variants of the Stroop task were not correlated with one another, and Welsh, Revilla, Strongin, and Kepler (2000) described a lack of correlation between performance on the Tower of London and Tower of Hanoi (with correlations ranging from 0.37 to 0.61). This highlights the need for researchers to carefully consider the demands of executive tasks of choice, and to use more than one EF task to tap each construct of interest so that common variance can be considered. Task impurity. Another obstacle when measuring EFs is that many tasks demand the use of several cognitive functions. This has often been referred to as the ‘task impurity problem’ and has been considered by many researchers studying EFs among children and adolescents (e.g. Lee, Bull, & Ho, 2013; van der Sluis et al., 2007). Ozonoff (1997) suggested that several widely used measures of EF, including the WCST, the Tower of Hanoi, the Trail Making Test, and the Stroop task involve more than one EF. Morris (1996) also found that several measures of EF were used by other researchers as measures of attention. Therefore, there is a debate about the underlying processes which are measured by EF tasks. As discussed earlier, the WCST is primarily used to test the shifting function of executive processes, but other researchers (Wang, Kakigi, & Hoshiyama, 2001) maintain that WCST involves inhibition and working memory. When a category switch occurs, participants have to suppress or inhibit the former response, and update their working memory with the new rule. The Tower of London has been employed as a measure of inhibition by some researchers (e.g. Lehto et al., 2003), but has also been viewed as a measure of problem solving and planning (Klenberg, Korkman, & Lahti-Nuuttila, 2001), and working memory and attention (Sikora, Haley, Edwards, & Butler, 2002). The word fluency test, in which participants have to provide as many words as they can from a given category or starting with a particular letter, was also viewed as a measurement of shifting by Lehto et al. (2003), but is considered by others as assessing the ability to retrieve information from long-term memory (e.g. Fisk & Sharp, 2004). The letter monitoring task has
Self-Reports 91
also been considered as a measure of goal neglect as well as a measure of shifting (Duncan et al., 1996; Towse, Lewis, & Knowles, 2007). One solution to this problem is to use multiple measures for assessing an EF. The common variance drawn from the measures is a better indicator of EF than the score on only one test. This was the approach taken by Miyake et al. (2000) in the seminal study discussed earlier. Another suggested solution though is to use control tasks. These control tasks are designed to be very similar to EF tasks, but do not actually require the engagement of EFs. EF ability can then be measured by examining the difference in performance between the EF task and its control counterpart (van der Sluis et al., 2007). For example, in the Stroop task discussed earlier this could be the difference between congruent and incongruent trials, in the trail making task this could be the difference between the numbers only and the number-letter switch conditions, and in working memory tasks this could be the difference between a working memory task and a short-term memory task with the same memory requirements (with the latter not requiring any kind of processing). Having discussed several issues to consider when choosing cognitive measures of EFs, a summary of some of the key findings in relation to reliability, validity, and task impurity of commonly used tasks is presented alongside the suitable age range for the tasks in Table 4.1.
Self-Reports In the previous section we discussed one approach to the measurement of EFs; that of using cognitive measures. Here we discuss the second approach; using self or proxy report behavioural rating scales. We begin with a brief overview of self-report measures, and then provide some examples of behaviours that are related to inhibition, shifting, and updating working memory. Although many researchers and practitioners assess EFs using laboratory-based performance tests, it is important to note that they are limited in terms of their ecological validity; the ability to predict functioning in the everyday environment. To capture everyday manifestations of EFs, rating scales have been developed to assess an individuals’ behaviour in their day-to-day environments. These measures are based on the premise that parents and teachers or sometimes the person themselves can provide useful information about EFs by reporting on their behaviour outside of a laboratory environment. Rating scales offer a complementary approach to performance-based assessment. Several executive function rating scales have been developed, including for children the Childhood Executive Functioning Inventory (CHEXI; Thorell & Nyberg, 2008; Thorell & Catale, 2014), the Comprehensive Executive Function Inventory (CEFI; Naglieri & Goldstein, 2013) and the Delis Rating of Executive Function (D-REF; Delis, 2012). Toplak, West, and Stanovich (2013) provide a
92 4. Assessment of Executive Functions in Children useful overview of several scales. Alternative methods have also been used to assess executive dysfunction in clinical populations. However, here we predominantly focus on the most commonly used rating scale of EFs in the extant literature; the Behavior Rating Inventory of Executive Function (BRIEF; Gioia, Isquith, Guy, & Kenworthy, 2000). The BRIEF is a rating scale that can be completed by parents and teachers of children aged 5–18 years. It allows the assessment of the everyday behavioural manifestations of EFs in the home and at school. It includes 86 items assessing 8 facets of executive function; Inhibit, Shift, Emotional Control, Initiate, Working Memory, Plan/Organize, Organization of Materials, and Monitor. The scale also includes two validity scales—Inconsistency and Negativity. Based on the factor structure, the 8 scales form two broader indexes, Behavioral Regulation and Metacognition, as well as an overall score (the Global Executive Composite). Although the BRIEF was developed for children aged 5–18 years, there is also a pre-school version for children aged 2–5 (BRIEF-P), a self-report version for adolescents aged 11–18 years (BRIEF-SR), and a self-report version for adults aged 18–90 years (BRIEF-A). Alongside the brief are normative data, characterizing what is usual for particular populations. Normative data are based on a large sample of children from rural, suburban, and urban areas, with a distribution of socioeconomic status, ethnicity, and gender. Although the BRIEF assesses 8 aspects of EF, to enable a comparison with the performance-based measures of EFs discussed earlier, a behavioural description and some example items assessing inhibition, shifting, and updating working memory are shown in Table 4.2. An important feature of the BRIEF is that some of its scales have no parallel performance‐based measures of executive function. These include the Initiate and Organization of Materials scales.
Table 4.2 Descriptions of executive functions and example items from the BRIEFs Executive construct
Behavioural description
Example item
Inhibition
Control impulses; appropriately stop own behaviour at the proper time
‘Gets out of seat at the wrong times’
Shifting
More freely from one situation, activity, or aspect of a problem to another as the situation demands; transition; solve problems flexibly
‘Takes the same approach to a problem over and over even when it does not work’
Updating working memory
Hold information in mind for the purpose of completing a task; stay with, or stick to, an activity
‘When given three things to do, only remembers the first or last’
Choosing a Rating Scale of EF 93
Important Considerations When Choosing a Rating Scale of Executive Function The earlier section on cognitive tasks provided a discussion of important considerations when employing cognitive measures of inhibition, shifting, and updating working memory. Here we present important considerations related to rating scales of EFs; reliability and validity. Several investigations have revealed good reliability of the BRIEF in children aged 5–18 years. For example, Gioia and Isquith (2011) reported high internal consistency (Cronbach’s alphas of 0.80–0.98) for both parent and teacher versions, and also high test-retest reliability (mean r = 0.82 for normative samples). Evidence for validity has come from several avenues, including findings of high inter-rater agreement for item-scale assignments, factor analytic studies, and structural equation modelling. Convergent validity has also been demonstrated, for example through evidence of correlations with scales of inattention and impulsivity (for a review on the validity of the BRIEF, see Strauss, Sherman, & Spreen, 2006). The BRIEF has also been shown to be reliable and valid in lots of different populations, including for example from Spain (Fernández et al., 2014), China (Qian & Wang, 2007), and Iran (Amani, Gandomani, & Nesayan, 2018). Importantly, the evidence of reliability and validity for the BRIEF has commonly been gathered from typically developing populations. This means that we need to exert caution in interpretation of the findings from the tool when used with children and young people with neurodevelopmental conditions. Future research should also aim to further demonstrate the reliability and validity of the BRIEF is varying atypical groups. Although the BRIEF has been shown to be reliable and valid, an important consideration, however, that applies to any type of self-report scale is that reports can be influenced by a number of factors, including bias as well as personal, cognitive, or other characteristics of informants (e.g. Grace & Malloy, 2001; Silver, 2014). In terms of bias, Dekker, Ziermans, Spruijt, and Swaab (2017) suggested that ratings may be influenced by the halo effect, central tendency bias, and leniency bias. Within the current context, the halo effect is a bias in which one’s overall feelings towards another produces overly positive or overly negative evaluations of them (for example if a teacher holds a child in high regard they may overestimate their abilities). The central tendency bias describes the tendency for informants to choose answers more towards the middle of a scale, rather than providing extreme responses (e.g. leading to a response that a problematic behaviour occurs ‘sometimes’ rather than ‘often’). Leniency bias simply describes the tendency to report others’ behaviours leniently, and is a bias displayed by some individuals more often than others. A useful consideration when using the BRIEF then, may be to collect information about behaviour from a variety of sources (e.g. both parent and teacher reports), and if appropriate triangulate this with cognitive indicators of EFs as a way to minimize bias. In the earlier section on cognitive measures of EFs, we discussed the importance of choosing tasks that are developmentally appropriate for the population of interest. One of the benefits of instruments like the BRIEF may be in their suitability for a wide
94 4. Assessment of Executive Functions in Children range of ages, reducing the requirement to consider developmental appropriateness. However, it is important to note that some rating scales of EFs have been developed and used predominantly for certain populations. For example, the Barkley Deficits in Executive Function Scale (BDEFS; Barkley, 2011), Barkley Deficits in Executive Functioning Scale—Children and Adolescents (BDEFS-CA; Barkley, 2011), and the Frontal Systems Behavior Scale (FrSBe; Grace & Malloy, 2001) are designed to capture executive dysfunction in clinical settings rather than the general population. Thus when choosing a rating scale the population of interest and the normative sample therefore need to be considered.
Cognitive Measures Versus Rating Scales In this chapter we have introduced both cognitive measures and rating scale measures of EFs, as two potential methods to assess the same underlying construct. However, does this mean that the two types of measures can be employed interchangeably, and that they produce the same research findings? In this section we consider the similarities and differences between cognitive measures and rating scales. It is important to note that the associations between scores on performance-based executive tasks and scores on rating scales of EFs are consistently weak. For example, Toplak et al. (2013) reviewed a number of studies which provided correlations between scores on cognitive measures and rating scales of EFs. Out of 182 reported correlations, only 35 were statistically significant (19%). In the studies that reported the correlation values, the mean correlation was 0.15 and the median correlation was 0.18. They therefore concluded that the association between ratings on the BRIEF and performance‐based measures of EFs were extremely weak. Similar conclusions have been reached in several studies using a range of typically and atypically developing groups of different ages (e.g. see Tan, Delgaty, Steward, & Bunner, 2018). It has therefore been proposed that the two types of assessment likely measure different aspects of EFs. For example, it has been suggested that the EF construct can be fractionated into a behavioural component that is assessed by the BRIEF and a cognitive component that is assessed by performance-based tasks. However, this is inconsistent with findings from neuroimaging studies suggesting that the two sets of measures share a common neuroanatomical substrate (Mahone et al., 2009). An alternative explanation, which is perhaps inherent in the original development of rating scales, is that performance-based tasks assess underlying skills whereas rating scales assess the application of those skills at home and at school. The application of skills may also be influenced by environmental variables, which may explain why parent and teacher ratings do not necessarily correspond to cognitive test scores (e.g. Mcauley et al., 2010).
How to Select a Measure of Executive Functioning 95
Toplak et al. (2013) further discussed the distinction between cognitive measures and rating scale measures as reflecting different cognitive levels; algorithmic and reflective. The algorithmic level relates to information process mechanisms, such as those required for performance-based tasks, whereas the reflective level (rating scales) is concerned with the goals and beliefs of a person. Another important distinction between cognitive measures and ratings of behaviour is that between measures of maximum and typical performance. This is a distinction which has historically been made by psychometricians. On measures of maximum performance (cognitive tasks) tasks are highly constrained and participants are instructed to perform as well as possible. On measures of typical performance (questionnaires) task interpretation is somewhat subjective, and the issue is what a person would typically do in particular situations.
How to Select a Measure of Executive Functioning So far in this chapter we have described both cognitive measures and rating scales of EFs, and commented on their relationships. We have also discussed several issues to consider when choosing an EF assessment. To conclude this chapter, Figure 4.1 presents a flowchart intended to guide the decision-making processes when choosing a suitable measure of EFs. This can be used in combination with Table 4.1 for cognitive measures. The first decision a researcher needs to make is which of the two broad approaches is more appropriate; using cognitive performance measures or behavioural indicators of EF. This decision may depend on the research question. If a study is concerned with cognitive or neuropsychological performance then measures of cognitive performance are likely to be appropriate, but if a study is concerned with the application of executive skills in a home or learning environment then behavioural indicators may be more suitable. If a researcher chooses cognitive performance measures they should then consider the component(s) of EF that they want to assess (e.g. inhibition, shifting, or updating of working memory). They should then consider the age of participants, so they can choose a task which is developmentally appropriate (see Table 4.1), and with a particular task in mind review existing literature to confirm the reliability and validity of the task in that particular age group. At this stage when a task is selected a researcher should consider methodological detail, such as the appropriate administration and scoring methods that have been found to be reliable. Finally, a researcher should consider whether this task alone can answer the research question, or whether additional tasks should be employed, for example to account for task impurity. If a researcher chooses to use behavioural indicators of EFs a well-established measure discussed in the current chapter is the BRIEF (Gioia et al., 2000), although of course a researcher may prefer another measure based for example on availability.
96 4. Assessment of Executive Functions in Children What do you want to measure?
Cognitive performance
Behavioural indicators
Which components of executive function do you want to assess?
How old and able are my intended participants?
How old and how able are your intended participants?
Do I require information about behaviour at home (parent ratings) or at school (teacher ratings)?
Which tasks have been shown to be reliable and valid in this particular participant group?
Is a completed rating scale sufficient for the area of investigation, or should I aim to triangulate this data with that from other informants, or from cognitive tasks?
Which scoring method does this reliability and validity information apply to?
Are there any potential biases when using a rating scale in this proposed way, which I will need to consider when drawing conclusions from my findings?
Could I employ a single task, or instead should I add multiple tasks or control tasks in order to account for task impurity?
Figure 4.1 Flowchart of considerations to guide the choice of an executive function assessment.
A researcher should then consider the age and ability of their intended participants (for lower ability individuals we would recommend not employing the self-report versions of the BRIEF). For children aged 2–5 researchers should use the BRIEF-P, and then the standard BRIEF should be used for those aged 5–18. A research must then consider who will complete the behavioural rating scale. If the research question relates to the home environment this should be a parent, and if it relates to the school environment then this should be a teacher. They should then consider whether using the BRIEF alone is sufficient to answer their research question, or if information is also needed from other sources. Finally, they should consider any potential biases with using the rating scale when interpreting their research findings.
References 97
References Abu-Akel, A., Testa, R.R., Jones, H.P., Ross, N., Skafidas, E., Tonge, B., & Pantelis, C. (2018). Attentional set-shifting and social abilities in children with schizotypal and comorbid autism spectrum disorders. Australian & New Zealand Journal of Psychiatry, 52(1), 68–77. Alloway, T.P., Gathercole, S.E., Kirkwood, H., & Elliott, J. (2008). Evaluating the validity of the automated working memory assessment. Educational Psychology, 28(7), 725–34. Amani, M., Asady Gandomani, R., & Nesayan, A. (2018). The reliability and validity of behavior rating inventory of executive functions tool teacher’s form among iranian primary school students. Iranian Rehabilitation Journal, 16(1), 25–34. Anderson, P., Anderson, V., & Lajoie, G. (1996). The tower of London test: validation and standardization for pediatric populatons. The Clinical Neuropsychologist, 10(1), 54–65. Arán-Filippetti, V. (2013). Structure and invariance of executive functioning tasks across socioeconomic status: evidence from Spanish-speaking children. The Spanish Journal of Psychology, 16, E101. Baddeley, A.D. (2000). The episodic buffer: a new component of working memory? Trends in Cognitive Sciences, 4(11), 417–23. Baddeley, A.D., & Hitch, G. (1974). Working memory. In G.H. Bower (Ed.). The Psychology of Learning and Motivation: Advances in Research and Theory (Vol. 8, pp. 47–89). New York, NY: Academic Press. Bardikoff, N., & Sabbagh, M. (2017). The differentiation of executive functioning across development: insights from developmental cognitive neuroscience. In N. Budwig, E. Turiel, & P. Zelazo (Eds.). New Perspectives on Human Development (pp. 27–46). Cambridge, UK: Cambridge University Press. Barkley, R.A. (2011). Barkley Deficits in Executive Functioning Scale (BDEFS) Manual. New York, NY: Guilford. Bowden, S.C., Fowler, K.S., Bell, R.C., Whelan, G., Clifford, C.C., Ritter, A.J., & Long, C.M. (1998). The reliability and internal validity of the Wisconsin Card Sorting Test. Neuropsychological Rehabilitation, 8(3), 243–54. Broadway, J.M., & Engle, R.W. (2010). Validating running memory span: measurement of working memory capacity and links with fluid intelligence. Behavior Research Methods, 42(2), 563–70. Brooks, B.L., Sherman, E.M., & Strauss, E. (2009). NEPSY-II: a developmental neuropsychological assessment. Child Neuropsychology, 16(1), 80–101. Brydges, C.R., Fox, A.M., Reid, C.L., & Anderson, M. (2014). The differentiation of executive functions in middle and late childhood: a longitudinal latent-variable analysis. Intelligence, 47, 34–43. Brydges, C.R., Reid, C.L., Fox, A.M., & Anderson, M. (2012). A unitary executive function predicts intelligence in children. Intelligence, 40(5), 458–69. Bunting, M., Cowan, N., & Scott Saults, J. (2006). How does running memory span work?. Quarterly Journal of Experimental Psychology, 59(10), 1691–700. Cambridge Cognition (1996). CANTAB. Cambridge, UK: Cambridge Cognition Ltd. Carney, D.P., Brown, J.H., & Henry, L.A. (2013). Executive function in Williams and Down syndromes. Research in Developmental Disabilities, 34(1), 46–55. Carver, A.C., Livesey, D.J., & Charles, M. (2001). Further manipulation of the stop-signal task: developmental changes in the ability to inhibit responding with longer stop-signal delays. International Journal of Neuroscience, 111(1–2), 39–53. Chasiotis, A., Kiessling, F., Winter, V., & Hofer, J. (2006). Sensory motor inhibition as a prerequisite for theory-of-mind: a comparison of clinical and normal preschoolers differing in sensory motor abilities. International Journal of Behavioral Development, 30, 178–90.
98 4. Assessment of Executive Functions in Children Conway, A.R.A., Kane, M.J., Bunting, M.F., Hambrick, D.Z., Wilhelm, O., & Engle, R.W. (2005). Working memory span tasks: a methodological review and user’s guide. Psychonomic Bulletin and Review, 12, 769–86. Craig, F., Margari, F., Legrottaglie, A.R., Palumbi, R., De Giambattista, C., & Margari, L. (2016). A review of executive function deficits in autism spectrum disorder and attention-deficit/ hyperactivity disorder. Neuropsychiatric Disease and Treatment, 12, 1191. Dekker, M.C., Ziermans, T.B., Spruijt, A.M., & Swaab, H. (2017). Cognitive, parent and teacher rating measures of executive functioning: shared and unique influences on school achievement. Frontiers in Psychology, 8, 48. Delis, D.C. (2012). Delis-Rating of Executive Function (D-REF). Bloomington, MN: Pearson. Duncan, J., Emslie, H., Williams, P., Johnson, R., & Freer, C. (1996). Intelligence and the frontal lobe: the organization of goal-directed behavior. Cognitive Psychology, 30(3), 257–303. Durston, S., Thomas, K.M., Yang, Y., Uluğ, A.M., Zimmerman, R.D., & Casey, B.J. (2002). A neural basis for the development of inhibitory control. Developmental Science, 5(4), F9–F16. Engel de Abreu, P.M., Abreu, N., Nikaedo, C.C., Puglisi, M.L., Tourinho, C.J., Miranda, M.C., . . . & Martin, R. (2014). Executive functioning and reading achievement in school: a study of Brazilian children assessed by their teachers as ‘poor readers’. Frontiers in Psychology, 5, 550. Eriksen, B.A., & Eriksen, C.W. (1974). Effects of noise letters upon the identification of a target letter in a nonsearch task. Perception & Psychophysics, 16(1), 143–9. Fernández, T.G., González-Pienda, J.A., Pérez, C.R., García, D.Á., & Pérez, L.Á. (2014). Psychometric characteristics of the BRIEF scale for the assessment of executive functions in Spanish clinical population. Psicothema, 26(1), 47–54. Fisk, J.E., & Sharp, C.A. (2004). Age-related impairment in executive functioning: updating, inhibition, shifting, and access. Journal of Clinical and Experimental Neuropsychology, 26(7), 874–90. Friedman, N.P., Miyake, A., Corley, R.P., Young, S.E., Defries, J.C., & Hewitt, J.K. (2006). Not all executive functions are related to intelligence. Psychological Science, 17, 172–9. Friedman, N.P., Miyake, A., Young, S.E., Defries, J.C., Corley, R.P., & Hewitt, J.K. (2008). Individual differences in executive functions are almost entirely genetic in origin. Journal of Experimental Psychology: General, 137, 201–25. Gathercole, S.E., Pickering, S.J., Knight, C., & Stegmann, Z. (2004). Working memory skills and educational attainment: evidence from national curriculum assessments at 7 and 14 years of age. Applied Cognitive Psychology, 18(1), 1–16. Gerstadt, C.L., Hong, Y.J., & Diamond, A. (1994). The relationship between cognition and action: performance of children 3½–7 years old on a Stroop-like day–night test. Cognition, 53, 129–53. Gioia, G.A., Isquith, P.K., Guy, S.C., & Kenworthy, L. (2000). Test review behavior rating inventory of executive function. Child Neuropsychology, 6(3), 235–8. Gioia, G.A., & Isquith, P.K. (2011). Behavior Rating Inventory for Executive Functions (pp. 372– 6). New York, NY: Springer. Golden, C.J., Freshwater, S.M., & Golden, Z. (2003). Stroop Color and Word Test, Children’s Version for Ages 5– 14: A Manual for Clinical and Experimental Uses. Wood Dale, IL: Stoelting Co. Gonthier, C., Aubry, A., & Bourdin, B. (2018). Measuring working memory capacity in children using adaptive tasks: example validation of an adaptive complex span. Behavior Research Methods, 50(3), 910–21. Grace, J., & Malloy, P.F. (2001). Frontal Systems Behavior Scale: FrSBe. Lutz, FL: Psychological Assessment Resources.
References 99 Grant, D.A., & Berg, E. (1948). A behavioral analysis of degree of reinforcement and ease of shifting to new responses in a Weigl-type card-sorting problem. Journal of Experimental Psychology, 38(4), 404. Greve, K.W., Stickle, T.R., Love, J.M., Bianchini, K.J., & Stanford, M.S. (2005). Latent structure of the Wisconsin Card Sorting Test: a confirmatory factor analytic study. Archives of Clinical Neuropsychology, 20, 355–64. Heaton, R.K., Chelune, G.J., Talley, J.L., Kay, G.G., & Curtiss, G. (1993). Wisconsin Card Sorting Test Manual. Odessa, FL: Psychological Assessment Resources. Howard, S.J., Okely, A.D., & Ellis, Y.G. (2015). Evaluation of a differentiation model of preschoolers’ executive functions. Frontiers in Psychology, 6, 285. Hughes, C., & Graham, A. (2002). Measuring executive functions in childhood: problems and solutions. Child and Adolescent Mental Health, 7, 131–42. Huizinga, M., Baeyens, D., & Burack, J.A. (2018). Executive function and education. Frontiers in Psychology, 9, 1357. Huizinga, M., Dolan, C.V., & Van Der Molen, M.W. (2006). Age-related change in executive function: developmental trends and a latent variable analysis. Neuropsychologia, 44(11), 2017–36. Humes, G.E., Welsh, M.C., Retzlaff, P., & Cookson, N. (1997). Towers of Hanoi and London: reliability and validity of two executive function tasks. Assessment, 4(3), 249–57. Jaeggi, S.M., Buschkuehl, M., Perrig, W.J., & Meier, B. (2010). The concurrent validity of the N- back task as a working memory measure. Memory, 18(4), 394–412. John, A.M.S., Kibbe, M., & Tarullo, A.R. (2019). A systematic assessment of socioeconomic status and executive functioning in early childhood. Journal of Experimental Child Psychology, 178, 352–68. Kane, M.J., Conway, A.R., Miura, T.K., & Colflesh, G.J. (2007). Working memory, attention control, and the N-back task: a question of construct validity. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33(3), 615. Karr, J.E., Hofer, S.M., Iverson, G.L., & García-Barrera, M.A. (2018). Examining the latent structure of the Delis–Kaplan executive function system. Archives of Clinical Neuropsychology, 34(3), 381–94. Klenberg, L., Korkman, M., & Lahti-Nuuttila, P. (2001). Differential development of attention and executive functions in 3- to 12- year- old Finnish children. Developmental Neuropsychology, 20(1), 407–28. Last, B.S., Lawson, G.M., Breiner, K., Steinberg, L., & Farah, M.J. (2018). Childhood socioeconomic status and executive function in childhood and beyond. PloS One, 13(8), e0202964. Lee, K., Bull, R., & Ho, R.M.H. (2013). Developmental changes in executive functioning. Child Development, 84(6), 1933–53. Lehto, J.E., Juujärvi, P., Kooistra, L., & Pulkkinen, L. (2003). Dimensions of executive functioning: evidence from children. British Journal of Developmental Psychology, 21(1), 59–80. Mahone, E.M., Martin, R., Kates, W.R., Hay, T., & Horská, A. (2009). Neuroimaging correlates of parent ratings of working memory in typically developing children. Journal of the International Neuropsychological Society, 15(1), 31–41. McAuley, T., Chen, S., Goos, L., Schachar, R., & Crosbie, J. (2010). Is the behavior rating inventory of executive function more strongly associated with measures of impairment or executive function? Journal of the International Neuropsychological Society, 16(3), 495–505. McDermott, J.M., Pérez-Edgar, K., & Fox, N.A. (2007). Variations of the flanker paradigm: assessing selective attention in young children. Behavior Research Methods, 39(1), 62–70. McKinlay, A. (2011). Trail Making Test. In S. Goldstein & J.A. Naglieri (Eds.). Encyclopedia of Child Behavior and Development. Boston, MA: Springer.
100 4. Assessment of Executive Functions in Children McLean, J.F., & Hitch, G.J. (1999). Working memory impairments in children with specific arithmetic learning difficulties. Journal of Experimental Child Psychology, 74(3), 240–60. Miller, M.R., Giesbrecht, G.F., Müller, U., McInerney, R.J., & Kerns, K.A. (2012). A latent variable approach to determining the structure of executive function in preschool children. Journal of Cognition and Development, 13(3), 395–423. Miyake, A., Emerson, M.J., & Friedman, N.P. (2000). Assessment of executive functions in clinical settings: problems and recommendations. Seminars in Speech and Language, 21, 169–83. Miyake, A., Friedman, N.P., Emerson, M.J., Witzki, A.H., Howerter, A., & Wager, T.D. (2000). The unity and diversity of executive functions and their contributions to complex ‘frontal lobe’ tasks: a latent variable analysis. Cognitive Psychology, 41(1), 49–100. Morris, R.D. (1996). Relationships and distinctions among the concepts of attention, memory, and executive function: a developmental perspective. In G.R. Lyon & N.A. Krasnegor (Eds.). Attention, Memory, and Executive Function (pp. 11–16). Baltimore, MD: Paul H Brookes Publishing Co. Moura, O., Simões, M.R., & Pereira, M. (2015). Executive functioning in children with developmental dyslexia. The Clinical Neuropsychologist, 28(sup1), 20–41. Naglieri, J.A., & Goldstein, S. (2013). Comprehensive Executive Function Inventory: Manual. North Tonawanda, NY: Multi-Health Systems. Nyongesa, M., Ssewanyana, D., Mutua, A.N., Chongwo, E., Scerif, G., Newton, C.R.C., & Abubakar, A. (2019). Assessing executive function in adolescence: a scoping review of existing measures and their psychometric properties. Frontiers in Psychology, 10, 311. Oberauer, K. (2005). Binding and inhibition in working memory: individual and age differences in short-term recognition. Journal of Experimental Psychology: General, 134(3), 368. Owen, A.M., McMillan, K.M., Laird, A.R., & Bullmore, E. (2005). N‐back working memory paradigm: a meta‐analysis of normative functional neuroimaging studies. Human Brain Mapping, 25(1), 46–59. Ozonoff, S. (1997). Components of executive function in autism and other disorders. In J. Russell (Ed.). Autism as an Executive Disorder (pp. 179–211). Oxford, UK: Oxford University Press. Packwood, S., Hodgetts, H.M., & Tremblay, S. (2011). A multiperspective approach to the conceptualization of executive functions. Journal of Clinical and Experimental Neuropsychology, 33(4), 456–70. Pauls, L.J., & Archibald, L.M. (2016). Executive functions in children with specific language impairment: a meta-analysis. Journal of Speech, Language, and Hearing Research, 59(5), 1074–86. Pelegrina, S., Lechuga, M.T., García-Madruga, J.A., Elosúa, M.R., Macizo, P., Carreiras, M., . . . & Bajo, M.T. (2015). Normative data on the n-back task for children and young adolescents. Frontiers in Psychology, 6, 1544. Qian, Y., & Wang, Y.F. (2007). Reliability and validity of behavior rating scale of executive function parent form for school age children in China. Beijing Da Xue Xue Bao, 39(3), 277–83. Redick, T.S., & Lindsey, D.R. (2013). Complex span and n-back measures of working memory: a meta-analysis. Psychonomic Bulletin & Review, 20(6), 1102–13. Reitan, R.M., & Wolfson, D. (2004). The Trail Making Test as an initial screening procedure for neuropsychological impairment in older children. Archives of Clinical Neuropsychology, 19(2), 281–8. Rhoades, B.L., Greenberg, M.T., & Domitrovich, C.E. (2009). The contribution of inhibitory control to preschoolers’ social–emotional competence. Journal of Applied Developmental Psychology, 30, 310–20. Rose, S.A., Feldman, J.F., & Jankowski, J.J. (2011). Modeling a cascade of effects: the role of speed and executive functioning in preterm/full‐term differences in academic achievement. Developmental Science, 14(5), 1161–75.
References 101 Shah, P., & Miyake, A. (1999). Models of working memory. In A. Miyake & P. Shah (Eds.). Models of Working Memory: Mechanisms of Active Maintenance and Executive Control (pp. 1–27). Cambridge, UK: Cambridge University Press. Shallice, T. (1982). Specific impairments of planning. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 298(1089), 199–209. Shallice, T., & Burgess, P.W. (1991). Deficits in strategy application following frontal lobe damage in man. Brain, 114, 727–41. Shilling, V.M., Cheywynd, A., & Rabbitt, P.M.A. (2002). Individual inconsistency across measures of inhibition: an investigation of the construct validity of inhibition in older adults. Neuropsychologia, 40, 605–19. Sikora, D.M., Haley, P., Edwards, J., & Butler, R.W. (2002). Tower of London test performance in children with poor arithmetic skills. Developmental Neuropsychology, 21(3), 243–54. Silver, C.H. (2014). Sources of data about children’s executive functioning: review and commentary. Child Neuropsychology, 20(1), 1–13. Simon, H.A. (1975). The functional equivalence of problem-solving skills. Cognitive Psychology, 7(2), 268–88. Simon, J.R., & Berbaum, K. (1990). Effect of conflicting cues on information processing: the ‘Stroop effect’ vs the ‘Simon effect’. Acta Psychologica, 73(2), 159–70. Soreni, N., Crosbie, J., Ickowicz, A., & Schachar, R. (2009). Stop signal and conners’ continuous performance tasks: test—retest reliability of two inhibition measures in ADHD children. Journal of Attention Disorders, 13(2), 137–43. Strauss, G.P., Allen, D.N., Jorgensen, M.L., & Cramer, S.L. (2005). Test-retest reliability of standard and emotional stroop tasks: an investigation of color-word and picture-word versions. Assessment, 12(3), 330–7. Strauss, E., Sherman, E., & Spreen, O. (2006). A Compendium of Neuropsychological Tests: Administration, Norms, and Commentary. New York, NY: Oxford University Press/ American Chemical Society. Stroop, J.R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18(6), 643. Syväoja, H.J., Tammelin, T.H., Ahonen, T., Räsänen, P., Tolvanen, A., Kankaanpää, A., & Kantomaa, M.T. (2015). Internal consistency and stability of the CANTAB neuropsychological test battery in children. Psychological Assessment, 27(2), 698–709. Tan, A., Delgaty, L., Steward, K., & Bunner, M. (2018). Performance-based measures and behavioral ratings of executive function in diagnosing attention-deficit/hyperactivity disorder in children. ADHD Attention Deficit and Hyperactivity Disorders, 10(4), 309–16. Thorell, L.B., & Catale, C. (2014). The assessment of executive functioning using the Childhood Executive Functioning Inventory (CHEXI). In S. Goldstein & J.A. Naglieri (Eds.). Handbook of Executive Functioning (pp. 359–66). New York, NY: Springer. Thorell, L.B., & Nyberg, L. (2008). The Childhood Executive Functioning Inventory (CHEXI): a new rating instrument for parents and teachers. Developmental Neuropsychology, 33(4), 536–52. Toplak, M.E., West, R.F., & Stanovich, K.E. (2013). Practitioner review: do performance‐based measures and ratings of executive function assess the same construct? Journal of Child Psychology and Psychiatry, 54(2), 131–43. Towse, J.N., Lewis, C., & Knowles, M. (2007). When knowledge is not enough: the phenomenon of goal neglect in preschool children. Journal of Experimental Child Psychology, 96(4), 320–32. Vaughan, L., & Giovanello, K. (2010). Executive function in daily life: age-related influences of executive processes on instrumental activities of daily living. Psychology and Aging, 25, 343–55.
102 4. Assessment of Executive Functions in Children Van Boxtel, G.J., Van der Molen, M.W., Jennings, J.R., & Brunia, C.H. (2001). A psychophysiological analysis of inhibitory motor control in the stop-signal paradigm. Biological Psychology, 58(3), 229–62. Van der Ven, S.H., Kroesbergen, E.H., Boom, J., & Leseman, P.P. (2012). The development of executive functions and early mathematics: a dynamic relationship. British Journal of Educational Psychology, 82(1), 100–19. Van der Ven, S.H., Kroesbergen, E.H., Boom, J., & Leseman, P.P. (2013). The structure of executive functions in children: a closer examination of inhibition, shifting, and updating. British Journal of Developmental Psychology, 31(1), 70–87. Van der Sluis, S., de Jong, P.F., & van der Leij, A. (2007). Executive functioning in children, and its relations with reasoning, reading, and arithmetic. Intelligence, 35(5), 427–49. Van Leeuwen, M., van den Berg, S.M., Hoekstra, R.A., & Boomsma, D.I. (2007). Endophenotypes for intelligence in children and adolescents. Intelligence, 35(4), 369–80. Viterbori, P., Usai, M.C., Traverso, L., & De Franchis, V. (2015). How preschool executive functioning predicts several aspects of math achievement in grades 1 and 3: a longitudinal study. Journal of Experimental Child Psychology, 140, 38–55. Wagner, S., Helmreich, I., Dahmen, N., Lieb, K., & Tadić, A. (2011). Reliability of three alternate forms of the trail making tests A and B. Archives of Clinical Neuropsychology, 26(4), 314–21. Wang, L., Kakigi, R., & Hoshiyama, M. (2001). Neural activities during Wisconsin Card Sorting Test—MEG observation. Cognitive Brain Research, 12(1), 19–31. Waters, G.S., & Caplan, D. (2003). The reliability and stability of verbal working memory measures. Behavior Research Methods, Instruments, & Computers, 35(4), 550–64. Welsh, M.C., Pennington, B.F., & Groisser, D.B. (1991). A normative‐developmental study of executive function: a window on prefrontal function in children. Developmental Neuropsychology, 7(2), 131–49. Welsh, M.C., Revilla, V., Strongin, D., & Kepler, M. (2000). Towers of London and Hanoi: is the nonshared variance due to differences in task administration? Perceptual and Motor Skills, 90, 562–72. Wiebe, S.A., Sheffield, T.D., & Espy, K.A. (2012). Separating the fish from the sharks: a longitudinal study of preschool response inhibition. Child Development, 83(4), 1245–61. Wöstmann, N.M., Aichert, D.S., Costa, A., Rubia, K., Möller, H.J., & Ettinger, U. (2013). Reliability and plasticity of response inhibition and interference control. Brain and Cognition, 81(1), 82–94. Zelazo, P.D. (2006). The Dimensional Change Card Sort (DCCS): a method of assessing executive function in children. Nature Protocols-Electronic Edition, 1(1), 297. Zelazo, P.D., & Jacques, S. (1997). Children’s rule use: representation, reflection, and cognitive control. Annals of Child Development, 12, 119–76.
5 Capturing the Challenges in Assessing Writing Development and Writing Dimensions Julie E. Dockrell and Vincent Connelly
Introduction Researchers and practitioners have been challenged by the complexity of the writing process and its development for many years. Writing develops over time through interactions between the child’s cognitive resources, the instructional context, and the demands of the writing task. The challenges writing poses for the learner (and the evaluator) varies by age and phase of writing proficiency. Effective writing skills allow students to express their ideas, succeed in education, and enter the workplace. Writing also enhances learning, in terms of both student’s reading comprehension (Hebert, Gillespie, & Graham, 2013) and subject content knowledge (Bangert-Drowns, Hurley, & Wilkinson, 2004). To understand writing development researchers must be able to conceptualize the components of the writing process and assess these in a reliable and valid fashion from the resultant writing products. By corollary practitioners need to assess writing in a developmentally appropriate manner; to devise and evaluate educational programmes, to identify struggling writers, those at risk of poorer performance and to provide targeted support. Understanding what to assess and how to assess writing to elucidate the development of writing proficiency is fundamental to both applied and basic science. This chapter will consider how researchers conceptualize the components of the writing process, assess the resulting products, and capture writing processes. These issues also inform practitioners in their assessment of writing. To address these objectives, we will draw on a wide range of literature concerned with writing assessment. The assessment of writing is dependent on sensitive measures of writing competencies; that is measures which reveal the students’ ability to produce a written text and capture the characteristics of proficient writing. Accurately measuring writing performance is important for both summative (see for example Dockrell, Lindsay, Connelly, & Mackie, 2007) and formative assessment (see for example Graham, Harris, & Hebert, 2011). More widely, assessment of writing has been identified as Julie E. Dockrell and Vincent Connelly, Capturing the Challenges in Assessing Writing In: Executive Functions and Writing. Edited by: Teresa Limpo and Thierry Olive, Oxford University Press. © Oxford University Press 2021. DOI: 10.1093/oso/9780198863564.003.0005
104 5. Capturing the Challenges in Assessing Writing problematic, with suggestions that it is the single greatest barrier to writing instruction and research (Cole, Haley, & Muenz, 1997). In this chapter we focus on the assessment of writing as writers move from the initial stages of learning to write (novices) to more proficient writers. We consider the challenges in what to assess and how writing can be assessed. We argue that there are key decisions to be made at all stages of the evaluation of the writing process and that these decisions should be informed by both the purpose of the assessment and current theories and models of writing development. Models are designed to capture both the skills that children need to produce a written text, the more distal factors which underpin these skills and the wider task environment (Graham, 2018; see Chapter 3 of this volume). These models guide researchers in what to assess but should not constrain the assessment process, which also needs to be sensitive to development, context, and purpose (Bazerman, 2018). As we shall argue the scores or profiles that are produced to reflect a student’s writing proficiency vary depending on what is assessed and how the assessment is operationalized (Schoonen, 2012). Assessors also vary in their interpretation of the scoring criteria; indeed, the more assessments diverge from objectively identifiable entities such as the numbers of words in a text the harder it is to reach high levels of agreement. As such, in addition to considering what should be assessed it is necessary to consider how accurately assessment can be operationalized.
What Is Writing? Producing a piece of written text requires the writer to generate ideas and represent them in a symbolic form. It serves both as means of personal meaning making and supports learning (Bangert-Drowns, Hurley, & Wilkinson, 2004). While the purpose of writing is to transmit information (of different kinds), the process of writing is underpinned by cognitive and linguistic processes (Hayes, 2012a). Theoretical models of the factors that underpin writing have been the focus of much discussion and development over the last 40 years (see MacArthur, Graham, & Fitzgerald, 2006). Yet capturing writing competence remains a challenge. Writing is effectively a problem-solving space where the writer must make decisions about communicating their ideas based on the task and the audience. This entails not only being proficient in the necessary skills for the production of a written text but also being able to use these skills flexibly. For the novice writer, struggling writer, or those students with learning difficulties, these decisions are often constrained by their transcription skills, that is handwriting/typing and spelling (Puranik & AlOtaiba, 2012; Sumner, Connelly, & Barnett, 2016) and linguistic competence (Dockrell, Lindsay, & Connelly, 2009; Koutsoftas, 2016). For most writers, the importance of these lower-level transcription skills reduces over time and by the time students leave elementary school the higher level writing skills including sensitivity to genre and purpose, use of rhetorical devices and textual
What to Assess? 105
organization become more important in gauging writing proficiency (Berninger et al., 1995). Writing as a problem-solving space can be conceptualized in a range of different ways; this inevitably influences the focus of assessments. In this chapter, we focus on the analysis of the writing product and the writing process and the necessary prerequisite skills to achieve proficiency in writing. Our framework is grounded within psychological approaches, which serve both to understand writing proficiency, but also aim to isolate key competencies for identifying children who struggle with writing and improve children’s writing performance. From this perspective, cognitive skills and the ways in which they are exploited impact on the writing products that are created, but these products are scaffolded by wider communicative factors (Myhill & Jones, 2007). One of the major challenges of writing assessment is that we have no a priori agreed definition of what constitutes writing proficiency at different points in development.
What to Assess? Various approaches to evaluation of written products have been used by researchers and teachers in the assessment of writing. These include both holistic scoring and analytic scoring of writing products, both result in a quantitative score (e.g. see Abbott & Berninger, 1993; Lee, Gentile, & Kantor, 2010; Mackie & Dockrell, 2004; McMaster & Espin, 2007; Puranik & AlOtaiba, 2012; Scott & Windsor, 2000; Wagner et al., 2011). These various approaches to evaluation differ in purpose and in their underlying assumptions about the dimensionality of written composition, but all rely on participants producing a written product at word, sentence, or text level. However, more fine-grained analyses have focused on single aspects of writing including handwriting fluency (Berninger et al., 1997), spelling (Caravolas, 2004) or lexical diversity (Roessingh, Elgie, & Kover, 2015), either as single tasks such as writing the alphabet (Puranik & AlOtaiba, 2012) or as part of a composition (Broc et al., 2013). Assessments of writing proficiency where a written product is not produced are rare but include a range of tasks where respondents must identify a correct response or an error in a sentence or text. These assessments can be judged both in terms of the accuracy of the response and latency to respond (Largy, Dedeyan, & Hupet, 2004). Currently this approach is used for the national testing of 11-year-olds in England (Standards and Testing Agency, 2019) where accuracy of response is assessed. The English Spelling, Punctuation and Grammar test (SPAG) explicitly examines students’ knowledge of punctuation and grammar using selected responses or the identification of a feature from a given set of options. Although there are several different response formats within the assessment the use of such an approach as a proxy for assessing children’s writing has been heavily criticised. Indeed, it has been argued that children can identify errors in isolated tests but far fewer can transfer that learning to their writing, so it does not provide any information about accuracy in writing. There
106 5. Capturing the Challenges in Assessing Writing is currently no evidence to indicate whether this form of assessment of punctuation and grammar is associated with student’s writing proficiency and indeed as an assessment approach moves away from the notion of writing as a communicative act. By contrast, recent research has indicated that knowledge of discourse markers and textual features, which do reflect communicative purpose, are a significant predictor of writing proficiency at a similar age (Wijekumar et al., 2019).
Evaluating the Writing Product Researchers assessing writing typically collect a sample or, less frequently, samples of students’ writing. These writing products can be evaluated in a myriad of ways including a focus on organization, logical development of ideas or mechanics (spelling and punctuation). In this section we consider different approaches to evaluating the written product.
Holistic Scoring Measures
Holistic scoring measures have been used in research, psychometric assessments, and in practice. The global quality of the text is rated on a single ordinal scale and while specific dimensions of the text might be considered, the ultimate result is not the sum of the parts (as in analytic scoring, see ‘Analytic Scoring’) but a single total score for the final composition. Scores are often based on a previously created rubric, which is transformed into a rating scale. Clarity of the descriptors is essential. Typically, descriptors are subjective and developed by experts, resulting in less consistent use, even across well trained assessors (Banerjee, Yan, Chapman, & Elliott, 2015). Rubrics, themselves, may not improve the reliability or validity of assessment if the assessors are not well trained on how to design and employ them effectively (Rexaei & Lovorn, 2010, Westby & Clauser, 1999). This approach was used in the level descriptors for writing in the English national curriculum (Qualifications and Curriculum Authority, 2010), where there was a government consultation with academics and professionals to create the descriptors. In this case, the evaluation rubric was informed by practice and expert opinion, not by models of writing. Alternatively, scales can be developed using writing performance data, where greater discriminability may be evident (Banerjee, Yan, Chapman, & Elliott, 2015). Holistic measures have the advantage of providing a single score with relatively little time involvement. Holistic assessments are often used to evaluate pupils’ written work in classes and in national assessments or as an option in some standardized writing assessments (see for example Wechsler Objective Language Dimensions (WOLD): Rust, 1996). However, which language constructs are examined in these writing assessments (Mo & Troia, 2017) and the extent to which these scores generalize to wider concepts of writing proficiency is less clear. In addition, they are limited in their ability to reliably differentiate among writing levels, monitor change over time and capture differential performance on the key components of writing (Espin
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et al., 2000). In novice writers and those with learning disabilities the, typically, short amount of text written by these children can also reduce the validity of a holistic approach to evaluation (McMaster & Espin, 2007). A major limitation for both theory and practice is the use of a single score, which does not allow the differentiation between different components of the written product. In this form of text evaluation, information about idea generation, for example, is not distinguishable from grammatical complexity. This approach therefore potentially limits both theory development and the identification of target skills to develop writing proficiency, particularly when the writer does not produce much text.
Analytic Scoring
Analytic scoring, by contrast, provides a more detailed and comprehensive scoring system and aims to focus on the qualities of proficient writing. Analytic scoring requires prior decisions to be made about the key components of writing proficiency to be assessed. Once these components have been identified it is possible to provide explicit guidelines for scoring the texts. For example, the WOLD (Rust, 1996) analytic scoring of written expression includes six elements: organization, unity and coherence, vocabulary, grammar and usage, capitalization, and punctuation. The measure has served to be a useful tool is examining the writing products and writing trajectories of pupils with developmental difficulties (Connelly, Campbell, MacLean, & Barnes, 2006; Dockrell, Lindsay, Connelly, & Mackie, 2007; Prunty, Barnett, Wilmut, & Plumb, 2016; Sumner, Connelly, & Barnett, 2016; Williams, Larkin, & Blaggan, 2013) and has been modified with small samples to link to local national curricular (see Dunsmuir et al., 2015 where the assessment was linked to the English national curriculum).
Dimensions of the Written Product
More recent work has attempted to identify evidence-based dimensions of children’s written text products. Sometimes these dimensions are considered together to create a single score. Other times the hypothesized dimensions are scored separately, and profiles of writing are produced in terms of analytic or quantitative scoring schemes (Huot, 1990). The number of dimensions that are thought to underpin written text production are a matter of debate. One approach has been to distinguish the macrostructure and the microstructure of the texts produced. This distinction can be captured in studies of composition that have identified two dimensions in written texts: quality and productivity (Berninger & Swanson, 1994; Graham et al., 1997; Olinghouse & Graham, 2009). Macrostructure typically focuses on the use of a bespoke holistic scoring scale (see for example Koutsoftas & Gray, 2012) or rating scales (Nelson & Van Meter, 2007) which capture quality. These scales vary by writing genre, text, or purpose. Productivity by contrast is typically a text level microstructure measure of length in either total number of words or sentences produced. Productivity is associated with quality both in younger elementary school writers and in university students
108 5. Capturing the Challenges in Assessing Writing (Connelly, Campbell, MacLean, & Barnes, 2006; Connelly, Dockrell, & Barnett, 2005; Connelly, Gee, & Walsh, 2007). Research has also considered microstructure in more detail including, for example, both the lexical diversity within the text and its syntactic complexity. Lexical diversity is reported to be a unique predictor of narrative text quality (Olinghouse & Leaird, 2009; Olinghouse & Wilson, 2013) and has been demonstrated to grow in the early years of elementary school (Wood, Schatschneider, & Hart, 2020). An alternative but complementary framework conceptualizes writing at the word, sentence, and text level (Fayol, Alarmagot, & Berninger, 2012; Hayes & Berninger, 2014). This has a number of important advantages; it ensures that the researcher and practitioner link writing to the levels of language necessary to produce a proficient text and as such can capture bottlenecks in production at word (Kim, Al Otaiba, & Wanzek, 2015; Sumner, Connelly, & Barnett, 2016), sentence (Dockrell, Connelly, & Arfè, 2019) and text (Dockrell, Ricketts, Charman, & Lindsay, 2014; Koutsoftas, 2016) levels. While this approach could be viewed as portraying writing proficiency as hierarchically organized these components are likely, at least, semi-independent. More recently, these dimensions have been refined to include factors related to text complexity and organization at word, sentence, and text level (Wagner et al., 2011). Wagner et al. (2011) identified a five-factor model of writing proficiency for students between first and fourth grade including macro-organization ideas (text level), productivity (word level including number and diversity of words used) complexity (sentence level including both syntactic density and mean length of T units) and transcription (spelling, punctuation, and handwriting fluency). Although these dimensions vary by age and population tested, they all capture dimensions of productivity (e.g. numbers of words generated), complexity (e.g. quality and accuracy) and grammatical correctness (Puranik, Lombardino, & Altmann, 2008 in children in grades 3, 4, 5, and 6; Wagner et al., 2011). These different measures appear to be dissociable products with different predictors even in early elementary school (Kim, Al Otaiba, Wanzek, & Gatlin, 2015 with second and third; Sénéchal, Hill, & Malette, 2018 with fourth grade children). These fine-grained analyses are not without their challenges for reliable assessment. For example, Type Token Ratios (TTRs) have been commonly used but are highly sensitive to number of words produced. A TTR is the total number of unique words a writer produces (types) which are divided by the total number of words (tokens) produced in the text. For example, if a writer produces 10 different words (tokens) but eight different words (types) the TTR of that written text product is.8, but if a writer produces 100 words (tokens) and 75 different words (types) the TTR is.75. The closer the TTR ratio is to 1, the greater is the purported lexical richness of the text, but as the example here shows TTR may not capture this accurately. This is a significant confound for students who produce shorter texts, as is the case with novice writers, or when the sample size varies markedly. Another approach using a mathematical formula to produce a single parameter D is argued to be a much more accurate reflection of the lexical diversity of texts (Duran, Malvern, Richards, & Chipere, 2004).
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The D-value is computed through a series of computations of the TTR on samples of different text lengths after which a random sampling TTR curve is computed. However, a minimum sample size of 50 words is still needed to calculate D and the type of writing task does impact on lexical diversity (Yu, 2010). The writing products of younger elementary school children often are simply not long enough to compute lexical diversity. Figure 5.1 demonstrates that in a sample of 1172 elementary school children completing a 10-minute writing task to a prompt it was not until the age of nine years that the mean number of words produced was above 50 words. Even at the of age nine years the Standard Deviations remained large and at age 11, 20% of the children still produced 50 words or less (Dockrell, Marshall, & Wyse, 2016). The reduced numbers of words produced by young students and those with writing difficulties will also have a bearing on other attempts at more fine-grained analyses of the students’ texts. Students need to produce sufficient numbers of words to judge these features and for the novice writer and struggling writers there may simply be insufficient tokens to make this kind of analysis. As an example, in a recent study examining verb argument structures in the writing of elementary school pupils with a mean age of 10 years there was limited variety in the use of verb structures used. Indeed, verb use was generally limited to more general all-purpose verbs (see Stuart, Connelly & Dockrell, 2019). Moreover, the number of verbs and the number of different verb types produced by the children in the written text did not account for significant variance in writing quality. From this study it was difficult to ascertain if the low numbers of verbs produced in writing was due to cognitive constraints imposed by the writing process or simply restricted by the amount of text children could produce in a time limited writing assessment. The extent to which the dimensions of productivity, complexity, and quality can be translated across different levels of writing proficiency is less clear. These frameworks capture writing in elementary and middle school (and struggling writers) but are not appropriate for preschool children (Coker & Ritchey, 2010; Keller-Margulis
Mean number of words produced
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Figure 5.1 Mean number of words produced in 10 minutes by age group (N = 1172).
110 5. Capturing the Challenges in Assessing Writing et al., 2019) and likely fail to capture the characteristics of more advanced writing (Diercks-Gransee, Weissenburger, Johnson, & Christensen, 2009). As students progress in their writing proficiency and move into high school, greater emphasis has been placed on the development of genre specific rhetorical structures and more sophisticated linguistic properties including greater lexical sophistication, often captured by lower word frequency. It is not that spelling and grammatical errors are not of importance, but it is the more advanced writing aspects that reflect writing productivity at this point. Indeed, for older writers in high school it is difficult to identify a single set of predefined linguistic features which capture high quality texts (Allen, Snow, & McNamara, 2016), rather different textual and author characteristics can result in higher quality texts for the more competent writer.
Evaluating the Writing Process With any assessment evaluating the completed written product there is a risk that the analysis of that written product is incomplete because it fails to capture the writing process. The writing process underpins written communicative efficiency from which the product is derived. Central to the production of written text is translation (Hayes & Berninger, 2014). Translation converts ideas into linguistically and grammatically appropriate word strings (Hayes, 2012b). These word strings then need to be transcribed into the written product through the application of the fluent and accurate transcription processes involved in handwriting/keyboarding and spelling (Hayes & Berninger, 2014; Kim et al., 2011). For novice writers, especially in English, transcription skills are thought to limit the efficiency of translation well into the elementary school years (see Kent & Wanzek, 2016 for a meta-analysis) and so, for example, a lack of fluency in transcription skills directly constrains productivity and quality of handwritten texts in English (Graham et al., 1997) and typed texts in third grade Norwegian students (Torkildsen, Morken, Helland, & Helland, 2016). As writers’ transcription skills become more fluent sentence generation and lexical retrieval support text production and processing constraints are imposed by working memory (McCutchen, Covill, Hoyne, & Mildes, 1994). Learning to translate ideas into text is the core of writing in the first years of schooling. Part of the challenge in examining the translation process in children has been the lack of objective measures that can assess the translation process. Indeed, focusing on the writing process shifts the emphasis for assessment from the student’s completed written products to the act of creating a piece of text. From this perspective, writing is understood as consisting of the interplay of three recursive cognitive subprocesses (planning, translation, and revision) which interact with the writer’s long-term memory and the writing task or task environment (Hayes & Berninger, 2014). Skilled writing has been conceived as a sequence of recursive processes where planning initially informs translation and ideas are translated into written text when reviewing and revising can occur (Hayes & Flower, 1980).
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Planning
Two types of planning can be distinguished: planning which occurs before writing (prewriting planning) or online planning, which occurs during the production of the written text (Berninger & Swanson, 1994). Planning which occurs during the translation process, that is online planning, arguably, is not operational until adolescence where young people are more competent and fluent writers and recursive planning and revising can occur (Olive & Kellogg, 2002; Olive, 2014). By contrast prewriting planning is promoted in elementary school classrooms (Alley & Peterson, 2017), although the nature and extent of instruction varies across country contexts (Parr & Jesson, 2016; Torrance et al., 2012), age (Dockrell, Marshall, & Wyse, 2016), and classrooms (De la Paz & Graham, 2002). Producing written plans as part of prewriting planning provides the writer with both the opportunity to generate ideas and structure them to develop the written product (Torrance, Thomas, & Robinson, 1999). The central function of planning is argued to be generating content for the text to be written. Writers prepare their text by extracting information from the task environment and by searching for content in their long-term memory. It is therefore not surprising that topic knowledge influences the final written product (Olinghouse, Graham, & Gillespie, 2015; Schoonen, 2012), a factor rarely controlled for in writing assessments. This generated material is (re) organized in a writing plan that guides text production. These prewriting planning activities reduce demands on the writers working memory, thereby providing the writer with greater scope to devote time to translation and transcription, resulting in increased writing fluency and higher ratings of text quality (Kellogg, 2008). Prewriting planning in college students has been shown to consistently improve holistic writing quality (Kellogg 1988, 1990), including both the fluency and the syntactic complexity of the texts produced (Limpo & Alves, 2018), but studies of younger children have been less positive. Early research on children’s prewriting planning indicated that elementary school children only plan prior to writing for a very short time (De la Paz, 1999), and when they do plan this is typically a draft of the text to be produced (Bereiter & Scardamalia, 1987). Children also produce text organizers, especially in the later years of elementary school (Llaurado & Dockrell, 2019). However, typically elementary school pupils do not use the plans they produce (Limpo & Alves, 2013; Llaurado & Dockrell, 2019). Nor do these preparatory activities predict text quality (Llaurado & Dockrell, 2019; Olinghouse & Graham, 2009; Whitaker, Berninger, Johnston, & Swanson, 1994). However, by sixth grade planning to write, defined as generating ideas and producing a first draft had a direct effect on translation (Koutsoftas & Gray, 2013). Thus, while younger elementary school students are able to produce plans, only older students seem to use them to guide text production (Limpo, Alves, & Fidalgo, 2014). Children may fail to use plans for a number of reasons. One possibility is that younger children may not differentiate the process of planning to write from the process of translating (Bereiter & Scardamalia, 1987). Koutsoftas and Gray (2013) found that while producing an outline had a direct effect on the production of a first draft, there were no
112 5. Capturing the Challenges in Assessing Writing subsequent effects on the production of a second revised text. Thus, the type of plan that children produce prior to the production of the written text may be critical in terms of its impact on the writing product. Despite the key role assigned to planning for writing in models of writing development (Bereiter & Scardamalia, 1987; Berninger et al., 1996; Macarthur & Graham, 1987) there have been few attempts to assess the types of activities that children might engage in prior to writing their texts. Planning before writing can involve, at least, two distinct elements: idea generation and organization. Again, the development of these written artefacts may vary with development but also between children and across tasks (Kieft, Rijlaarsdam, Galbraith, & van den Bergh, 2007). These initial written plans can also be examined in a number of ways (see Hayes & Nash, 1996 for a review on planning measures). Outlines and graphic organizers have been considered as the most advanced form of preplanning (Limpo & Alves, 2013; Whitaker, Berninger, Johnston, & Swanson, 1994). The effect of content or idea generation in prewriting planning on text production has been less explored (but see Koutsoftas & Gray, 2013). Examining the plans writers produce and the ways in which they are used informs our understanding of the writing process by capturing when and how planning underpins writing proficiency (Baaijen, Galbraith, & de Glopper, 2014). Capturing these processes informs both theory and pedagogy.
The Translation Processes
It has long been noted that skilled writers compose in bursts of writing activity broken by relatively long pauses (Kaufer, Hayes, & Flower, 1986). These segments of activity have been termed writing bursts. Two different types of burst have been identified: production bursts and revision bursts. Revision bursts are periods of writing that end with the intention of revising some previously written text and represent about 10 to 15% of bursts in skilled adult writers (Galbraith & Baaijen, 2019; Hayes, 2011), but are very rare in elementary school aged writers (Berninger & Swanson, 1994; Torkildsen, Morken, Helland, & Helland, 2016; Torrance, Fidalgo, & García, 2007). Production bursts, by contrast, are commonly observed in both elementary school students and adults and are thought to derive from the translation process as writers convert their ideas into the written form (Alves & Limpo, 2015; Hayes, 2011, 2012a, 2012b). Production bursts have been characterized by pauses of 2 seconds or more, punctuated by sustained writing activity that reaches on average about nine words long in skilled writers and ends when the translation ‘production process appears to run out of steam’ (Hayes, 2009 p.66). The long pauses following production bursts are associated with uncertainty about what to write next in adult think aloud protocols (Kaufer, Hayes, & Flower, 1986); but there is no equivalent data to our knowledge for younger writers. The length of production bursts increases with writer’s experience and language proficiency (Hayes, 2011), so these writing bursts are hypothesized to reflect the impact of translation processes during writing. Thus, the length of written language bursts are, arguably, symptomatic of the efficiency of translation processes in
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the writer (Hayes, 2009, 2011, 2012a, 2012b) and likely affected by the length of text produced (see ‘Dimensions of the Written Product’). The majority of the evidence on writing bursts has come from studies of adult writers and have been interpreted within models of adult writing (Hayes & Flower, 1980). There have been fewer studies examining writing bursts in novice writers, with a number of notable exceptions. Alves and colleagues carried out a series of studies examining the development of writing bursts in Portuguese children (Limpo & Alves, 2013; Alves, Branco, Castro, & Olive, 2012; Alves et al., 2016). These studies have confirmed that in elementary school children, unlike adults, transcription skills play a significant role in the development of burst length, and so may constrain the translation process. Nine-year-old children with good handwriting fluency produced longer bursts than those with slow or average handwriting fluency, and longer bursts were associated with higher quality text (Alves, Branco, Castro, & Olive, 2012). A larger study by the same research group examined the writing of 310 children between 7 and 14 years of age and found a year on year growth in burst length and a reduction in pause length (Alves & Limpo, 2015). Similar results where burst length predicted text quality but were constrained by transcription skills were also reported in eleven-year-old children with language impairments (Connelly, Dockrell, Walter, & Critten, 2012). Thus, as with studies examining children’s written products, these initial studies identify a critical role for transcription skills in the development of burst length, independent of writing genre (see also Olive, Alves, & Castro, 2009 in adults). A challenge for researchers is how to determine a burst length. There has been considerable debate around the criterion for the pause length from which the beginning and end of bursts should be measured (e.g. see Baaijen, Galbraith, & de Glopper, 2012; Chenu, Pellegrino, Jisa, & Fayol, 2014). The original study (Kaufer, Hayes, & Flower, 1986) noted from their think aloud protocol data that it was pauses of 2 seconds or more that punctuated the most writing bursts. However, most recent commentators on this issue consider that 2 seconds is probably a long pause for adults, and they have used different ways of deciding on pause thresholds (Chenu, Pellegrino, Jisa, & Fayol, 2014; Galbraith & Baaijen, 2019). Thresholds for novice writers and struggling writers remain to be empirically established.
Revision
Studies that focus on revision activities during development are still relatively infrequent despite the central role of revising in theories of writing. Revision can happen at any point during text production, serves to identify ambiguities or errors in the text, and aims to improve the communicative quality of the text. Revision after writing can be distinguished from revision during writing or online revision. Students, however, tend to conceptualize revision as a post-textual activity (Myhill & Jones, 2007). Revision requires the writer both to reread the text and to evaluate the product, highlighting the recursive nature of the process and the importance of the writer’s reading skills. The complexity of the revising process places heavy demands on the
114 5. Capturing the Challenges in Assessing Writing writer’s working memory (see ‘Working Memory’; McCutchen, 1996). Scardamalia and Bereiter (1986) identified three components of the revision process: compare, diagnose, and operate. Each component draws on a range of skills. A variety of coding schemes have been developed to capture revision, with the most complex capturing both surface changes and changes of meaning (Fitzgerald, 1987). Novice or beginner writers perform few spontaneous revisions after writing (Limpo, Alves, & Fidalgo, 2014; Torkildsen, Morken, Helland, & Helland, 2016) and when revisions are made they typically reflect surface aspects of the text such as spelling, punctuation, and grammar (Fitzgerald, 1987; Largy, Dedeyan, & Hupet, 2004), as opposed to the meaning of the text and its coherence. By contrast the revisions of more skilled writers are reported to improve the quality of the written product (Fitzgerald, 1987; Breuer, 2019). The limited revision of text products by novice writers raises questions about why they do not revise. Novice writers may consider revising to be limited to error correction or minor editorial changes (Graham, Schwartz, & Macarthur, 1993), regarding it more as a proofreading activity. Alternatively, revision places substantial demands on working memory. For the novice or beginner writer their attentional resources are focused on transcription and text generation limiting resources for more extensive revision. It is therefore of import to disentangle working memory limitations with a lack of understanding of the need for text revision. Evidence to support the role of working memory comes from a study by Chanquoy (2001). She provided writers with a one-day delay between writing and revision and demonstrated that this delay improved the depth of children’s revisions; providing further evidence that for the assessment of writing proficiency we need to move away from assessments at single points in time. A unique study by Limpo and colleagues (Limpo, Alves, & Fidalgo, 2014) examined the development of both planning and revising, demonstrating the importance of considering both factors. Using data from students from grades 4 to 9 they demonstrated that for the older students both planning and revising contributed to writing quality. However, for revision it was only substantive revision focusing on text meaning that impacted on the quality of the product (see also Sénéchal, Hill, & Malette, 2018).
Metacognitive Control
Metacognitive control plays an important role in the production of a written text (McCutchen, 1988). From this perspective writing proficiency may best be captured by the writer’s ability to adapt to the demands of different text types (Allen, Snow, & McNamara, 2016). Choosing when and where to use specific words, rhetorical devices, and how to structure the ensuing text becomes central to becoming a proficient writer. Assessing flexibility involves both collecting multiple samples of writing from the same individual as well as identifying key properties of the texts that are produced. Writing products may fluctuate in relation to the specific writing prompt or assignment (Allen, Snow, & McNamara, 2016; see also ‘How to Assess?’).
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Communication
While the focus on metacognitive control and flexibility emphasizes the role of executive functions (see ‘Executive Functions’) it also captures the view that communication is the ‘driving force for writing’ (Hayes, 2009). As such, when writing, writers need to consider their readers (Bereiter & Scardamalia, 1987). When this perspective on the writing process is taken, writing can be conceptualized as a social practice, one where it is necessary to consider the contexts that drive engagement and participation, and the norms and expectations internalized as a result of participation in different communities (see for example Bazerman, 2004; Rietdijk et al., 2018). Until recently, the sociocultural approach to writing was seen as diametrically opposed to cognitive perspectives of writing development (Graham, 2018). Yet, recent frameworks have attempted to readdress this issue (Deane, 2018; Graham, 2018). The fundamental aspect is an acknowledgement that there are specific cultural, social, and political influences on writing. Writing is a social activity that is situated within specific contexts, sometimes described as writing communities (Hull & Schultz, 2001). At its most basic level the communicative act of writing is to provide information, what might be considered knowledge telling. Such an activity may place fewer demands on the writer’s skills. By contrast, in other sociocultural environments, for example professional and academic settings, where text quality and argumentation are prioritized, writers may produce multiple-draft plans, reviews, and use a range of other strategies. As Olinghouse and Santangelo (2010) demonstrated in their review, students will differ in their social experiences that impact on understandings of writing; and these differences will impact on their writing proficiency and their instructional needs as learners. As an example, consider student argumentation ability. This varies across school-age populations in high school (seventh, eighth, and ninth grade: Deane, Song, van Rijn, et al., 2018). Only students who are consistently accurate on tasks of argument evaluation produced well-developed summaries, essays, or critiques; while writers who show little metacognitive understanding of the structure of arguments produced minimally elaborated responses (Deane et al., 2018). From this perspective it is important to consider the context of instruction, learner characteristics as well as the foundational skills that the writer needs to acquire.
How to Assess? Which type of writing task, how many samples, and which prompts? These are all decisions that need to be made in the assessment of writing and writing development. By far the most common approach to assessment requires the student to produce some text but after that there is marked inconsistency. As Bazerman notes (Bazerman, 2018) the tasks that have been traditionally used to explore children’s writing are narrow. They typically reflect one particular writing task –a short essay to a prescribed prompt—and rarely the range of writing activities that children and young people engage in. Typical formats include producing a written response in relation
116 5. Capturing the Challenges in Assessing Writing to a written or picture prompt, producing a source based writing response or generating a response after hearing an oral story or report. Each of these writing tasks places different demands on the writer and their pre-existing knowledge and skills. Source based writing or read to write tasks are commonly used in the USA in instruction (Graham & Harris, 2017) and in some national assessments, while writing to a prompt is common in research studies. Writing in kindergarten often includes writing letters and writing sentences, moving to word and sentence copying. Sentence copying, story, picture-word, and photo prompts are promising writing measures in early elementary school as is word dictation (Keller-Margulis et al., 2019; McMaster, Du, & Petursdottir, 2009). While limitations in instructional contexts, such as filling in blanks or producing formulaic answers, can lead to a rigid and an undeveloped approach to writing (Deane, 2018). To develop a flexible writing system, the child must be allowed to experience writing with different genres, for different audiences and through different media. Here we consider three decisions that influence our ability to assess students’ flexible writing skills.
How Many and How Long? How many texts are needed to capture writing competency? While there is no agreed consensus on the actual number there is now strong evidence that more than one task is more informative about a writer’s skills. The impact of different writing tasks on children’s written products are evident in pupils in elementary school (Kim et al., 2017) and high school (Allen, Snow, & McNamara, 2016). Task effects are also evident using different measures of assessing the written product (Kim et al., 2017). In general, there are only weak to moderate correlations in performance across writing tasks (Graham et al., 2011). Recent research has begun to use generalisability theory to explore writing competence (Graham, Hebert, Sandbank, & Harris, 2016; Kim et al., 2017). This approach allows the researcher to examine variance accounted for by different facets of the assessment process including task, assessor, and the interaction between the two. Often summative assessments are made from single texts and this type of assessment is typical in research studies and in standardized assessments of writing. However, multiple tasks are likely needed to provide a valid indicator of writing proficiency. Recently research from Wilson and colleagues (Wilson, Chen, Sandbank, & Hebert, 2019) has demonstrated that for the scoring of writing quality to be reliable (.9) at least two prompts across genres were required for typical writers, but for struggling writers four, or even five, prompts across genres were needed. There has been much less discussion about how long a student needs to write for before an indication of writing competence can be captured. Curriculum-based measures of writing (CBM-W) are an example where students write for short amounts of time typically about 5 minutes and can be scored for productivity (total words written), grammatical accuracy (correct word sequences minus incorrect word sequences), and writing quality (Dockrell, Connelly, Walter, & Critten, 2015). These
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aspects of the CBM-W capture different aspects of writing and are associated with different underlying constructs (Kim et al., 2015). CBM-W measures are most sensitive in middle elementary school and with struggling writers. More recently CBM-W assessments have been developed to assess writing in later elementary school, where students produce an informational text using evidence from a passage (Truckenmiller et al., 2019). Simpler prompts with shorter administration times are more reliable for younger children, whereas for capturing writing proficiency in older children more complex prompts with longer writing times are more accurate (Espin et al., 2008). Nonetheless across age groups similar metrics capture writing proficiency, specifically measures of grammatical accuracy (Truckenmiller et al., 2019)
Text Genre Assessments of single writing products also fail to capture the demands of different types of writing tasks (Scott & Windsor, 2000). Ideally to capture writing competence comparisons should be made across different writing genres (Berman, 2008; Olinghouse & Wilson, 2013). Narrative and expository writing are common school tasks and comparisons between the two genres has been the focus of a number of studies. Narrative writing involves telling a story, while expository texts involve conveying facts or describing procedures. Expository texts take longer to master (Berman & Verhoeven, 2002) and differences are evident in the student’s text (Beers & Nagy, 2011; Koutsoftas & Gray, 2012). Expository writing is argued to be more cognitively demanding for novice writers in elementary school (Dockrell, Marshall, & Wyse, 2015), demands the use of more complex vocabulary (Berman & Nir-Sagiv, 2007), as well as more sophisticated sentence structure (Reilly, Zamora, & McGivern, 2005). Thus, expository texts place a greater cognitive load on the writer including greater time required in planning and demands more sophisticated knowledge transforming (Beauvais, Olive, & Passerault, 2011). There is also indicative evidence that, at least for writers who are not writing in their first language, that the two writing genres influence assessor reliability (Jeong, 2017). Novice writers produce shorter summaries which are more error prone when they produce expository texts, but more complex text structures may be used (Scott & Windsor, 2000). CBM-W writing measures differentiate successfully between narrative and expository texts (Dockrell, Marshall, & Wyse, 2015). This confirms previous work using other forms of writing assessments examining these genre differences (Apel & Apel, 2011; Koutsoftas & Gray, 2012; Scott & Windsor, 2000), and provides a further source of information about the potential validity of the CBM-W measure. In elementary school pupils (English pupils equivalent to grades 3, 4, and 5) Dockrell, Marshall, and Wyse (2015) found that less text was produced, and students were less accurate in response to an expository probe. In contrast, more punctuation marks were used in response to the expository probe than in the narrative probe, perhaps indicating the tendency for a more list like nature associated with narrative texts at this point in
118 5. Capturing the Challenges in Assessing Writing development. There were large effect sizes for these differences, as would be expected when children are new to writing in a genre. This raises an important caveat in using these assessments to differentiate between pupils and across time in that comparisons need to be made using similar types of probes.
Automated Scoring of Texts Anyone who has scored writing products knows that it is both a challenging and a time-consuming endeavour. Some research with novice writers has used detailed scoring systems designed for oral language, e.g. Systematic Analysis of Language Transcripts (SALT: Nelson & Van Meter, 2007), but this typically requires the addition and revision of many of the codes to ensure that the writing product is accurately reflected (see Mackie, Dockrell, & Lindsay, 2013 as an example). However, several automatic scoring systems now exist specifically for written texts. These systems rely on automatically extracting predefined information from the text produced using natural language processing and require the researcher to decide, a priori, the focus of the textual coding. Often these systems have been developed to reflect the scores that human assessors would allocate on the basis of structure and content (Dikli, 2006). In addition, these can be directly related to models of writing, for instance levels of language used and, as such, identify new detection algorithms that should be incorporated within the automatic evaluation of the students’ written texts (see ‘Dimensions of the Written Product’; Wilson, Roscoe, & Ahmed 2017). Automatic scoring assesses the written product and can use a combination of approaches to create both holistic and analytic scores. A wide range of tools are now available capturing text quality (Wilson Chen, Sandbank, & Hebert 2019), text cohesion (Crossley, Kyle, & McNamara, 2016), thematic content (Crossley, Allen, Kyle, & McNamara, 2014) lexical sophistication and automated scoring of grammar and mechanical errors (Crossley, Bradfield, & Bustamante, 2019; Wilson, Roscoe, & Ahmed, 2017). Within each tool different metrics are used to evaluate the text. For example, in the analysis of lexical sophistication, the identification of hundreds of lexical features is now possible (Crossley & Kyle, 2018). These methods can be used to provide profiles of proficient writers by analysing the linguistic features of the text at word, sentence, and discourse level and for screening at risk writers (see Wilson, 2018 using Project essay grade, PEG). Automated writing evaluation systems have also been developed to support students’ writing (Allen, Likens, & MacNamara, 2019), but multiple metrics will be required for this to be effective (Wilson & Roscoe, 2019). These technical developments show promise for testing theories in large samples of writers, using multiple texts to capture a comprehensive range of textual features. They also provide for the possibility of monitoring interventions in a more rigorous and reliable way. For some researchers this will be an ideal solution to assessing the complex construct of writing. However, without a strong theory underpinning the choice of text to be produced, the
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textual features analysed, and the metrics used, their contribution to understanding writing development will be limited.
Proximal and Distal Factors Models of writing often highlight the importance of individual competencies including oral language (Arfè, Dockrell, & De Bernardi, 2016), transcription skill automaticity (Berninger, 1999), working memory capacity (Berninger et al., 2010), executive functions (Berninger & Winn, 2006) and prior world knowledge (Olinghouse, Graham, & Gillespie, 2015) and assessments of writing often include measures of these skills as potential moderation or mediation variables. Distinguishing between the proximal and distal factors that support writing development provides a framework to understand both writing development and writing difficulties. From this perspective, transcription skills that directly impact on the production of written text can be conceptualized as proximal factors. As we have demonstrated the proximal factors of handwriting and spelling directly influence children’s writing in the initial stages of learning to write. Spelling continues to be a challenge to written text production in English elementary school children. By contrast, competencies which work more indirectly and mediate the production of written text, can be considered distal factors. As children master the proximal skills of handwriting and spelling in elementary school and become more proficient writers then distal factors are hypothesized to play a greater role in text generation in later elementary school, even though the variance they account for in the children’s written products is often small (Kent & Wanzek, 2016; Kim & Schatschneider, 2017). Thus, assessments of writing proficiency should consider addressing a wider range of relevant skills. Distal factors support writing processes indirectly, typically working through more proximal factors such as transcription or idea generation in supporting children’s writing (Zoccolotti, De Luca, Marinelli, & Spinelli, 2014). The direct and indirect effects model of writing development (DIEW) was developed by Kim and colleagues (Kim, 2016; Kim & Schatschneider, 2017) from data collected with grade 1 pupils. The focus was on the three component skills identified in the not-so-simple view of writing (Berninger & Winn, 2006): transcription skills, executive functions, and idea generation, but in addition the model specified subcomponent skills for the process of text generation. The DIEW model incorporates three levels of mental representation of written texts: the situation model, or what the text is about, the textbase, or the local integration of the ideas (propositions) expressed in the text, and the surface structure level, corresponding to the specific words and phrases which linguistically express the propositions/ideas in the text (Kintsch, 1992, 2005). For establishing global coherence and elaborating texts at the level of the situation model, higher-order cognitive skills, such as inference making and the ability to infer the mental states of others need to be considered. For elaborating and integrating the single propositions (specific mental concepts/representations) of the text, vocabulary, grammatical knowledge,
120 5. Capturing the Challenges in Assessing Writing attentional control, and working memory are used. The same foundational language and cognitive skills are necessary to elaborate the surface structure, that is single words and sentences in the text (Kim, 2016; Kim & Schatschneider, 2017). For the first time the model explicitly captures more distal factors which underpin the production of written text and leads to an alternative way of conceptualizing the assessment of writing proficiency.
Oral Language To generate text, children need to access cognitive representations and this involves the fluent use of different levels of language to translate these into written products (Abbott, Berninger, & Fayol, 2010; Chenoweth & Hayes, 2001). We have already identified the importance of examining the written product at word, sentence, and text level (see ‘Dimensions of the Written Product’). Here we document the importance of oral language skills at these levels. Oral language skills account for independent variance in children’s written text products, although the precise linguistic driver is a matter of debate (Mackie, Dockrell, & Lindsay, 2013). Vocabulary, grammatical knowledge and discourse level oral language, are all associated with writing development (Abbott & Berninger, 1993; Babayigit & Stainthorp, 2010; Kim, et al., 2014; Olinghouse & Leaird, 2009; Sénéchal, Hill, & Malette, 2018), although their effects depend on the age of the children assessed and the way in which the writing product is assessed (Connelly, Dockrell, Walter, & Critten, 2012; Dockrell, Lindsay, & Connelly, 2009). In addition, children’s ability to generate fluently oral sentences, as well as written sentences, underpins the production of written text (Arfè, Dockrell, & De Bernardi, et al., 2016; Arfè & Pizzocaro, 2016; Dockrell, Connelly, & Arfè, 2019; McCutchen, Covill, Hoyne, & Mildes, 1994). Recently, Sénéchal and colleagues (2018) have demonstrated that for students in grade 4 oral storytelling explained unique variance in the corresponding aspect of written narratives. Current studies typically report only weak to moderate correlations between measures of language and the quality of student’s written products, with weaker correlations with writing productivity (Apel & Apel, 2011; Dockrell, Connelly, & Arfè, 2019; Kent & Wanzek, 2016; Olinghouse & Graham, 2009; Olinghouse & Leaird, 2009). Nonetheless, the role of oral language in written text production should not be minimized as recent evidence indicates that oral sentence fluency in grade 1 supports written text generation over time (grade 6) and across languages (French and English) (Savage et al., 2017).
Reading Reading also influences written text production. Word reading is associated with transcription skills (Abbott & Berninger, 1993) and word recognition skills consistently predict spelling abilities at all elementary grade levels (Abbott & Berninger, 1993) as
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described in ‘Revision’. Accurate revision also is premised on accurate reading skills. Children with better reading and spelling scores have been reported to make more online revisions and these are associated with narrative quality and length (Torkildsen, Morken, Helland, & Helland, 2016). By corollary, poor reading comprehension impacts on text level writing, where children with poorer reading comprehension, but age appropriate spelling, produce texts which are more limited and less sophisticated in comparison to age matched peers (Cragg & Nation, 2006). Although, again, only moderate associations between writing and measures of reading are reported (Kent & Wanzek, 2016).
Working Memory As we have seen the coordination of the components of text production place heavy demands on working memory (WM) resources (McCutchen, 1996; Olive, Favart, Beauvais, & Beauvais, 2009). If a child needs to search for the letters to create a word, then ideas, plans and revising can be lost as they overload the capacity of WM (Graham et al., 1997). There is increasing evidence that WM, particularly the central executive, are important in the writing processes of high-school students (Vanderberg & Swanson, 2007). WM is also an independent longitudinal predictor of later writing disabilities in elementary school (Costa, Green, Sideris, & Hooper, 2018). Moreover, WM has been explicitly included in the Not-So-Simple model of writing development (Berninger & Winn, 2006) and, as such, is an important distal factor in supporting writing production.
Executive Functions Executive functions (EFs) are another constellation of cognitive abilities which have been identified as distal factors in writing studies and are explicitly included in models of writing (see Chapter 3 of this volume). EFs are complex cognitive abilities that enable the identification of goals, mental planning, behaviour organization, and planning actions to achieve these goals (Diamond, 2013). Given the complex cognitive demands involved in producing written text it is not surprising that EFs underpin aspects of text production (Berninger & Chanquoy, 2012; Berninger & Winn, 2006). Indeed, some of the activities subsumed within EFs, e.g. planning and revising and processes such as WM were discussed in ‘The Translation Processes’ and ‘Revisions’, respectively, and WM in ‘Working Memory’. However, there is less clarity about which EF measures should be assessed, at which point in development and in relation to which writing product. EFs directly related to writing such as ability to plan are more directly linked to writing as are EF skills involving language (see Chapter 6 of this volume). For example, in a study of 88 children between grades 4 and 9, multiple regressions based on multiple levels of language showed that measures of attention and
122 5. Capturing the Challenges in Assessing Writing executive function involving language processing, rather than ratings of attention and executive function not specifically related to language, accounted for more variance, and identified more unique predictors in the composite outcomes including writing (Berninger, Abbott, Cook, & Nagy, 2017). So, when deciding on which aspects of EF to include it is important to consider how parsimonious these are with the writing process and the child’s writing skills. As another example consider, Cordeiro, Limpo, Olive, and Castro (2020) who examined the impact of inhibitory control, WM, cognitive flexibility, and planning (but see ‘Planning’, earlier) on text quality in grade 2 pupils and found WM and planning to have a significant effect. Whereas Drijbooms, Groen, and Verhoeven (2015) showed that inhibitory control was important in fourth grade. So, despite the evidence showing that EFs are associated with writing it is important to specify which EF, for which aspect of writing (Altemeier, Jones, Abbott, & Berninger, 2006) at which point in development (see Drijbooms, Groen, & Verhoeven, 2017).
An Illustration To explore some of the issues in profiling children’s writing skills we assessed the writing skills of 91 students with a mean age of nine years four months. We aimed to explore both the writing product defined in terms of quality, productivity, and accuracy, and the writing process defined as writing pauses and writing bursts in relation to proximal and distal factors which underpin writing. Using stepwise linear regression, we examined whether WM, transcription (spelling and handwriting), oral language (word and sentence level) and process measures predicted productivity, accuracy, and quality of writing using linear regression. We first controlled for participant age and then entered the proximal and distal measures of writing ability followed by the process measures in a second step. The models accounted for a significant proportion of variance for all measures, the most variance was accounted for when text accuracy (76%) and text generation (75%) were the dependent variables, and the least for text quality (46%). Writing burst length was strongly associated with transcription skills and moderately associated with producing oral language utterances but not oral vocabulary. The study identified the relationships between process writing measures and measures of the written product in terms of quality, productivity and grammatical accuracy and confirms previous work on writing bursts in children that report strong and consistent relationships between writing burst length and transcription measures of spelling and handwriting in both children (Alves, Branco, Castro, & Olive, 2012; Limpo & Alves, 2013; Alves et al., 2016) and adults ( Hayes, 2011). A novel finding was that writing burst length predicted independent variance over and above the proximal and distal measures of writing assessed in the children relating to both text productivity and accuracy. There was little additional variance accounted for in text quality. This is a new finding and offers support to the hypothesis that burst length represents a measure of the efficiency of the translator during
Conclusions 123
writing and confirms Hayes (2011, 2012a, 2012b) arguments about writing bursts. During writing the efficiency of translation allows writers to apply the appropriate grammar to the language strings required to be presented in a fluent and accurate manner. Those with shorter bursts are less productive and their grammatical choices are less accurate for the intended meaning. This mirrors results found in adults whose translation processes were thought to be less efficient (Chenoweth & Hayes, 2001). It would be important in the future to compare different task demands (see ‘How to Assess?’), include measures of executive function, and monitor the impact on burst length as a consequence.
Conclusions The complexity of the writing system has implications for both what we assess and how we assess it. This inevitably influences our understanding of developmental progress in writing and what is construed as writing proficiency. The evaluation of students writing products is the most common form of assessment in the research literature and in practice; yet there is little doubt that evaluating proficiency in written text production challenges the very basis of our assessment of text quality (Bazerman, 2019). As our analysis has demonstrated it is important to consider the context of instruction, learner characteristics as well as the foundational skills that the writer needs to acquire. Writing models speak to the importance of developing competency in a range of dimensions and attempts to provide analytic profiles aligns with the multidimensional nature of writing; but attempts to identify ‘key features’ of quality texts have been fraught with difficulties including subjective assessments (Meadows & Billington, 2005) and reliance on the assessments of single products or single genres may simply provide insufficient data to judge competency and to track development. Nonetheless these analytic frameworks for analysing text products have been useful at identifying struggling writers at word, sentence, and text levels. As we have argued key features of writing that assessments need to incorporate to capture writing proficiency are fluency at word, sentence, and text level, efficiency of the translation process and flexibility across genres and purpose. Doing so is fundamental to developing a theory of the development of writing proficiency and to support effective pedagogy but as we have argued requires an understanding of the developmental phases of the writing process. Transcription skills are key to the initial stages of learning to write where children produce shorter texts of limited complexity. As the writer progresses through elementary school both sentence generation and lexical sophistication are demonstrably important dimensions of the writing product and by the end of elementary school clear genre differences are evident in children’s written products. As the student enters high school more diversity in the written product is evident. The ability to produce texts in a flexible and fluent fashion continues to underpin proficient writing; this flexibility
124 5. Capturing the Challenges in Assessing Writing is best demonstrated through studies which include evaluations of multiple texts. Throughout development both the student’s topic knowledge and social experience impact on their written products. Teachers need to be able to profile pupils developing writing skills so appropriate action can be taken (Fuchs & Fuchs, 2009). Our view of assessment highlights the importance of using multiple tasks and likely different assessment methods; decisions based on single tests may not be reliable and may not capture some of the critical dimensions of becoming a proficient writer. Assessments that are short in time span provide promise for quick and efficient testing, such as CBM-W, but may suffer from being too short to provide specific analyses in detail. As we have demonstrated these measures need to be designed to reflect writing skills. Measures that can be counted provide advantages, including efficiency and high inter rater reliability (Gansle et al., 2002, 2004) and reduced subjectivity (Meadows & Billington, 2005). However, they may fail to capture the details of a writer’s proficiency because they do not capture the writer’s flexibility in written communication. All of these approaches require specialized training to reliably identify the target dimensions, and the construct validity of some analytical dimensions is often lower than holistic scoring schemes (Espin, De La Paz, Scierka, & Roelofs, 2005; Gansle et al., 2006). The increasingly automated scoring of texts could provide the opportunity to collect much data that will be very useful for our understanding of writing development. However, this does not relinquish the researcher from addressing the conceptual and theoretical understandings of what they are measuring and why. Researchers have traditionally concentrated on the analysis of the writing product. However, focusing on the writing process shifts the emphasis for assessment to the act of creating a piece of text. Thus, writing is understood as consisting of the interplay of three recursive cognitive subprocesses (planning, translation, and revision) which interact with the writer’s long-term memory and the writing task or task environment. The assessment of plans, writing bursts and revision techniques require as much attention as the final texts if we are to understand how writing develops and what is happening when text is being written. While there are a large number of challenges with assessment of the writing process there is much to be explored that may transform our understanding of writing. Linked to this is the role of distal factors in the development of writing, such as oral language, reading, WM, and other executive function tasks and the ways in which these skills impact on writing at different developmental phases. These more complex approaches lead to an alternative way of conceptualizing the assessment of writing proficiency (Kim, 2016; Kim & Schatschneider, 2017). The writing researcher can benefit here from the many different assessment types already available from related research fields. A major question that we have not addressed in this review of writing assessment is the question of the language in which the written text is produced. Few studies have assessed writing across orthographies beyond the single word level. Languages differ in a number of ways, but orthographic transparency and morphological complexity
References 125
are two which impact on the writers’ ability to flexibly use the resources at their disposal. These differences will also impact on the reliability and validity of different approaches to assessment of the writing product. Productivity measured by word count may reflect different core skills across languages. For example the sentence which presents the same simple idea of passing something to someone has different word counts, the typical measure of productivity, across languages: in English ‘ I gave it to him’ N = 5, in Italian ‘Gliel’ho dato’ N = 3 and French ‘Je lui ai donné’ N = 4. It would not be legitimate conclude from such data that the English writer is more proficient. Rather languages mark syntax and use vocabulary in different ways and this is reflected in the written product. Similarly, in transparent orthographies it is less likely that spelling creates a bottle neck to writing quality and other factors become salient earlier in development. For example, Llaurado and Dockrell (2019) have shown how in elementary school children reading skills predicted writing quality in Spanish (a transparent orthography) whereas spelling and handwriting constrained text quality and productivity in English and Catalan. It should not be a matter of fitting data from other languages to models developed in English but rather capturing how assessments of writing in other languages inform models of writing (see also Barnett, Connelly, & Miller, 2020). The research example we provided illustrated many of the challenges of assessing writing in the field and the complexities of integrating many of the measurements taken. Assessment of writing is a complex process in itself. This is not surprising given the complexity of writing processes and the time students take to reach mastery in writing—if we can agree on how to assess when mastery is achieved. What is in agreement is that as a writing research community we should not shy away from continually critically examining our methods of writing assessment, their underlying rationale, their validity and their reliability, and continue to reflect as a community on the strengths and weaknesses of our writing assessments.
References Abbott, R.D., & Berninger, V.W. (1993). Structural equation modeling of relationships among developmental skills and writing skills in primary-grade and intermediate-grade writers. Journal of Educational Psychology, 85(3), 478–508. Abbott, R.D., Berninger, V.W., & Fayol, M. (2010). Longitudinal relationships of levels of language in writing and between writing and reading in grades 1 to 7. Journal of Educational Psychology, 102(2), 281–98. Allen, L.K., Likens, A.D., & McNamara, D.S. (2019). Writing flexibility in argumentative essays: A multidimensional analysis. Reading and Writing: An Interdisciplinary Journal, 32(6), 1607–34. doi:10.1007/s11145-018-9921 Allen, L.K., Snow, E.L., & McNamara, D.S. (2016). The narrative waltz: the role of flexibility in writing proficiency. Journal of Educational Psychology, 108(7), 911–24. Alley, K.M., & Peterson, B.J. (2017). Ideas as a springboard for writing in K-8 classrooms. Writing Instruction to Support Literacy Success, 7, 65–93.
126 5. Capturing the Challenges in Assessing Writing Altemeier, L., Jones, J., Abbott, R.D., & Berninger, V.W. (2006). Executive functions in becoming writing readers and reading writers: note taking and report writing in third and fifth graders. Developmental Neuropsychology, 29(1), 161–73. doi:10.1207/s15326942dn2901_8. PMID: 16390292 Alves, R.A., & Limpo, T. (2015). Progress in written language bursts, pauses, transcription, and written composition across schooling. Scientific Studies of Reading, 19(5), 374–91. Alves, R.A., Branco, M., Castro, S.L., & Olive, T. (2012). Effects of handwriting skill, handwriting and dictation modes, and gender of fourth graders on pauses, written language bursts, fluency, and quality. In V.W. Berninger (Ed.). Past, Present, and Future Contributions of Cognitive Writing Research to Cognitive Psychology (pp. 389–402). New York, NY: Psychology Press. Alves, R.A., Limpo, T., Fidalgo, R., Carvalhais, L., Pereira, L.Á., & Castro, S.L. (2016). The impact of promoting transcription on early text production: effects on bursts and pauses, levels of written language, and writing performance. Journal of Educational Psychology, 108(5), 665–79. Apel, K., & Apel, L. (2011). Identifying intraindividual differences in students’ written language abilities. Topics in Language Disorders, 31(1), 54–72. Arfè, B., & Pizzocaro, E. (2016). Sentence generation in children with and without problems of written expression. In J. Perera, M. Aparici, E. Rosado, & N. Salas (Eds.). Written and Spoken Development Across the Lifespan. New York, NY: Springer. Arfè, B., Dockrell, J.E., & De Bernardi, B. (2016). The effect of language specific factors on early written composition: the role of spelling, oral language and text generation skills in a shallow orthography. Reading and Writing, 29(3), 501–27. Baaijen, V.M., Galbraith, D., & de Glopper, K. (2012). Keystroke analysis: reflections on procedures and measures. Written Communication, 29, 246–77. Baaijen, V.M., Galbraith, D., & de Glopper, K. (2014). Effects of writing beliefs and planning on writing performance. Learning and Instruction, 33, 81–91. Babayigit, S., & Stainthorp, R. (2010). Component processes of early reading, spelling, and narrative writing skills in Turkish: a longitudinal study. Reading and Writing, 23(5), 539–68. Banerjee, J., Yan, X., Chapman, M., & Elliott, H. (2015). Keeping up with the times: revising and refreshing a rating scale. Assessing Writing, 26, 5–19. Bangert-Drowns, R.L., Hurley, M.M., & Wilkinson, B. (2004). The effects of school-based writing- to- learn interventions on academic achievement: a meta- analysis. Review of Educational Research, 74(1), 29–58. Barnett, A.L., Connelly, V., & Miller, B. (2020). The interaction of reading, spelling and handwriting difficulties with writing development. Journal of Learning Disabilities, 3(2), 92–5. Bazerman, C. (2004). Speech acts, genres, and activity systems: how texts organize activity and people. In C. Bazerman & P. Prior (Eds.). What Writing Does and How it Does it: An Introduction (pp. 209–39). Mahwah, NJ: Erlbaum. Bazerman, C. (2018). What does a model? And for whom? Educational Psychologist, 53(4), 301–18. Bazerman, C. (2019). A? Developmental? Path? To Text? Quality? Journal of Literacy Research, 51(3), 381–7. Beauvais, C., Olive, T., & Passerault, J. M. (2011). Why are some texts good and others not? Relationship between text quality and management of the writing processes. Journal of Educational Psychology, 103(2), 415–28. Beers, S.F., & Nagy, W.E. (2011). Writing development in four genres from grades three to seven: Syntactic complexity and genre differentiation. Reading and Writing: An Interdisciplinary Journal, 24(2), 183–202. doi:10.1007/s11145-010-9264-9. Bereiter, C., & Scardamalia, M. (1987). An attainable version of high literacy—approaches to teaching higher-order skills in reading and writing. Curriculum Inquiry, 17(1), 9–30. Berman, R. (2008). The psycholinguistics of developing text construction. Journal of Child Language, 35(4), 735–71. doi:10.1017/S0305000908008787
References 127 Berman, R.A., & Nir-Sagiv, B. (2007). Comparing narrative and expository text construction across adolescence: a developmental paradox. Discourse Processes, 43(2), 79–120. Berman, R., & Verhoeven, L. (2002). Cross-linguistic perspectives on the development of text- production abilities: Speech and writing. Written Language & Literacy, 5(1), 1–43. Berninger, V.W. (1999). Coordinating transcription and text generation in working memory during composing: automatic and constructive processes. Learning Disability Quarterly, 22(2), 99–112. Berninger, V., Abbott, R., Cook, C.R., & Nagy, W. (2017). Relationships of Attention and Executive Functions to Oral Language, Reading, and Writing Skills and Systems in Middle Childhood and Early Adolescence. Journal of Learning Disabilities, 50(4), 434–449. doi:10.1177/0022219415617167 Berninger, V.W., & Chanquoy, L. (2012). What writing is and how it changes across early and middle childhood development: A multidisciplinary perspective. In E.L. Grigorenko, E. Mambrino, & D.D. Preiss (Eds.), Writing: A Mosaic of New Perspectives (pp. 65–84). Psychology Press. Berninger, V.W., & Swanson, H.L. (1994). Modifying Hayes and Flowers’ model of skilled writing to explain developing writing. In E.C. Butterfield (Ed.). Advances in Cognition and Educational Practice. Children’s Writing: Toward a Process Theory of the Development of Skilled Writing (Vol. 2, pp. 1–30). Greenwich, CT: JAI Press. Berninger, V.W., & Winn, W.D. (2006). Implications of advancements in brain research and technology for writing development, writing instruction, and educational evolution. In C. MacArthur, S. Graham, & J. Fitzgerald (Eds.). Handbook of Writing Research. New York, NY: Guildford. Berninger, V.W., Abbott, R.D., Swanson, H.L., Lovitt, D., Trivedi, P., Lin, S. J., . . . & Amtmann, D. (2010). Relationship of word-and sentence-level working memory to reading and writing in second, fourth, and sixth grade. Hearing Services in Schools, 41(2), 179–93. Berninger, V.W., Abbott, R.D., Whitaker, D., Sylvester, L., & Nolen, S.B. (1995). Integrating low-level and high-level skills in instructional protocols for writing disabilities. Learning Disability Quarterly, 18(4), 293–309. Berninger, V.W., Vaughan, K.B., Graham, S., Abbott, R.D., Abbott, S.P., Rogan, L.W., . . . & Reed, E. (1997). Treatment of handwriting problems in beginning writers: transfer from handwriting to composition. Journal of Educational Psychology, 89(4), 652–66. Berninger, V.W., Whitaker, D., Feng, Y., Swanson, H.L., & Abbott, R.D. (1996). Assessment of planning, translating, and revising in junior high writers. Journal of School Psychology, 34(1), 193–218. Breuer, E.O. (2019). Fluency in L1 and FL writing: an analysis of planning, essay writing and final revision. In E. Lindgren & K. Sullivan (Eds.). Observing Writing (pp. 190–211). Leiden, the Netherlands: BRILL. Broc, L., Bernicot, J., Olive, T., Favart, M., Reilly, J., Quemart, P., & Uze, J. (2013). Lexical spelling in children and adolescents with specific language impairment: variations with the writing situation. Research in Developmental Disabilities, 34(10), 3253–66. Caravolas, M. (2004). Spelling development in alphabetic writing systems: a cross-linguistic perspective. European Psychologist, 9(1), 3–14. Chanquoy, L. (2001). How to make it easier for children to revise their writing: a study of text revision from 3rd to 5th grades. British Journal of Educational Psychology, 71, 15–41. Chenoweth, N.A., & Hayes, J.R. (2001). Fluency in writing—generating text in L1 and L2. Written Communication, 18(1), 80–98. Chenu, F., Pellegrino, F., Jisa, H., & Fayol, M. (2014). Interword and intraword pause threshold in the writing of texts by children and adolescents: a methodological approach. Frontiers in Psychology, 5, 182. Coker, D.L., & Ritchey, K.D. (2010). Curriculum-based measurement of writing in kindergarten and first grade: an investigation of production aid qualitative scores. Exceptional Children, 76(2), 175–93.
128 5. Capturing the Challenges in Assessing Writing Cole, J., Haley, K., & Muenz, T. (1997). Written expression reviewed. Research in the Schools, 4(1), 17–34. Connelly, V., Dockrell, J. E., & Barnett, J. (2005). The slow handwriting of undergraduate students constrains overall performance in exam essays. Educational Psychology, 25(1), 99–107. Connelly, V., Campbell, S., MacLean, M., & Barnes, J. (2006). Contribution of lower order skills to the written composition of college students with and without dyslexia. Developmental Neuropsychology, 29(1), 175–96. Connelly, V., Dockrell, J.E., Walter, K., & Critten, S. (2012). Predicting the quality of composition and written language bursts from oral language, spelling, and handwriting skills in children with and without specific language impairment. Written Communication, 29(3), 278–302. Connelly, V., Gee, D., & Walsh, E. (2007). A comparison of keyboarded and handwritten compositions and the relationship with transcription speed. British Journal of Educational Psychology, 77(2), 479–92. Cordeiro, C., Limpo, T., Olive, T., & Castro, S. (2020). Do executive functions contribute to writing quality in beginning writers? A longitudinal study with second graders. Reading and Writing, 33, 813–33. doi:10.1007/s11145-019-09963-6 Costa, L.J., Green, M., Sideris, J., & Hooper, S.R. (2018). First-grade cognitive predictors of writing disabilities in grades 2 through 4 elementary school students. Journal of Learning Disabilities, 51(4), 351–62. Cragg, L., & Nation, K. (2006). Exploring written narrative in children with poor reading comprehension. Educational Psychology, 26, 17. Crossley, S.A., Bradfield, F., & Bustamante, A. (2019). Using human judgments to examine the validity of automated grammar, syntax, and mechanical errors in writing. Journal of Writing Research, 11(2), 251–70. doi:10.17239/jowr-2019.11.02.01 Crossley, D., & Kyle, K. (2018). Assessing writing with the tool for the automatic analysis of lexical sophistication (TAALES). Assessing Writing, 38, 46–50. Crossley, S.A., Allen, L.K., Kyle, K., & McNamara, D.S. (2014). Analyzing discourse processing using a simple natural language processing tool. Discourse Processes, 51(5–6), 511–34. Crossley, S.A., Kyle, K., & McNamara, D.S. (2016). The tool for the automatic analysis of text cohesion (TAACO): automatic assessment of local, global, and text cohesion. Behavior Research Methods, 48(4), 1227–37. De la Paz, S. (1999). Teaching writing strategies and self-regulation procedures to middle school students with learning disabilities. Focus on Exceptional Children, 31(5), 1–16. De la Paz, S., & Graham, S. (2002). Explicitly teaching strategies, skills, and knowledge: writing instruction in middle school classrooms. Journal of Educational Psychology, 94(4), 687–98. Deane, P. (2018). The challenges of writing in school: conceptualizing writing development within a sociocognitive framework. Educational Psychologist, 53(4), 280–300. Deane, P., Song, Y., van Rijn, P., O’Reilly, T., Fowles, M., Bennett, R., . . . & Zhang, M. (2018). The case for scenario-based assessment of written argumentation. Reading and Writing: An Interdisciplinary Journal, 32(6), 1575–606. Diamond, A. (2013). Executive Functions. Annual Review of Psychology, 64(1), 135–68. Diercks-Gransee, B., Weissenburger, J.W., Johnson, C.L., & Christensen, P. (2009). Curriculum- based measures of writing for high school students. Remedial and Special Education, 30(6), 360–71. Dikli, S. (2006). An overview of automated scoring of essays. The Journal of Technology, Learning and Assessment, 5(1). Retrieved from https://ejournals.bc.edu/index.php/jtla/article/view/1640 Dockrell, J.E., Connelly, V., & Arfè, B. (2019). Struggling writers in elementary school: capturing drivers of performance. Learning and Instruction, 60, 75–84. Dockrell, J.E., Lindsay, G., & Connelly, V. (2009). The impact of specific language impairment on adolescents’ written text. Exceptional Children, 75(4), 427–46.
References 129 Dockrell, J.E., Lindsay, G., Connelly, V., & Mackie, C. (2007). Constraints in the production of written text in children with specific language impairments. Exceptional Children, 73, 147–64. Dockrell, J.E., Marshall, C.R., & Wyse, D. (2016). Teachers’ reported practices for teaching writing in England. Reading and Writing, 29(3), 409–34. Dockrell, J.E., Ricketts, J., Charman, T., & Lindsay, G. (2014). Exploring writing products in students with language impairments and autism spectrum disorders. Learning and Instruction, 32, 81–90. Dockrell, J.E., Marshall, C.R, & Wyse, D. (2015). Talk for Writing. Evaluation Report and Executive Summary. Retrieved from: https://files.eric.ed.gov/fulltext/ED581467.pdf Dockrell, J.E., Connelly, V., Walter, K., & Critten, S. (2015). Assessing children's writing products: the role of curriculum based measures. British Educational Research Journal, 41(4), 575–95. doi:10.1002/berj.3162 Drijbooms, E., Groen, M.A., & Verhoeven, L. (2015). The contribution of executive functions to narrative writing in fourth grade children. Reading and Writing: An Interdisciplinary Journal, 28(7), 989–1011. doi:10.1007/s11145-015-9558-z Drijbooms, E., Groen, M.A., & Verhoeven, L. (2017). How executive functions predict development in syntactic complexity of narrative writing in the upper elementary grades. Reading and Writing, 30(1), 209–31. doi:10.1007/s11145-016-9670-8. Epub 2016 Jul 1. PMID: 28163388; PMCID: PMC5247531. Dunsmuir, S., Kyriacou, M., Batuwitage, S., Hinson, E., Ingram, V., & O’Sullivan, S. (2015). An evaluation of the Writing Assessment Measure (WAM) for children’s narrative writing. Assessing Writing, 23, 1–18. Duran, P., Malvern, D., Richards, B., & Chipere, N. (2004). Developmental trends in lexical diversity. Applied Linguistics, 25(2), 220–42. Espin, C., De La Paz, S., Scierka, B.J., & Roelofs, L. (2005). The relationship between curriculum- based measures in written expression and quality and completeness of expository writing for middle school students. Journal of Special Education, 38(4), 208–17. Espin, C., Shin, J., Deno, S. L., Skare, S., Robinson, S., & Benner, B. (2000). Identifying indicators of written expression proficiency for middle school students. Journal of Special Education, 34(3), 140–53. Espin, C., Wallace, T., Campbell, H., Lembke, E.S., Long, J.D., & Ticha, R. (2008). Curriculum- based measurement in writing: predicting the success of high-school students on state standards tests. Exceptional Children, 74(2), 174–93. Fayol, M., Alarmagot, D., & Berninger, V. (2012). Translation of Thought to Written Text While Composing: Advancing Theory, Knowledge, Methods and Applications. New York, NY: Psychology Press/Taylor. Fitzgerald, J. (1987). Research on revision in writing. Review of Educational Research, 57(4), 481–506. Fuchs, L.S., & Fuchs, D. (2009). On the Importance of a Unified Model of Responsiveness to Intervention. Child Development Perspectives, 3, 41–3. doi:0.1111/j.1750-8606.2008. 00074.x Galbraith, D., & Baaijen, V.M. (2019). Aligning keystrokes with cognitive processes in writing. In E. Lindgren & K. Sullivan (Eds.). Observing Writing (pp. 306–25). Leiden, the Netherlands: BRILL. Gansle, K.A., Noell, G.H., VanDerHeyden, A.M., Naquin, G.M., & Slider, N.J. (2002). Moving beyond total words written: the reliability, criterion validity, and time cost of alternate measures for curriculum-based measurement in writing. School Psychology Review, 31(4), 477–97. Gansle, K.A., Noell, G.H., Vanderheyden, A.M., Slider, N.J., Hoffpauir, L.D., Whitmarsh, E.L., & Naquin, G.M. (2004). An examination of the criterion validity and sensitivity to brief
130 5. Capturing the Challenges in Assessing Writing intervention of alternate curriculum-based measures of writing skill. Psychology in the Schools, 41(3), 291–300. Gansle, K.A., VanDerHeyden, A.M., Noell, G.H., Resetar, J.L., & Williams, K.L. (2006). The technical adequacy of curriculum-based and rating-based measures of written expression for elementary school students. School Psychology Review, 35(3), 435–50. Graham, S. (2018). Introduction to conceptualizing writing. Educational Psychologist, 53(4), 217–19. Graham, S., Berninger, V.W., Abbott, R.D., Abbott, S.P., & Whitaker, D. (1997). Role of mechanics in composing of elementary school students. A new methodological approach. Journal of Educational Psychology, 89(13), 170–82. Graham, S., & Harris, K.R. (2017). Evidence-based writing practices: A meta-analysis of existing meta- analyses. In Design Principles for Teaching Effective Writing. Leiden, The Netherlands: Brill. doi:10.1163/9789004270480_003 Graham, S., Harris, K., & Hebert, M. (2011). Informing Writing: The Benefits of Formative Assessment. A Carnegie Corporation Time to Act report. Retrieved from Washington, D.C.: https://w ww.carnegie.org/p ublications/i nforming-w riting-t hebenefits-of-formative-assessment/ Graham, S., Hebert, M., Sandbank, M.P., & Harris, K.R. (2016). Assessing the writing achievement of young struggling writers: application of generalizability theory. Learning Disability Quarterly, 39(2), 72–82. Graham, S., Schwartz, S.S., & Macarthur, C.A. (1993). Knowledge of writing and the composing process, attitude toward writing, and self-efficacy for students with and without learning- disabilities. Journal of Learning Disabilities, 26(4), 237–49. Hayes, J. R. (2009). From idea to text. In R. Beard, D. Myhill, M. Nystrand, & J. Riley (Eds.). Handbook of Writing Development (pp. 65–79). London, UK: Sage. Hayes, J. R. (2012a). Modeling and remodeling writing. Written Communication, 29(3), 369–88. Hayes, J.R. (2012b). Evidence from language bursts, revision, and transcription for translation and its relation to other writing processes. In M. Fayol, D. Alamargot, and V. Berninger (Eds.). Translation of Thought to Written Text While Composing: Advancing Theory, Knowledge, Methods, and Applications (pp. 45–67). New York, NY: Psychology Press. Hayes, J.R., & Berninger, V.W. (2014). Cognitive processing in writing. In B. Arfè, J.E. Dockrell, & V. Berninger (Eds.). Writing Development in Children with Hearing Loss, Dyslexia or Oral Language Problems: Implications for Assessment and Instruction (pp. 3–15). New York, NY: Oxford University Press. Hayes, J.R., & Nash, J.G. (1996). On the nature of planning in writing. In C. M. Levy & S. Ransdell (Eds.). The Science of Writing: Theories, Methods, Individual Differences, and Applications (pp. 29–55). Mahwah, NJ: Lawrence Erlbaum. Hayes, J., & Flower, L. (1980). Identifying the organisation of writing processes. In L. Gregg & R. Sternberg (Eds.). Cognitive Processes in Writing (pp. 3–30). Mahwah, NJ: Lawrence Erlbaum. Hayes, J.R. (2011). Kinds of knowledge-telling: modelling early writing development. Journal of Writing Research, 3(2), 74–92. Hebert, M., Gillespie, A., & Graham, S. (2013). Comparing effects of different writing activities on reading comprehension: a meta-analysis. Reading and Writing, 26(1), 111–38. Hull, G., & Schultz, K. (2001). Literacy and learning out of school: a review of theory and research. Review of Educational Research, 71(4), 575–611. Huot, B. (1990). The literature of direct writing assessment—major concerns and prevailing trends. Review of Educational Research, 60(2), 237–63. Jeong, H. (2017). Narrative and expository genre effects on students, raters, and performance criteria. Assessing Writing, 31, 113–25. Kaufer, D.S., Hayes, J.R., & Flower, L. (1986). Composing written sentences. Research in the Teaching of English, 20(2), 121–40.
References 131 Keller-Margulis, M.A., Ochs, S., Reid, E.K., Faith, E.L., & Schanding, G.T. (2019). Validity and diagnostic accuracy of early written expression screeners in kindergarten. Journal of Psychoeducational Assessment, 37(5), 539–52. Kellogg, R. (1988). Attentional overload and writing performance: effects of rough draft and outline strategies. Journal of Experimental Psychology: Learning, Memory and Cognition, 14(2), 355–65. Kellogg, R.T. (1990). Effectiveness of prewriting strategies as a function of task demands. American Journal of Psychology, 103, 327–42. Kellogg, R.T. (2008). Training writing skills: a cognitive developmental perspective. Journal of Writing Research, 1, 26. Kent, S.C., & Wanzek, J. (2016). The relationship between component skills and writing quality and production across developmental levels: a meta-analysis of the last 25 years. Review of Educational Research, 86(2), 570–601. Kieft, M., Rijlaarsdam, G., Galbraith, D., & van den Bergh, H. (2007). The effects of adapting a writing course to students’ writing strategies. British Journal of Educational Psychology, 77(3), 565–78. Kim, Y.S.G. (2016). Direct and mediated effects of language and cognitive skills on comprehension of oral narrative texts (listening comprehension) for children. Journal of Experimental Child Psychology, 141, 101–20. Kim, Y.S.G., & Schatschneider, C. (2017). Expanding the developmental models of writing: a direct and indirect effects model of developmental writing (DIEW). Journal of Educational Psychology, 109(1), 35–50. Kim, Y.S.G., Schatschneider, C., Wanzek, J., Gatlin, B., & Al Otaiba, S. (2017). Writing evaluation: rater and task effects on the reliability of writing scores for children in Grades 3 and 4. Reading and Writing, 30(6), 1287–310. Kim, Y.S., Al Otaiba, S., & Wanzek, J. (2015). Kindergarten predictors of third grade writing. Learning and Individual Differences, 37, 27–37. Kim, Y.S., Al Otaiba, S., Puranik, C., Folsom, J.S., Greulich, L., & Wagner, R.K. (2011). Componential skills of beginning writing: an exploratory study. Learning and Individual Differences, 21(5), 517–25. Kim, Y.S., Al Otaiba, S., Wanzek, J., & Gatlin, B. (2015). Toward an understanding of dimensions, predictors, and the gender gap in written composition. Journal of Educational Psychology, 107(1), 79–95. Kim, Y.-S., Al Otaiba, S., Folsom, J.S., Greulich, L., & Puranik, C. (2014). Evaluating the dimensionality of first-grade written composition. Journal of Speech Language and Hearing Research, 57(1), 199–211. Kintsch, W. (1992). The construction integration model—a cognitive architecture for comprehension. International Journal of Psychology, 27(3–4), 66. Kintsch, W. (2005). An overview of top-down and bottom-up effects in comprehension: the CI perspective. Discourse Processes, 39(2–3), 125–8. Koutsoftas, A.D. (2016). Writing process products in intermediate-grade children with and without language-based learning disabilities. Journal of Speech Language and Hearing Research, 59(6), 1471–83. Koutsoftas, A.D., & Gray, S. (2012). Comparison of narrative and expository writing in students with and without language-learning disabilities. Language, Speech, and Hearing Services in Schools, 43(4), 395–409. Koutsoftas, A.D., & Gray, S. (2013). A structural equation model of the writing process in typically-developing sixth grade children. Reading and Writing, 26(6), 941–66. Largy, P., Dedeyan, A., & Hupet, M. (2004). Orthographic revision: a developmental study of how revisers check verbal agreements in written texts. British Journal of Educational Psychology, 74, 533–50.
132 5. Capturing the Challenges in Assessing Writing Lee, Y.W., Gentile, C., & Kantor, R. (2010). Toward automated multi-trait scoring of essays: investigating links among holistic, analytic, and text feature scores. Applied Linguistics, 31(3), 391–417. Limpo, T., & Alves, R.A. (2013). Modeling writing development: contribution of transcription and self-regulation to Portuguese students’ text generation quality. Journal of Educational Psychology, 105(2), 401–13. Limpo, T., & Alves, R.A. (2018). Effects of planning strategies on writing dynamics and final texts. Acta Psychologica, 188, 97–109. Limpo, T., Alves, R.A., & Fidalgo, R. (2014). Children’s high-level writing skills: development of planning and revising and their contribution to writing quality. British Journal of Educational Psychology, 84(2), 177–93. Llaurado, A., & Dockrell, J.E. (2019). Children’s plans for writing: characteristics and impact on writing performance. Journal of Literacy Research, 51(3), 336–56. Macarthur, C.A., & Graham, S. (1987). Learning-disabled students composing under 3 methods of text production—handwriting, word-processing, and dictation. Journal of Special Education, 21(3), 22–42. MacArthur, C., Graham, S., & Fitzgerald, J. (2006). Handbook of Research on Writing. New York, NY: Guildford. Mackie, C.J., Dockrell, J., & Lindsay, G. (2013). An evaluation of the written texts of children with SLI: the contributions of oral language, reading and phonological short-term memory. Reading and Writing, 26(6), 865–88. Mackie, C., & Dockrell, J.E. (2004). The nature of written language deficits in children with SLI. Journal of Speech Language and Hearing Research, 47(6), 1469–83. McCutchen, D. (1988). Functional automaticity in children’s writing—a problem of metacognitive control. Written Communication, 5(3), 306–24. McCutchen, D. (1996). A capacity theory of writing: working memory in composition. Educational Psychology Review, 8(3), 299–325. McCutchen, D., Covill, A., Hoyne, S.H., & Mildes, K. (1994). Individual-differences in writing— implications of translating fluency. Journal of Educational Psychology, 86(2), 256–66. McMaster, K.L., Du, X., & Petursdottir, A.-L. (2009). Technical features of curriculum-based measures for beginning writers. Journal of Learning Disabilities, 42(1), 41–60. McMaster, K., & Espin, C. (2007). Technical features of curriculum-based measurement in writing—a literature review. Journal of Special Education, 41(2), 68–84. Meadows, M., & Billington, L. (2005). Review of the Literature on Marking Reliability. Report for the Qualifications and Curriculum Authority. London, UK: National Assessment Agency. Mo, Y., & Troia, G.A. (2017). Similarities and differences in constructs represented by US States’ middle school writing tests and the 2007 National Assessment of Educational Progress writing assessment. Assessing Writing, 33, 48–67. Myhill, D., & Jones, S. (2007). More than just error correction—students’ perspectives on their revision processes during writing. Written Communication, 24(4), 323–43. Nelson, N.W., & Van Meter, A.M. (2007). Measuring written language ability in narrative samples. Reading & Writing Quarterly, 23(3), 287–309. Olinghouse, N.G., & Graham, S. (2009). The relationship between the discourse knowledge and the writing performance of elementary-grade students. Journal of Educational Psychology, 101(1), 37–50. Olinghouse, N.G., & Leaird, J.T. (2009). The relationship between measures of vocabulary and narrative writing quality in second-and fourth-grade students. Reading and Writing, 22(5), 545–65. Olinghouse, N.G., & Santangelo, T. (2010). Assessing the writing of struggling learners. Focus on Exceptional Children, 43(4), 1–27. Olinghouse, N.G., & Wilson, J. (2013). The relationship between vocabulary and writing quality in three genres. Reading and Writing, 26(1), 45–65.
References 133 Olinghouse, N.G., Graham, S., & Gillespie, A. (2015). The relationship of discourse and topic knowledge to fifth graders’ writing performance. Journal of Educational Psychology, 107(2), 391–406. Olive, T. (2014). Toward a parallel and cascading model of the writing system: a review of research on writing processes coordination. Journal of Writing Research, 6(2). Olive, T., Alves, R.A., & Castro, S.L. (2009). Cognitive processes in writing during pause and execution periods. European Journal of Cognitive Psychology, 21, 758–85. Olive, T., Favart, M., Beauvais, C., & Beauvais, L. (2009). Children’s cognitive effort and fluency in writing: effects of genre and of handwriting automatisation. Learning and Instruction, 19(4), 299–308. Olive, T., & Kellogg, R.T. (2002). Concurrent activation of high-and low-level production processes in written composition. Memory & Cognition, 30, 594–600. Parr, J.M., & Jesson, R. (2016). Mapping the landscape of writing instruction in New Zealand primary school classrooms. Reading and Writing, 29(5), 981–1011. Prunty, M.M., Barnett, A.L., Wilmut, K., & Plumb, M.S. (2016). The impact of handwriting difficulties on compositional quality in children with developmental coordination disorder. British Journal of Occupational Therapy, 79(10), 591–7. Puranik, C.S., & AlOtaiba, S. (2012). Examining the contribution of handwriting and spelling to written expression in kindergarten children. Reading and Writing, 25(7), 1523–46. Puranik, C.S., Lombardino, L.J., & Altmann, L.J.P. (2008). Assessing the microstructure of written language using a retelling paradigm. American Journal of Speech-Language Pathology, 17(2), 107–20. Qualifications and Curriculum Authority (2010). The National Curriculum. Level descriptions for subjects. Ref QCDA/09/4675 ISBN 978-1-84962-312-4. Retrieved from https://dera.ioe. ac.uk/10747/7/1849623848_Redacted.pdf Reilly, J., Zamora, A., & McGivern, R.F. (2005). Acquiring perspective in English: the development of stance. Journal of Pragmatics, 37(2), 185–208. Rexaei, A., & Lovorn, M. (2010). Reliability and validity of rubrics for assessment through writing. Assessing Writing, 15, 18–39. Rietdijk, S., van Weijen, D., Janssen, T., van den Bergh, H., & Rijlaarsdam, G. (2018). Teaching writing in primary education: classroom practice, time, teachers’ beliefs and skills. Journal of Educational Psychology, 110(5), 640–63. Roessingh, H., Elgie, S., & Kover, P. (2015). Using lexical profiling tools to investigate children’s written vocabulary in grade 3: an exploratory study. Language Assessment Quarterly, 12(1), 67–86. Rust, J. (1996). Wechsler Objective Language Dimensions (WOLD): UK Edition. London, England: Psychological Corporation. Savage, R., Kozakewich, M., Genesee, F., Erdos, C., & Haigh, C. (2017). Predicting writing development in dual language instructional contexts: exploring cross-linguistic relationships. Developmental Science, 20(1). doi:10.1111/desc.12406 Scardamalia, M., & Bereiter, C. (1986). Research on written composition. In M. Wittrock (Ed.). Handbook of Research on Teaching (3rd ed.). New York, NY: Macmillan Education Ltd. Schoonen, R. (2012). The validity and generalizability of writing scores: the effect of rater, task and language. Measuring Writing: Recent Insights into Theory, Methodology and Practices, 1–22. doi:10.1108/s1572-6304(2012)0000027004 Scott, C.M., & Windsor, J. (2000). General language performance measures in spoken and written narrative and expository discourse of school-age children with language learning disabilities. Journal of Speech Language and Hearing Research, 43(2), 324–339. Sénéchal, M., Hill, S., & Malette, M. (2018). Individual differences in grade 4 children’s written compositions: the role of online planning and revising, oral storytelling, and reading for pleasure. Cognitive Development, 45, 92–104.
134 5. Capturing the Challenges in Assessing Writing Standards and Testing Agency (2019). Key stage 2 English grammar, punctuation and spelling, Paper 1: questions. Retrieved from https://assets.publishing.service.gov.uk/government/ uploads/system/uploads/attachment_data/file/803816/STA198213e_2019_ks2_English_ GPS_Paper1_questions.pdf Stuart, N.J., Connelly, V., & Dockrell, J.E. (2019). Written verb use and diversity in children with Developmental Language Disorder: stepping stones to academic writing. Reading and Writing, 3, 67–96. Sumner, E., Connelly, V., & Barnett, A.L. (2016). The influence of spelling ability on vocabulary choices when writing for children with dyslexia. Journal of Learning Disabilities, 49(3), 293–304. Torkildsen, J.V., Morken, F., Helland, W.A., & Helland, T. (2016). The dynamics of narrative writing in primary grade children: writing process factors predict story quality. Reading and Writing, 29(3), 529–54. Torrance, M., Alamargot, D., Castelló, M., Ganier, F., Kruse, O., Mangen, A., . . . & van Waes, L. (2012). Learning to Write Effectively: Current Trends in European Research. Bingley, UK: Emerald Group Publishing. Torrance, M., Fidalgo, R., & García, J.-N. (2007). The teachability and effectiveness of cognitive self-regulation in sixth-grade writers. Learning and Instruction, 17(3), 265–85. Torrance, M., Thomas, G.V., & Robinson, E.J. (1999). Individual differences in writing behaviours of undergraduate students. British Journal of Ediucational Psychology, 69, 189–99. Truckenmiller, A.J., McKindles, J.V., Petscher, Y., Eckert, T.L., & Tock, J. (2019). Expanding curriculum-based measurement in written expression for middle school. The Journal of Special Education, 54(3), 133–45. Vanderberg, R., & Swanson, H.L. (2007). Which components of working memory are important in the writing process? Reading and Writing, 20(7), 721–52. Wagner, R.K., Puranik, C.S., Foorman, B., Foster, E., Wilson, L.G., Tschinkel, E., & Kantor, P.T. (2011). Modeling the development of written language. Reading and Writing, 24(2), 203–20. Westby, C.E., & Clauser, P.S. (1999). The right stuff for writing: assessing and facilitating written language. In H. Catts & A. Kamhi (Eds.). Language and Reading Disabilities (pp. 259–324). New York, NY: Allyn and Bacon. Whitaker, D., Berninger, V., Johnston, J., & Swanson, H.L. (1994). Intraindividual differences in levels of language in intermediate grade writers—implications for the translating process. Learning and Individual Differences, 6(1), 107–30. Wijekumar, K., Graham, S., Harris, K.R., Lei, P.W., Barkel, A., Aitken, A., . . . & Houston, J. (2019). The roles of writing knowledge, motivation, strategic behaviors, and skills in predicting elementary students’ persuasive writing from source material. Reading and Writing, 32(6), 1431–57. Williams, G.J., Larkin, R.F., & Blaggan, S. (2013). Written language skills in children with specific language impairment. International Journal of Language & Communication Disorders, 48(2), 160–71. Wilson J. (2018). Universal screening with automated essay scoring: Evaluating classification accuracy in grades 3 and 4. Journal of School Psychology, 68, 19–37. doi:10.1016/ j.jsp.2017.12.005. Epub 2018 Feb 3. PMID: 29861028. Wilson, J., Chen, D., Sandbank, M.P., & Hebert, M. (2019). Generalizability of automated scores of writing quality in Grades 3–5. Journal of Educational Psychology, 111(4), 619–40. Wilson, J., & Roscoe, R. (2019). Automated writing evaluation and feedback: Multiple metrics of efficacy. Journal of Educational Computing Research. https://doi.org/10.1177/ 0735633119830764 Wilson, J., Roscoe, R., & Ahmed, Y. (2017). Automated formative writing assessment using a levels of language framework. Assessing Writing, 34, 16–36.
References 135 Wood, C., Schatschneider, C., & Hart, S. (2020). Average one year change in lexical measures of written narratives for school age students. Reading & Writing Quarterly, 36(3), 260–77. Yu, G. (2010). Lexical diversity in writing and speaking task performances. Applied Linguistics, 31(2), 236–59. Zoccolotti, P., De Luca, M., Marinelli, C.V., & Spinelli, D. (2014). Modeling individual differences in text reading fluency: a different pattern of predictors for typically developing and dyslexic readers. Frontiers in Psychology, 5, 1374.
IV
EXECUTIVE FUNCTIONS AND WRITING ACROSS THE LIFESPAN
6 Executive Functions and Writing Skills in Children and Adolescents Developmental Associations and Dissociations Stephen R. Hooper, Lara Costa, Edmund Fernandez, Alexandra Barker, Courtney Valdes, Stephanie Catlett, and Melissa Green
Introduction In this chapter we provide an overview of what is known and unknown about the relations between executive functions (EF) and written expression. To this point in the volume, chapters have expertly dealt with key definitional issues, the importance of the context of written expression, and assessment strategies. To follow are chapters dealing with EFs across the lifespan, with a particular focus on different types of writers. As part of that selection of chapters (Executive Functions and Writing Across the Lifespan), we present the developmental associations and dissociations in the relations between EFs and writing skills in children and adolescents. We provide an overview of some of the models of EF that are applicable to written expression, and we will invoke a developmental perspective to understand some of the relations between EF and writing skills. An overview of evidence-based findings pertaining to the EF components relevant for written expression are presented, and important associations and disassociations will be underscored—when either suspected or supported by the empirical literature. Finally, the chapter will conclude with some directions for future research into advancing our understanding of these relationships.
Executive Function Models Applicable to Written Expression EF is a multidimensional construct that refers to the higher-level cognitive processes needed for goal-directed control of thoughts, behaviours, and emotions (Friedman & Miyake, 2017). As seen in Chapter 2, EF is a multidimensional set of skills, with each skill contributing to the overall regulatory functioning of the individual. The Stephen R. Hooper, Lara Costa, Edmund Fernandez, Alexandra Barker, Courtney Valdes, Stephanie Catlett, and Melissa Green, Executive Functions and Writing Skills in Children and Adolescents In: Executive Functions and Writing. Edited by: Teresa Limpo and Thierry Olive, Oxford University Press. © Oxford University Press 2021. DOI: 10.1093/oso/9780198863564.003.0006
140 6. Executive Functions and Writing Skills construct typically includes working memory, inhibitory control, cognitive flexibility, set shifting, planning/problem solving, attention regulation, and emotional regulation. Suffice it to say, as a testament to the multidimensionality of EF, there are conceptual and empirical models going back over 35 years describing 2 (Carlson, Moses & Claxton, 2004), 3 (Hughes, Ensor, Wilson, & Graham, 2009), 4 (Espy et al., 2004), and 6 factors (Daigneault, Braun, & Whitaker, 1992). For preschool children, there has been some debate over the number of EF components that exist, with some investigators proposing a one factor model (Allan & Lonigan, 2011) and other groups suggesting multiple (2 or 3) dimensions (Garon, Byrson, & Smith 2008). How these various models relate to written expression remains relatively unknown, but there has been an increasing amount of literature that has begun to explore these relationships (Costa, Greene & Hooper, 2020; Hooper et al., 2020; Hooper et al., 2011; Zins & Hooper, 2012). For instance, Hooper et al. (2002) demonstrated the importance of several EFs (i.e. initiating, set shifting, sustaining) as differentiating those with and without writing problems in fourth and fifth grade, and Hooper et al. (2011) showed that EF could serve as early predictors in spelling and written expression in first and second grade students. Given its complexity, numerous definitions of EF also have been proposed— including those espoused in this text, as well as several models, theories, and frameworks (e.g. Miyake et al., 2000; Pennington, Bennetto, McAleer, & Roberts, 1996; Zelazo, Carter, Reznick, & Frye, 1997). Many definitions of EF are simply a list of the components that are thought to comprise this construct, while other models do not focus on the theoretical relationships among EF components but, rather, are constructed based on the components of the measure being used to assess EF processes (Barkley, 2001). Other definitions and models treat EF as a single distinct human ability (Zelazo, Muller, Frye, & Marcovitch, 2003). Prior to discussion on the developmental aspects of EF and the available literature showing a linkage between EF and writing in children and adolescents, we will describe several key models (i.e. Psychological Models, Problem-Solving Models, Working Memory Models) that have potential applications to written expression.
Psychological Models Pennington and colleagues (Pennington, Bennetto, McAleer, & Roberts, 1996; Welsh & Pennington, 1988; Welsh, Pennington, & Grosser, 1991) have theorized and examined EF through three lenses: developmental psychology, cognitive psychology, and neuropsychology. The definition Welsh and Pennington put forth in 1988 has endured, even though Pennington and Ozonoff (1996) claimed that it was temporary and underspecified. Welsh and Pennington (1988) defined EF as: ‘the ability to maintain an appropriate problem-solving set for attainment of a future goal. This set can involve one or more of the following: (a) an intention to inhibit a response or
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to defer it to a later more appropriate time, (b) a strategic plan of action sequences, and (c) a mental representation of the task’ (pp. 201–2). EF, such as regulatory control, planning, set shifting, working memory, contextual memory, inhibition, fluency, maintaining goals, attentional control, and self-monitoring, all facilitate goal-directed behaviour (Pennington & Ozonoff, 1996; Roberts & Pennington, 1996), and a quick linkage can be made to the production of written output. As we will explore later in this chapter, all of these EF components appear to have significant relevance to the development and production of writing, although perhaps some may have more of an impact at different developmental time points.
Problem-Solving Models Zelazo, Carter, Reznick, and Frye (1997) created a problem-solving framework for understanding executive functioning. They suggested a problem-based lens with time ordered phases to aid in the systematization of the wide range of EF aspects. With the hope of creating a definition that was more than a list of EF abilities (e.g. expectation, goal creation, planning, and monitoring of responses and feedback; Stuss & Benson, 1984), Zelazo et al. (1997) defined executive function as the control of thought and action where the outcome is the solution to the problem. While Pennington and colleagues sought to explore the interactions between various EF, Zelazo et al. decided that in order to study EF a framework was needed that could be used in various contexts that involved problem solving. Zelazo, Muller, Frye, and Marcovitch (2003) developed and revised their framework to include a developmental component. In their Cognitive Complexity and Control (CCC) theory (Frye, Zelazo, & Burack, 1998; Zelazo & Frye, 1998), these investigators explained that EF development ‘can be understood in terms of age-related increases in the maximum complexity of the rules children can formulate and use when solving problems’ (p. vii). In other words, maturation drives changes in EF performance scores such that as children age, the rules they can use to solve problems become more complex. While Zelazo et al. (2003) advanced the understanding of the development of EF through the CCC theory, most recently Zelazo, Qu, and Kesek (2010) have taken the theory a step further to include emotional and motivational components—also key aspects to written expression. They suggested that these factors are important because they bring about meaningful, self-relevant (i.e. applicable to the individual) rewards or punishers. They assert that a complete understanding of the development of EF requires both hot (i.e. emotional and motivational) and cool (i.e. cognitive) components. Zelazo et al. (2010) suggested that together these components interact (e.g. emotional aspects can hinder or assist cognitive processing), are driven by maturation, and influence the control of thought and goal-directed behaviour (i.e. EF). All of these components are critical to the writing process, with this model also involving the affective components that can be involved in written expression.
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Working Memory Models The EF models reviewed here subsume working memory under EF, as the theorists believe that working memory is one of several EF. Not all theorists, however, have modelled working memory in this way. For instance, Kellogg (1999), Cowan (2005), and Baddeley and Larsen (2007) proposed models that only explain working memory. Not one included the term EF, although they did include constructs of attention, which Zelazo et al. and Pennington et al. consider an EF. Furthermore, Berninger and Winn (2006) present working memory and EF as separate constructs in their Not-So- Simple View of Writing. The differences in how theorists model the relation between working memory and EF is not insignificant, but it important to note that an ideal model for working memory has yet to be supported. Even though the models vary in scope and emphasis, they all recognize the essential role working memory has in complex cognition (Miyake et al., 2000). To date, given its purported importance to writing, working memory has been included in nearly all cognitive models of written expression, and its theoretical importance to the development of the writing process and the execution of the writing product seems clear, although the available empirical evidence is relative sparse in children.
Development of Executive Functions In addition to the issues of multidimensionality, EF are considered developmental constructs (i.e. those that change over time) by all theorists (e.g. Denckla, 2007; Friedman et al., 2008; Welsh & Pennington, 1988; Zelazo, Qu, & Kesek, 2010), with each of the EF subcomponents having an overlapping, but individual ontogeny. Generally, EF begin as simple and develop on a continuum to become more refined across the lifespan (Welsh & Pennington, 1988). Simply put, when people are younger, they can only handle tasks requiring little effort; but, as they grow older, they can handle more demanding and complex ones (Denckla, 1996). Specifically, EF begin to develop in infancy and continue well into the second decade of life, with some theorists noting that EF can continue evolving into the early forties (Denckla, 2007). As well, the mental representations of young children are one-dimensional and concrete, and therefore do not contain all pertinent task information; but, as children develop, these representations begin to include abstract sequences of actions, and imagined goals and outcomes become more refined and complex (Welsh & Pennington, 1988). While a thorough developmental mapping of the various EF has not yet been conducted, the literature does provide emergent clues as to how many of the core EF evolve over time. A developmental unfolding of basic EF begins very early in life, but typically they are first noted during the preschool years. For example, attentional control appears to manifest in infancy and shows continued development well into the second and
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third decades of life (Anderson, 2002). Inhibitory control is one of the first noted at age 3 years, and this is followed by set-shifting at ages 4 for simple response sets with subsequent more rapid growth occurring at ages 5 to 6 years and throughout late childhood and early adolescence. Similarly, working memory begins to manifest and become more functional at around age 4 with its developmental trajectory being tracked into the early teenage years (Best & Miller, 2010). Planning, problem solving, and strategy use are evident early in the preschool years, but typically are focused on specific tasks and not routinely generalized. At around 8 years of age, however, children begin to use strategies in a routine fashion, but they also begin to devise their own strategies to solve problems. The development of the various EFs is not mutually exclusive and build on one another to facilitate increased demands. Further, despite the argument of multidimensionality of EF across the lifespan, there are a number of studies in the preschool years that argue that this multidimensionality evolves out of a single dimension (Allan & Lonigan, 2011). In a similar fashion, writing skills evolve from early sounds and symbols critical to the emergent literacy process, with ideation, handwriting, spelling, and sentence construction evolving in the late preschool and early elementary years, and the higher-order aspects of perspective taking, planning, and editing evolving later. Berninger and Winn (2006) provided a theoretical unfolding for these skills in their Not-So-Simple View of Writing wherein fine-motor skills contributed to early writing output, the development of language capabilities facilitated the ongoing development of these skills, and finally EFs, particularly working memory, playing a critical role in the writing process. More specifically, EF are associated with handwriting automaticity, which requires both orthographic-motor integration and processing speed, and with higher-level composing (Altemeier, Abbott, & Berninger, 2008). A clear empirical basis for this theoretical model is needed, particularly, since recent evidence has shown the importance of EF in not only early elementary writing performance (e.g. Hooper et al., 2011), but also in teacher ratings of preschool performance (Hooper et al., 2020). The Not-So-Simple View of Writing does provide a formulation for how various relations between EF and writing could manifest. How the concurrent evolution of EF and writing skills takes place remains a challenge to our understanding this relationship, but given the abundance of literature shared in this volume, clearly the development of one does appear to affect the other— perhaps in a bidirectional manner. Indeed, this is a complex interrelationship with multiple dimensions, each developing over time in their own right, yet overlapping. We still do not have a good understanding of this developmental unfolding for written expression, and this dilemma becomes even more complex when we insert the developmental unfolding of EF. Some initial efforts have begun to be asserted in this regard (e.g. Costa, Greene, & Hooper, 2020; Decker et al., 2016; Zins & Hooper, 2012), and findings from these compilations of literature and associated empirical studies should provide insights into what relations might be most critical and when.
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An Overview of the Relations Between EF Components and Writing As noted earlier and throughout this volume, there is abundant literature to describe the components of EF and the components of writing output, but there are relatively few studies detailing the relations between EF and writing skills across the life span. In concert with Willoughby and Hudson in this volume (Chapter 2), we examine a common set of EF features—inhibitory control, cognitive flexibility, working memory, and planning—and describe what is known about their relations to written expression. While we are mindful that these relations likely extend across the lifespan, we focus on children and adolescents.
Inhibitory Control Inhibitory control can be looked at both cognitively (attention) and behaviourally (impulse control). Best and Miller (2010) noted that inhibitory control is the one of the primary EF that first develops around the age of 3 or 4, and most likely has its origins even earlier in infancy and toddlerhood. With inhibitory control in place, this EF allows a person to develop all other executive functions. In order to successfully complete a task or meet a goal, inhibition delays the automatic response by allowing the implementation of self-directed and self-regulatory actions. Inhibitory control has been studied by looking at the Stop Signal Task (SST) during reading and writing. Children who have a deficit in their inhibitory control may respond too quickly or too slowly. Schacher et al. (1999) examined inhibitory control in children with ADHD, ages 7 to 12 years, and found a deficit when compared to similarly aged children with learning disabilities, behavioural disorders, or anxiety disorders on the SSTs. Children in the latter groups performed on par with typically developing children (Schacher & Logan, 1990; Schacher, Tannock, Marriott, & Logan, 1995). These findings were consistent with previous research findings showing children with ADHD having less inhibitory control than typical children (Oosterlaan, Logan, & Sergeant, 1998). While children with ADHD, conduct disorder (CD), and both ADHD and CD had slower reaction times than control children, only children with a single diagnosis of ADHD had slower stop reaction times. Given the relatively poorer writing performance in children with ADHD (see Filipe, Chapter 7), these findings would suggest the importance of intact inhibitory control to facilitate the development of writing skills. More recently, Lipszyc and Schachar (2010) completed a meta-analysis of studies examining the SST as a measure to assess inhibitory control. They found similar findings across multiple studies that totalled 5593 patients and 3654 controls, particularly those with ADHD and reading disorder. Altemeier, Abbott, and Berninger, (2008) examined the relations among three EF measures (i.e. Delis–Kaplan Executive Function System Inhibition and Inhibition/
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Switching, Process Assessment of the Learner Rapid Automatic Switching) and the development of spelling and written expression. They found that as children matured from first grade to fifth grade their processing time decreased on EF tasks that required inhibition and switching. Furthermore, their results suggested that intact inhibition and rapid automatic switching capabilities contributed to spelling and written expression performance in a positive fashion. These investigators suggested that EF may contribute differently to spelling and written expression, such that lower- level EF (e.g. inhibition, set shifting) may support word-level skills, such as spelling, while higher-level EF (e.g. planning) may support text-level writing. Given the aforementioned findings pertaining to inhibitory control and ADHD, it should come as no surprise that learning problems—including writing difficulties— can be associated with these difficulties (Mayes & Calhoun, 2007). A logical connection would be knowing that children with ADHD have a deficit in this area, they have the potential to struggle in reading and writing for a couple reasons, not the least of which is their overall poor regulatory control (see Filipe, Chapter 7). An inability to attend to the reading prompt, stay on topic when writing, and even the ability to sustain focus to complete the task could be due to their distractibility and by responding to signals in their environment either too quickly or too slowly. One might imagine that children experiencing difficulties in their inhibitory control would show a high rate of misspellings in their writing, demonstrate frequent letter and word omissions in their written output, produce disorganized writing products from sentence construction to paragraph organization, and manifest poor and inconsistent attendance to issues such as genre demands and audience. Despite these logical suppositions, however, Hooper, Swartz, Wakely, de Kruif, and Montgomery (2002) did not show a significant difference between good and poor fourth and fifth grade writers on the inhibition component of EF.
Cognitive Flexibility Written expression comprises a complex set of skills whose increasingly recursive nature requires a great demand on the switching of attention efficiently and frequently between planning, monitoring, sentence generation, evaluation, and revision (Alevriadou & Giaouri, 2015). One element of EF that assists in this manner is set shifting, or cognitive flexibility. Cognitive flexibility is a critical component of EF that allows us to adapt quickly and in a flexible manner to differing mental sets, thoughts, or attention in order to process or respond effectively to changing situations within our environment (Drijbooms, Groen, & Verhoeven, 2015; Rende, 2000). It also incorporates problem-solving efficiency and self-monitoring throughout task demands (Altemeier, Jones, Abbott, & Berninger, 2006). Cognitive flexibility, in general, has been shown to be inversely correlated with age (Wecker, Kramer, Hallam, & Delis, 2005), and significantly correlated with education (Tombaugh, 2004; Blair, 2006). Throughout development and especially during the
146 6. Executive Functions and Writing Skills preschool years (ages 3–5), cognitive flexibility and other components of EF are quite malleable (Welsh et al., 2010). In a study with children aged 9 to 12, van der Sluis, de Jong, and van der Leij (2007) showed that cognitive flexibility significantly related to non-verbal reasoning and reading, which demonstrated the wide range of domains in which this EF component is important. Although the relative contribution of EF to writing continues to be unpacked, it is evident that cognitive flexibility is important to writing (Drijbooms, Groen, & Verhoeven, 2017). For instance, while writing a sentence, cognitive flexibility permits recursive movement between lower (e.g. identifying the component letters in individual words) and higher levels of processing (e.g. maintaining the surface form of the planned sentence and identifying the new word in the sequence) (St. Clair-Thompson & Gathercole, 2006). During the process of translating ideas into written language, cognitive flexibility also allows an individual to switch between various subprocesses and knowledge (Drijbooms, Groen, & Verhoeven, 2017; Quinlan, Loncke, Leijten, & Van Waes, 2012). Additionally, it permits moving within levels of complexity, such as shifting between different concepts in global text (i.e. macrostructure) or facilitate lexicon selection and sentence construction (i.e. microstructure) (Aran-Filippetti & Richaud, 2015; Drijbooms, Groen, & Verhoeven, 2015; Puranik, Lombardino, & Altmann, 2008; Vadnais, 2018; Wagner et al., 2011). In a seminal study, Hooper et al. (2002) examined EFs of 55 elementary school- aged children with and without difficulties in written expression. Using the Wisconsin Card Sorting Task (WCST; Heaton et al., 1993) to measure children’s cognitive flexibility, findings revealed statistically significant differences between the groups. Specifically, children with writing difficulties had poorer cognitive flexibility than their counterparts, although the effect size was relatively small. In a more recent study, Balioussis, Johnson, and Pascual-Leone (2012) examined the extent to which measures of shifting, updating, and mental capacity correlated with writing scores as measured by writing fluency (number of words) and writing complexity (number of complex T-units) across persuasive and narrative writing genres. As expected, fluency and complexity of writing increased with age in the narrative genre, but only fluency increased in the persuasive genre. More specifically, cognitive flexibility was a significant positive predictor of fluency and complexity of writing across both genres. Expressive vocabulary and age accounted for additional significant variance beyond the EF measures in the narrative genre, but not for the persuasive genre, suggesting that individual differences in children’s persuasive writing are more attributable to EF such as cognitive flexibility (Balioussis, Johnson, & Pascual-Leone, 2012; Vadnais, 2018). Additionally, Balioussis et al. (2012) noted that cognitive flexibility also may constrain children’s writing performance, particularly if cognitive rigidity is present, and this construct may prove to be important in its impact across development and with different populations (e.g. learning disabilities, ADHD, etc.). It is important to note that the contributions of cognitive flexibility also might vary across different aspects of writing. Altemeier, Jones, Abbott, and Berninger (2006) found that basic EF for developing reading-writing connections in third and fifth
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graders contributed uniquely to writing—depending on the specific reading-writing task. These investigators found cognitive flexibility to be a strong predictor of a report-writing task. Cognitive flexibility also explained the variance in spelling and written expression in children in third, fourth, and fifth grades (Altemeier, Abbott, & Berninger, 2008). Despite the aforementioned findings, at present it is unclear how basic EF, such as inhibition and cognitive flexibility, contribute to written expression due to poor linear progression across development. Thus, basic EF like cognitive flexibility may support word-level processing, whereas complex EF may predict text-level processing (Drijbooms, Groen, & Verhoeven, 2015). As a caveat, however, it is important to note that cognitive flexibility is not easily dissociable from inhibition in very young children (Hughes, Ensor, Wilson, & Graham, 2009), and may emerge as a more separate component of EF later in development (Drijbooms, Groen, & Verhoeven, 2015).
Working Memory Perhaps of all of the EF, the relations between working memory and writing skills has been researched the most, particularly with adults (Kellogg, 1999). While the debate as to when working memory begins to assert its influence on written expression is ongoing, owing to definitional as well as measurement challenges, most researchers agree that working memory it is an essential part of learning to read and write for young children. At present, studies of working memory and writing have spanned the age range of young children and adolescents, and even have included different languages. Decker et al. (2016) examined a large sample of elementary school children in first through fourth grade to parse out how working memory factored into a child’s ability to organize their thoughts and language abilities. In their cross-sectional study, the processes that were significant varied across grade levels with the exception of letter- word identification, which was a consistent contributor in first through fourth grade. One particular working memory task, repeating numbers in a reverse order, was significant only in fourth grade. This finding was consistent with the notion that the skills needed for young learners to write varies as their skill level changes. Berninger, Abbott, Swanson, et al. (2010) also examined working memory in elementary school age students. Looking at two different types of working memory, word-level and level, they found that word-level working memory played a factor at all grades (second, fourth, and sixth) they assessed for handwriting and spelling, supporting the importance of working memory for the development of writing during most of elementary school starting at least as early as second grade. Also noting the importance of working memory in the development of writing, Kim and Schatschneider (2017) had a narrower focus (first grade students) and hypothesized working memory to be essential from the beginning stages of learning to write. Using a listening span task, findings showed the importance of working
148 6. Executive Functions and Writing Skills memory to writing for young learners, particularly during the early stages of learning to write, because of the strong connections to vocabulary, grammar, spelling, handwriting as well as theory of mind. Interestingly, working memory also showed signs of when its impact would be of lesser importance for those young learners. Once all cognitive and language skills were controlled for, working memory did not have as great of an impact on writing skill success, but the overall effect was still moderate to large in magnitude. Core components of early literacy, phonological awareness, letter-name knowledge, vocabulary, and non-word and word spelling are related to EFs. Biname and Poncelet (2016) worked with kindergarten students across a three-year timeframe to assess the aforementioned skills at varying timepoints to understand how working memory played a factor in their development. Working memory was found to predict word and non-word spelling in both first and second grades (Biname & Poncelet, 2016).
Planning EF theorists describe planning as a strategic plan of action sequences (Welsh & Pennington, 1988) and/or as problem-solving strategies (Zelazo, Carter, Reznick, & Frye 1997). Writing theorists, however, use the term in a more specific fashion and describe planning in the context of students generating and organizing their ideas. For instance, in their seminal cognitive process theory of writing, Flower and Hayes (1981) described planning as the act of building an internal representation of the knowledge the writer will utilize when producing text. This process includes generating ideas, organizing, and goal-setting, with expansion of these ideas in the most recent iteration of this model (Hayes, 2012). Planning, along with the writing processes of transcribing and revising, relies heavily on the writer’s skills in meeting the organizational, adaptive, and attentional requirements necessary to produce skilfully written text (Graham, Harris, & Olinghouse, 2007). From a problem-solving perspective, writing skills can be divided into two skill sets: low-level (i.e. basic) and high-level (i.e. complex). Low-level or basic skills, such as handwriting, spelling, and basic sentence structure, develop in the early stages of writing and are the greatest predictors of writing quality in grades 1–3 (Berninger et al., 1992). Planning, translation (e.g. sentence construction), and revision are high- level, more complex skills that begin to develop in late elementary school, and then continue into adulthood. These more complex skills are indicative of writing success in early adolescence and beyond (Limpo, Alves, & Fidalgo, 2014). In their study of 419 native Portuguese speakers in grades 4 through 9, Limpo, Alves, and Fidalgo (2014) found that the planning and revising skills of children increased; however, the variance in more complex, high-level writing skills only explained the quality of written text for children in grades 7 through 9, and less so for
Associations and Dissociations of EF and Written Expression 149
those in grades 4 through 6. These findings are supported by developmental studies of EF which show an increase in planning and problem solving through adolescence (Anderson et al., 2001). As well as neurological evidence which points to an increase in the development of myelin (i.e. white matter) and related neurological connections in the frontal lobe roughly during that developmental time frame which purportedly supports the development of planning and problem-solving skills (Huttenlocher & Dabholkar, 1997; Klinberg et al., 1999; Thatcher, 1991). As children progress through school, and writing tasks become more demanding, the ability to employ more complex skills is critical to their writing success (Graham, Harris, & Olinghouse, 2007; Limpo, Alves, & Fidalgo, 2014; Wong, Butler, Ficzere, & Kuperis, 1996). To this end, researchers have developed interventions geared toward developing the high-level skills, including planning, of struggling writers. Graham, McKeown, Kiuhara, and Harris (2012) conducted a meta-analysis of 13 writing interventions that remediated a range of elementary (grades 1–6) students’ writing skills including explicit instruction in writing strategies and text structure; scaffolding instruction through prewriting activities, goal-setting, peer assistance or direct assessment; and instructional programmes that incorporated the development of a variety of planning and problem-solving skills into writing instruction. Of these, instruction in strategies, prewriting, and goal-setting, as well as programmes using peer assistance, were the most effective in improving the overall quality of children’s writing—all strategies which are related to planning and problem solving. Relatedly, problem-solving approaches to writing intervention, such as the Self-Regulated Strategy Development (SRSD) model (Harris & Graham, 1996), also have demonstrated significant empirical strength as evidence-based interventions due, in part, to their inclusion of ‘analysis, decision making and planning, execution and coordination of mental and affective resources, attentional control, and flexible adaptation’ (Graham, Harris, & Olinghouse, 2007). These findings further support the importance of the relations between writing and problem solving and planning, particularly for struggling writers (Graham, McKeown, Kiuhara, & Harris, 2012).
Associations and Dissociations of EF and Written Expression As evidenced in the earlier overview of studies examining EF and writing skills, there is significant amount of evidence implicating the importance of various EF skills for written output. Thus, it is important to begin to understand the EF which are specifically associated with writing and which ones are less related or dissociated. Further, it is important to understand not only which EF are associated and dissociated with written expression, but also via an even more challenging scientific question, when these relations are prominent in their appearance and impact.
150 6. Executive Functions and Writing Skills
Associations Figure 6.1 depicts the numerous associations asserted for EF and written expression (i.e. intact EF, intact writing; impaired EF, impaired writing). Specifically, there appears to be a linear relation between the integrity of the various EF and the quality of the writing skills. All of the individual EF, as well as executive function as a single construct, appear to show the pattern of poorer EF skills leading to poorer writing skills and more intact or advanced EF skills leading to better writing skills. This linear relation appears to hold for both lower-level writing skills as well as higher-order, more complex writing skills. There also appears to be a developmental gradient across the various studies with the various writing skills progressing in tandem with the different executive function components, although how the various components of written language and EF interact over the course of development remains unknown. What is apparent, though, is that as EF skills evolve and become more complex, the capabilities of children and adolescents to produce more sophisticated written text increases. It is suspected that children with intact EF are more available to receive and manage writing instruction (and all instruction), and their overall regulatory functions permit increased efficiency and coordination of the various EF components and the increasing complexities of written expression. Studies have shown that intact inhibitory control, cognitive flexibility, working memory, and planning tend to be associated with good writers whereas the converse tends to be true; i.e. the presence of executive dysfunction or EF deficits are associated with poor writers (Hooper et al.,
Executive Functions
Written Expression
Intact
Intact
Impaired
Inhibitory Control Cognitive Flexibility Working Memory Planning EF as a single construct
No Studies Available. Probably most prevalent where writing instruction is poor/absent.
No Studies Available.
Impaired
Probably present in children having strong instruction and remediation and effective treatment of executive dysfunction(s) is in place.
Inhibitory Control Cognitive Flexibility Working Memory Planning EF as a single construct
Figure 6.1 Associations and dissociations between written expression and executive functions (data from: Altemeier et al., 2008; Balioussis et al., 2012; Berninger et al., 1992; Berninger et al., 2010; Biname & Poncelet, 2016; Decker et al., 2016; Drijbooms et al., 2017; Graham et al., 2007; Hooper et al., 2002; Kim & Schatschneider, 2017; Limpo et al., 2014; Quinlan et al., 2012; St. Claire-Thomas & Gathercole, 2006).
Associations and Dissociations of EF and Written Expression 151
2002). The increased efficiency and coordination of EF also may contribute to individuals having more cognitive resources to devote to the writing process whereas EF inefficiencies likely require more cognitive resources, thus leaving fewer resources to devote to the demands of the writing task. Figure 6.1 depicts these suspected associations of EF and writing skills.
Dissociations As can be seen in Figure 6.1, the number of dissociations (i.e. intact EF, impaired writing; impaired EF, intact writing) is less apparent. In part, this is likely due to the researchers not being able to publish results that are found to be not statistically significant as well as to the few studies that have compared and contrasted different EF components. Here, it is important to note that even when various executive functions were included within a study of written expression, there tended to be the observation noted earlier with respect to higher and lower EF being associated with better and worse written expression skills, respectively. In only the Hooper et al. (2006) study did one EF, inhibitory control, not separate good versus poor writers, and even in that study there was the interpretative limitation of a restricted age range (i.e. fourth and fifth grade students). It is entirely feasible, though, for a child or adolescent to have relatively intact executive capabilities, but manifest poor written expression. There may be a variety of reasons for this dissociation, with one likely variable being the lack of quality instruction to improve writing skills. Similarly, it also could be possible for a child or adolescent to have impaired EF and demonstrated intact written expression. We acknowledge that this dissociation is less likely to occur; but, depending on the severity and type of the EF, and the availability of strong instruction or remediation programmes in written language, we imagine that intact writing skills could emerge. Further, should the EF deficits be related to inhibitory control, perhaps secondary to attention dysregulation (e.g. ADHD), then a positive response to pharmacological intervention also may allow the student to be more available for instruction in written language (and other academic skills as well). These dissociations allow for the possibility of interesting case studies in the classroom as well as for study of the possible bidirectional relationship(s) between EF and writing (e.g. if you improve one skill set, does this lead to improvement in the other?).
Associations, Dissociations, Development, and Related Factors Complicating the issue of associations and dissociations between EF and written expression is the question of how these various components interdigitate over the course of development. From the developmental literature noted earlier, it does seem that there is increasing complexity in the various EF skills over time, along with the
152 6. Executive Functions and Writing Skills increased capabilities in literacy, and written expression in particular. However, the field has not yet demonstrated how these areas intertwine and affect one another. To date, a number of cross-sectional studies have provided important information pertaining to the associations of EF with written expression, including studies that have examined various facets of EF and writing across childhood and early adolescence (Berninger et al., 2010; Decker et al., 2016; Hooper et al., 2011; Limpo, Alves, & Fidalgo, 2014); but how one or more EF influence the development of the various writing skills and the subsequent complexity has not been fully explored. In one of the few studies directly examining these relations over time, Costa, Greene, and Hooper (2020) used cutting edge statistical techniques to examine writing development and provided one of the first longitudinal examinations of both written language and EF in elementary aged children. They found no evidence to support within-person (i.e. intraindividual) effects between written language and EF, suggesting that EF did not predict written language scores across time; conversely, nor did written language predict EF scores across time. The findings from this preliminary study did reveal statistically significant positive relationships between the written language intercept and written language slope as well as written language intercept and EF intercept. In short, these results imply that there may be some support for between-person effects between written language and EF, and suggested that individual variability in written language at grade 1 positively relates to the individual variability in rate of change over time of written language and the individual variability in EF at grade 1. While the study by Costa et al. (2020) is innovative in its efforts, the findings were far from satisfying. Conceptually, given the empirical findings to date pertaining to the associations of EF and written expression, it makes sense that the development of the various EF will have both direct and indirect effects on the development of writing skills, and this does not yet take into account a plethora of other potential contributors to these relationships. As seen in Figure 6.2, there is a deluge of the evolving skills for
Construct
Developmental Levels Birth to 2
3 to 5
6 to 12
13 and older
Inhibitory Control Cognitive Flexibility Working Memory Planning Emergent Literacy Handwriting Spelling Written Expression
Figure 6.2 Hypothesized developmental associations between the development of basic executive functions and the development of basic writing components across developmental levels (data from: Andersen, 2002; Berninger et al., 2006; Best & Miller, 2010; Costa et al., 2020; Decker et al., 2016; Denckla, 2007; Welsh & Pennington, 1988; Zelazo et al., 2010; Zins & Hooper, 2012).
Conclusions and Directions 153
both domains, and this does not take into account any acceleration or delays in the various skills over time, or other factors that could influence the development of these functions. Further, how impairment in EF might affect the development of writing, both simple and complex forms of written expression, remains unknown; however, the available studies do suggest that a negative effect is likely given the apparent linear relation of the development of both skill sets. It is important to note that we have spent the bulk of our time focusing on the relation of EF and written expression, but as alluded to earlier, there are a host of other variables that could affect the developmental unfolding shown in Figure 6.2. In addition to the developmental complexity inherent in both EF and writing, both intrinsic factors (e.g. IQ, language problems, ADHD, learning disabilities, affective and behavioural difficulties) and extrinsic factors (e.g. poverty—which is a known predictor of executive dysfunction [Raver, Blair, & Willoughby, 2013], family literacy, educational experiences, amount, and quality of writing instruction) all can affect both of these domains in relatively unknown ways. Further, it is not known if the impact of these factors might have a bigger impact on EF and writing at different developmental periods. For example, might such skills be more vulnerable to developmental disruption with early exposure versus later exposure (Willoughby et al., 2017)? Would intervention at targeted developmental periods work more effectively and efficiently? This exploration of the dynamic relationships between the development and EF and writing truly is in its infancy.
Conclusions and Directions Our understanding of the relations between EF and written expression has made significant gains over the past 25 to 30 years. Our understanding of both areas has improved immensely, with important discoveries pertaining to the various aspects of writing and EF. Nonetheless, the ways in which these two constructs interact largely remains in the early stages of scientific inquiry, at best, and there is much work needed to advance this aspect of written language. The available findings to date are clear, though, as there appears to be not only a positive association between EF and written language, but also a ‘dose-related’ effect, as higher EF skills tend to be associated with higher writing skills and worse EF tend to lead to poorer written expression. In addition to reviewing some of literature conducted to date across targeted components of EF (i.e. inhibitory control, cognitive flexibility, working memory, planning), this chapter has addressed what we know about the various associations and dissociations between these two domains. Indeed, it appears that nearly every EF discussed has some positive association with written expression, and these findings range from the preschool years through adolescence. Consequently, the available findings are clear in indicating a positive relationship between EF and written language production, with a strong
154 6. Executive Functions and Writing Skills supposition that there is a linkage between executive function development and writing development as well. Whether the dissociations discussed in this chapter manifest (i.e. intact EF and poor writing; poor EF and intact writing) remains to be seen. Further, few researchers have been able to study EF and written language together in longitudinal models wherein the specific nuances of this relationship could be revealed, with perhaps a bidirectional relationship being uncovered. The one study conducted to date (Costa, Greene, & Hooper, 2020) showed some promise in this regard, and subsequent studies should follow suit. While the importance of conducting such a study is recognized, the practicality of doing such studies is daunting, particularly given the host of other intrinsic and extrinsic variables that would need to be taken into account to reveal the interplay between EF and written expression. Such longitudinal data will be important in further conceptualizing instructional programmes across the age span, particularly for learners who may have difficulties with written expression (Graham, Harris, & Hebert, 2011). Additionally, the influence of written language on EF is another interesting relationship, but this conceptualization has received relatively little empirical support to date. Graham (1997) and colleagues (De La Paz, Swanson, & Graham, 1998) investigated executive control and revising, where the researchers taught students a procedure for revising. The procedure provided the students with a systematic approach to revising that specifically aided in executive control (i.e. self-regulation). When the students used the revising procedures, they had fewer difficulties with revising, and their essays improved as compared to when they used their typical revising procedures. While there is not yet any available empirical research on the influence of writing on EFs, it seems plausible that improvements in written language skills could have a positive effect upon how students engage their EFs, and studies allowing for the mediating effects of writing on EF development remain of scientific interest. Going forward with the solid evidence-base to date, and perhaps learning from the early exploits of those studying reading, cross-sectional studies will only take the field so far, particularly with respect to the potential bidirectional influence of these two constructs. The need for more sophisticated longitudinal studies with well validated models of both EF and writing, strong associated measurements, carefully selected covariates (e.g. instruction), and of course sample sizes large enough to have the power to explore the various associations of EF and writing within a particular time frame, using one area at a single time point to predict the status of the other at another time point (i.e. lagged models), and the developmental trajectories simultaneous being tracked over the course of time. Even conducting such a study within the confines of a developmental range or employing cohort-sequential types of models would serve to move the field forward, thus explaining the interplay between EF and writing within a large age range. This latter approach may be important given the age- appropriateness of different types of genres. In this chapter, we described the available literature in EF and its association with written expression. We reviewed models of EF and detailed key empirical findings
References 155
pertaining to inhibitory control, cognitive flexibility, working memory, and planning and their contribution to writing. As a complement to many of the chapters in this text, we have endeavoured to explore the associations and dissociations between EF and written expression, and have further attempted to place these relationships within a developmental context. While the field of cognitive science has moved our understanding of EF and written expression forward, there is still much work needed to increase our understanding of these various relationships. Uncovering these relationships should serve to provide additional avenues for understanding how children learn to write, the influence of EFs on writing development at different developmental time points, and offer new directions for evidence-based interventions and general classroom instruction for developing and improving writing skills in children and adolescence.
References Alevriadou, A., & Giaouri, S. (2015). The impact of executive functions on the written language process: some evidence from children with writing disabilities. Journal of Psychologists and Counsellors in Schools, 25(1), 24–37. Allan, N.P., & Lonigan, C.J. (2011). Examining the dimensionality of effortful control in preschool children and its relation to academic and socioemotional indicators. Developmental Psychology, 47, 905–15. Altemeier, L., Jones, J., Abbott, R.D., & Berninger, V.W. (2006). Executive functions in becoming writing readers and reading writers: note taking and report writing in third and fifth graders. Developmental Neuropsychology, 29(1), 161–73. Altemeier, L.E., Abbott, R.D., Berninger, V.W. (2008). Executive functions for reading and writing in typical literacy development and dyslexia. Journal of Clinical and Experimental Neuropsychology, 30(5), 588–606. Anderson, P. (2002). Assessment and development of executive function during childhood. Child Neuropsychology, 8(2), 71–82. Anderson, V., Anderson, P., Northam, E., Jacobs, R., & Catroppa, C. (2001). Development of executive functions through late childhood and adolescence in an Australian sample. Developmental Neuropsychology, 20, 385–406. Aran-Filippetti, V., & Richaud, M.C. (2015). Do executive functions predict written composition?: Effects beyond age, verbal intelligence, and reading comprehension. Acta Neuropsychologica, 13(4), 331–49. Baddeley, A.D., & Larsen, J. (2007). The phonological loop: some answers and some questions. The Quarterly Journal of Experimental Psychology, 60(4), 512–18. Balioussis, C., Johnson, J., & Pascual-Leone, J. (2012). Fluency and complexity in children’s writing: the role of mental attention and executive function. Rivista di Psicolinguistica Applicata/Journal of Applied Psycholinguistics: Special Issue, XII, 3, 33–45. Barkley, R.A. (2001). The executive functions and self-regulation. An evolutionary neuropsychological perspective. Neuropsychology Review, 11, 1–29. Berninger, V., Abbott, R., Swanson, H.L., Lovitt, D., Trivedi, P., Lin, S., . . . & Amtmann, D. (2010). Relationship of word-and sentence-level working memory to reading and writing in second, fourth, and sixth grade. Language, Speech, and Hearing Services in Schools, 41, 179–93.
156 6. Executive Functions and Writing Skills Berninger, V., & Winn, W. (2006). Implications of advancements in brain research and technology for writing development, writing instruction, and educational evolution. In C. MacArthur, S. Graham, & J. Fitzgerald (Eds.), Handbook of Writing Research (pp. 96–114). New York, NY: The Guilford Press. Berninger, V., Yates, C., Cartwright, A., Rutberg, J., Remy, E., & Abbott, R. (1992). Lower- level developmental skills in beginning writing. Reading and Writing: An Interdisciplinary Journal, 4, 257–80. Best, J.R., & Miller, P.H. (2010). A developmental perspective on executive function. Child Development, 81, 1641–60. Biname, F., & Poncelet, M. (2016). Order short term memory capacity predicts nonword reading and spelling in first and second grade. Reading and Writing: An Interdisciplinary Journal, 29(1), 1–20. Blair, C. (2006). How similar are fluid cognition and general intelligence? A developmental neuroscience perspective on fluid cognition as an aspect of human cognitive ability. Behavioral and Brain Sciences, 29(2), 109–25. Carlson, S.M., Moses, L.J., & Claxton, L.J. (2004). Individual differences in executive functioning and theory of mind: an investigation of inhibitory control and planning ability. Journal of Experimental Child Psychology, 87, 299–319. Costa, L.-J.C., Greene, J.A., & Hooper, S.R. (2020). The relations among the development of written language and executive functions for children in elementary school. In Talinn, P. (Ed.). Writing Across the Lifespan (pp. 159–75). Anderson, SC: Parlor Press. Cowan, N. (2005). Working Memory Capacity: Essays in Cognitive Psychology. New York, NY: Psychology Press. Daigneault, S., Braun, C.M.J., & Whitaker, H.A. (1992). Early effects of normal aging on perseverative and non-perseverative prefrontal measures. Developmental Neuropsychology, 8, 99–114. De La Paz, S., Swanson, P.N., & Graham, S. (1998). The contribution of executive control to the revising by students with writing and learning difficulties. Journal of Educational Psychology, 90(3), 448–60. Decker, S.L., Roberts, A.M., Roberts, K.L., Stafford, A.L., & Eckert, M.A. (2016). Cognitive components of developmental writing skill. Psychology in the Schools, 53(6), 617–25. Denckla, M.B. (1996). A theory and model of executive function. In G.R. Lyon & N.A. Krasegor (Eds.). Attention, Memory and Executive Function (pp. 263–78). Baltimore, MD: Brookes. Denckla, M.B. (2007). Executive function. In L. Meltzer (Ed.). Executive Function in Education: From Theory to Practice (pp. 5–18). New York, NY: Guilford Press. Drijbooms, E., Groen, M.A., & Verhoeven, L. (2015). The contribution of executive functions to narrative writing in fourth grade children. Reading and Writing, 28(7), 989–1011. Drijbooms, E., Groen, M.A., & Verhoeven, L. (2017). How executive functions predict development in syntactic complexity of narrative writing in the upper elementary grades. Reading and Writing, 30, 209–31. Espy, K.A., McDiarmid, M.M., Cwik, M.F., Stalets, M.M., Hamby, A., & Senn, T.E. (2004). The contribution of executive functions to emergent mathematic skills in preschool children. Developmental Neuropsychology, 26, 465–86. Flower, L., & Hayes, J.R., (1981). A cognitive process theory of writing. College Composition and Communication, 32(4), 365–87. Friedman, N.P., & Miyake, A. (2017). Uniuty and diversity of executive functions: Individual differences as a window on cognitive structure. Cortex, 86, 186–204. Friedman, N.P., Miyake, A., Young, S.E., DeFries, J.C., Corley, R.P., & Hewitt, J.K. (2008). Individual differences in executive functions are almost entirely genetic in origin. Journal of Experimental Psychology: General, 137(2), 201–25.
References 157 Frye, D., Zelazo, P., & Burack, J.A. (1998). Cognitive complexity and control: implications for theory of mind in typical and atypical development. Current Directions in Psychological Science, 7(4), 116–21. Garon, N., Byrson, S.E, & Smith, I.M. (2008). Executive function in preschoolers: a review using an integrative framework. Psychological Bulletin, 134, 31–60. Graham, S. (1997). Executive control in the revising of students with learning and writing difficulties. Journal of Educational Psychology, 89(2), 223–34. Graham, S., Harris, K., & Hebert, M. (2011). Informing Writing: The Benefits of Formative Assessment. Washington, DC: Alliance for Excellent Education. Graham, S., Harris, K.R., & Olinghouse, N. (2007). Addressing executive function difficulties in writing: an example from the Self-Regulated Strategy Development model. In L. Meltzer (Ed.). Executive Functioning in Education: From Theory to Practice (pp. 216–36). New York, NY: Guilford Graham, S., McKeown, D., Kiuhara, S., & Harris, K.R. (2012). A meta-analysis of writing instruction for students in the elementary grades. Journal of Educational Psychology, 104(4), 879–96. Harris, K.R., & Graham, S. (1996). Making the Writing Process Work: Strategies for Composition and Self-Regulation (2nd Ed.). Cambridge, MA: Brookline Books. Hayes, J.R. (2012). My past and present as writing researcher and thoughts about the future of writing research. In V.W. Berninger (Ed.). Past, Present, and Future Contributions of Cognitive Writing Research to Cognitive Psychology (pp. 3– 26). New York, NY: Psychology Press. Heaton, R.K., Chelune, G.J., Talley, J.L., Kay, G.G., & Curtiss, G. (1993). Wisconsin Card Sorting Test (WCST): Manual: Revised and Expanded. Odessa, FL: Psychological Assessment Resources. Hooper, S.R., Costa, L.J., McBee, M., Anderson, K.L., Yerby, D.C., Knuth, S.B., & Childress, A. (2011). Concurrent and longitudinal neuropsychological contributors to written language expression in first and second grade students. Reading and Writing, 24(2), 221–52. Hooper, S.R., Costa, L.C., Green, M.B., Catlett, S.R., Barker, A., Fernandez, E., & Faldowski, R. (2020). The relationship of teacher ratings of executive functions to emergent literacy in Head Start. Reading and Writing: An Interdisciplinary Journal, 33(4), 963–89. Hooper, S.R., Swartz, C.W., Wakely, M.B., de Kruif, R.E., & Montgomery, J.W. (2002). Executive functions in elementary school children with and without problems in written expression. Journal of Learning Disabilities, 35(1), 57–68. Hooper, S., Wakely, M., de Kruif, R., & Swartz, C. (2006). Aptitude-treatment interactions revisited: Effect of metacognitive intervention on subtypes of written expression in elementary school students. Developmental Neuropsychology, 29(1), 217–41. Hughes, C., Ensor, R., Wilson, A., & Graham, A. (2009). Tracking executive function across the transition to school: a latent variable approach. Developmental Neuropsychology, 35(1), 20–36. Huttenlocher, P., & Dabholkar, A. (1997). Developmental anatomy of prefrontal cortex. In N. Krasnegor, G. Reid Lyon, & P. Goldman-Rakic (Eds.). Development of the Prefrontal Cortex: Evolution, Neurobiology, and Behavior (pp. 69–84). Baltimore, MD: Brookes. Kellogg, R.T. (1999). The Psychology of Writing. New York, NY: Oxford University Press, Kim, Y.-S., & Schatschneider, C. (2017). Expanding the developmental models of writing: a direct and indirect effects model of developmental writing (DIEW). Journal of Educational Psychology, 109(1), 35–50. Klinberg, T., Vaidya, C., Gabrieli, J., Moseley, M., & Hedehus, M. (1999). Myelination and organization of the frontal white matter in children: a diffusion tensor study. NeuroReport, 10, 2817–21.
158 6. Executive Functions and Writing Skills Limpo, T., Alves, R.A., & Fidalgo, R. (2014). Children’s high-level writing skills: development of planning and revising and their contribution to writing quality. British Journal of Educational Psychology, 84, 177–93. Lipszyc, J., & Schachar, R. (2010). Inhibitory control and psychopathology: a meta-analysis of studies using stop signal task. Journal of the International Neuropsychological Society, 16(6), 1064–76. Mayes, S., & Calhoun, S. (2007). Learning, attention, writing, and processing speed in typical children and children with ADHD, autism, anxiety, depression and oppositional defiant disorder. Child Neuropsychology, 3, 469–93. Miyake, A., Friedman, N.P., Emerson, M.J., Witzki, A.H., Howerter, A., & Wager, T.D. (2000). The unity and diversity of executive functions and their contributions to complex ‘frontal lobe’ tasks: a latent variable analysis. Cognitive Psychology, 41, 49–100. Oosterlaan, J., Logan, G.D., & Sergeant, J.A. (1998). Response inhibition in AD/HD, CD, comorbid AD/HDCCD, anxious, and control children: a meta-analysis of studies with the stop task. Journal of Child Psychology and Psychiatry, (39), 411–25. Pennington, B.F., Bennetto, L., McAleer, O., & Roberts, R.J. (1996). Executive functions and working memory: theoretical and measurement issues. In G.R. Lyon, & N.A. Krasnegor (Eds.). Attention, Memory, and Executive Function (pp. 327–48). Baltimore, MD: Brookes. Pennington, B.F., & Ozonoff, S. (1996). Executive functions and developmental psychopathology. Journal of Child Psychology, 37(1), 51–87. Puranik, C.S., Lombardino, L.J., & Altmann, L.J.P. (2008). Assessing the microstructure of written language using a retelling paradigm. American Journal of Speech-Language Pathology, 17, 107–20. Quinlan, T., Loncke, M., Leijten, M., & Van Waes, L. (2012). Coordinating the cognitive processes of writing: the role of the monitor. Written Communication, 29(3), 345–68. Raver, C.C., Blair, C., & Willoughby, M. (2013). Poverty as a predictor of 4-year-olds’ executive function: new perspectives on models of differential susceptibility. Developmental Psychology, 49(2), 292–304. Rende, B. (2000). Cognitive flexibility: theory, assessment, and treatment. Seminars in Speech and Language, 21(2,), 121–53. Roberts, R.J., & Pennington, B.F. (1996). An interactive framework for examining prefrontal cognitive processes. Developmental Neuropsychology, 12(1), 105–26. Schacher, R., & Logan, G.D. (1990). Impulsivity and inhibitory control in normal development and childhood psychopathology. Developmental Psychology, 26, 710–20. Schacher, R., Tannock, R., Marriott, M., & Logan, G. (1995). Deficient inhibitory control in attention deficit hyperactivity disorder. Journal of Abnormal Child Psychology, 23, 411–37. Schacher, R., Mota, V., Logan, G.D., Tannock, R., & Klim, P. (1999). Confirmation of an inhibitory control deficit in attention-deficit/hyperactivity disorder. Journal of Abnormal Child Psychology, 28(3), 227–35. St. Clair-Thompson, H.L., & Gathercole, S.E. (2006). Executive functions and achievements in school: shifting, updating, inhibition, and working memory. The Quarterly Journal of Experimental Psychology, 59(4), 745–59. Stuss, D.T., & Benson, D.S. (1984). Neuropsychological studies of the frontal lobes. Psychological Bulletin, 95, 3–28. Thatcher, R.W. (1991). Maturation of the human frontal lobes: physiological evidence for staging. Developmental Neuropsychology, 7, 397–419. Tombaugh, T.N. (2004). Trail Making Test A and B: normative data stratified by age and education. Archives of Clinical Neuropsychology, 19(2), 203–14. Vadnais, S.A. (2018). Executive Functioning as a Predictor of College Student Writing Ability (Doctoral dissertation, Southern Illinois University at Carbondale).
References 159 van der Sluis, S., de Jong, P.F., & van der Leij, A. (2007). Executive functioning in children, and its relations with reasoning, reading, and arithmetic. Intelligence, 35(5), 427–49.Wagner, R.K., Puranik, C.S., Foorman, B., Foster, E., Wilson, L.G., Tschinkel, E., & Kantor, P.T. (2011). Modeling the development of written language. Reading and Writing, 24(2), 203–20. Wecker, N.S., Kramer, J.H., Hallam, B.J., & Delis, D.C. (2005). Mental flexibility: age effects on switching. Neuropsychology, 19(3), 345. Welsh, J.A., Nix, R.L., Blair, C., Bierman, K.L., & Nelson, K.E. (2010). The development of cognitive skills and gains in academic school readiness for children from low-income families. Journal of Educational Psychology, 102(1), 43. Welsh, M.C., & Pennington, B.F. (1988). Assessing frontal lobe functioning in children: views from developmental psychology. Developmental Neuropsychology, 4, 199–230. Welsh, M.C., Pennington, B.F., & Grosser, D.B. (1991). A normative-developmental study of executive function: a window on prefrontal function in children. Developmental Neuropsychology, 7(2), 131–49. Willoughby, M.T., Magnus, B., Vernon-Feagans, L., Blair, C.B., & the Family Life Project Investigators (2017). Developmental delays in executive function from 3 to 5 years of age predict kindergarten academic readiness. Journal of Learning Disabilities, 50, 359–72. Wong, B.Y.L., Butler, D.L., Ficzere, S.A., & Kuperis, S. (1996). Teaching low achievers and students with learning disabilities to plan, write, and revise opinion essays. Journal of Learning Disabilities, 29, 197–212. Zelazo, P., Carter, A., Reznick, J., & Frye, D. (1997). Early development of executive function: a problem-solving framework. Review of General Psychology, 1, 198–226. Zelazo, P., & Frye, D. (1998). Cognitive complexity and control: the development of executive function. Current Directions in Psychological Science, 7(4), 121–6. Zelazo, P., Muller, U., Frye, D., & Marcovitch, S. (2003). The development of executive function in early childhood. Monographs of the Society for Research in Child Development, 68(3), 1–137. Zelazo, P.D., Qu, L., & Kesek, A. (2010). Hot executive function: emotion and the development of cognitive control. In S.D. Calkins & M.A. Bell (Eds.). Child Development at the Intersection of Emotion and Cognition (pp. 97– 111). Washington, DC: American Psychological Association. Zins, J., & Hooper, S.R. (2012). The integration of child development principles and the development of written language. In E. Grigerenko, E. Mambrino, & D. Pleiss (Eds.). Handbook of Writing. New York, NY: The Psychology Press.
7 How Do Executive Functions Issues Affect Writing in Students with Neurodevelopmental Disorders? Marisa Filipe
Introduction Those who have difficulties to learn to write are at educational and occupational disadvantage. For example, the ability to communicate in writing is essential for the school’s educational goals. Students must be able to read and spell words, know the meaning of the words and the syntax of the language, complete written exams, and write reports. Furthermore, writing is used to memorize, remember, and share knowledge (Durst & Newell, 1989). In the workplace, this skill continues to be crucial. For instance, in a survey of 120 American corporations, writing was acknowledged as a threshold skill for hiring and promoting workers (National Commission on Writing, 2004). Therefore, individuals who experience problems with writing are unlikely to fulfil their personal, academic, and occupational potential. Although writing is a key ability, several children may experience difficulties with this skill. Among the many reasons for problems with the development of writing skills (e.g. Graham & Harris, 2000; MacArthur, Graham, & Fitzgerald, 2006), a possible one is the presence of a neurodevelopmental disorder. A neurodevelopmental disorder implies an impairment in the growth and development of the central nervous system (e.g. Reynolds & Goldstein, 1999). This type of disorder involves a dynamic inter-relationship between genetic, cognitive, emotional, and behavioural factors, whose symptoms emerge in early childhood and frequently persist throughout adulthood (Bishop & Rutter, 2008). According to the Diagnostic and Statistical Manual of Mental Disorders— 5 (DSM- 5; American Psychiatric Association, 2013), neurodevelopmental disorders include the following diagnostic categories: (a) intellectual disabilities; (b) communication disorders; (c) autism spectrum disorders; (d) attention deficit and hyperactivity disorder; (e) specific learning disorders (e.g. dyslexia and dyscalculia); and (f) motor disorders (including developmental coordination and movements disorders, Tourette’s, and tic disorders). Most children diagnosed with a neurodevelopmental disorder experience problems with Marisa Filipe, How Do Executive Functions Issues Affect Writing in Students with Neurodevelopmental Disorders? In: Executive Functions and Writing. Edited by: Teresa Limpo and Thierry Olive, Oxford University Press. © Oxford University Press 2021. DOI: 10.1093/oso/9780198863564.003.0007
Introduction 161
behaviour and cognitive functions, and these difficulties impact their social, academic, and occupational functioning (American Psychiatric Association, 2013). A critical cognitive function frequently impaired in a neurodevelopmental disorder is executive functioning. This is an umbrella concept that involves several cognitive control processes responsible for guiding, directing, and managing cognitive, emotional, and behavioural functions, mainly during novel problem solving (Gioia, Isquith, Guy, & Kenworthy, 2000). According to several authors, there are three core executive functions (EF; Lehto, Juujärvi, Kooistra, & Pulkkinen, 2003, Miyake et al., 2000): (a) inhibition (i.e. ability to inhibit impulsive responses including self-control; Diamond, 2013), (b) working memory (i.e. the ability to temporally store, manipulate, and process information while performing a task; Baddeley, 2000), and (c) cognitive flexibility (i.e. ability to switch thoughts between different concepts, to think about multiple concepts simultaneously, or to adapt behaviours in response to changes in the environment; Scott, 1962). Higher-order EF are built from these three core functions, such as problem solving and planning (Collins & Koechlin, 2012; Lunt et al., 2012). Writing is a complex skill that requires a range of linguistic abilities but also implies several cognitive processes such as EF (Ardila & Surloff, 2006; Graham, 1990). This skill depends on the coordination of: (a) the formulation of words, sentences, and speech; (b) the transformation of phonological, orthographic, and morphological knowledge into text; and (c) the EF to plan, review, and revise expression (Berninger, 2009; Berninger, García, & Abbot, 2009). As EF have an impact on successful writing (e.g. Kellogg, 1996; Vanderberg & Swanson 2007), obstacles to written expression go beyond deficits in spelling, grammar, and punctuation, and EF are critical to writing skills. Different models of writing (Berninger & Winn, 2006; Hayes & Flower, 1980; Kellogg, 1996) agree that writing is a cognitive task that requires the coordinated deployment of a relevant set of cognitive abilities such as working memory (Berninger, 2011). Working memory skills are important as the text emerges since they help writers to match the text with representations in memory (St Clair-Thompson & Gathercole, 2006), select ideas, hold thoughts in mind, ignore distractions, and retrieve information from long-term memory. Along with working memory, inhibition and cognitive flexibility also play an important role in written expression. Inhibitory control allows, for instance, the inhibition of ideas that have already been covered, the suppression of inappropriate lexical representations, and the selection of the appropriate words and phrases (e.g. Kellogg et al., 2013; Olive, 2011). Cognitive flexibility is also important when thinking of different ways of writing about something, and writers must have cognitive flexibility to formulate their thoughts while writing. Writing can be frustrating and difficult for many students, especially for those with neurodevelopmental disorders (American Psychological Association, 2013). One possible reason for the close link between neurodevelopmental disorders and writing difficulties might be the role that EF play in the process required to writing expression. Research on EF in students with neurodevelopmental disorders has grown exponentially in recent years. A large body of research exists for autism spectrum disorders (Ozonoff,
162 7. Executive Functions, Writing, and Disorders Pennington, & Rogers, 1991; Pennington et al., 1997), attention deficit and hyperactivity disorder (Barkley, 1997; Brown, 2006), and specific learning disorders (e.g. Arrington et al., 2014; Gathercole, Alloway, Willis, & Adams, 2006; Toll, Van der Ven, Kroesbergen, & Van Luit, 2011). These particular neurodevelopmental disorders are the three most common disorders presenting impaired EF: 1 in 68 children have been diagnosed with autism spectrum disorder (Christensen et al., 2016), up to 1 in 15 children have a diagnosis of attention deficit and hyperactivity disorder (Willcutt, 2012), and the prevalence of specific learning disorders is 5–15% (American Psychological Association, 2013). Furthermore, although some of these disorders may share similar features of executive dysfunction, the profiles appear to differ according to the diagnostic category—that is, different disorders may have unique executive profiles (Pennington & Ozonoff, 1996). For this reason, this chapter focused on the characterization of these neurodevelopmental disorders characterized by unique EF deficits and writing difficulties.
Autism Spectrum Disorder (ASD) Interest in ASD in the past decade has increased following the dramatic increase in the prevalence published in the most recent reports (Christensen et al., 2016). Autism spectrum disorder is characterized by: (a) persistent deficits in social communication and social interaction across multiple contexts; and (b) restricted, repetitive patterns of behaviour, interests, or activities (American Psychiatric Association, 2013). Autism affects how people communicate with and relate to other people. This disorder is characterized by a wide range of variability, from low-functioning autism to high-functioning autism. Individuals who are more severely affected typically present more profound impairments and lower intellectual functioning. In comparison, individuals with high-functioning autism are characterized by higher verbal and intellectual functioning (e.g. Carpenter, Soorya, & Halpern, 2009). As a consequence, individuals with ASD vary greatly in their cognitive profile. Research at the cognitive level of analysis has been very active, perhaps because the profile of strengths and weaknesses in individuals with ASD is interesting and unusual. Individuals with this type of disorder are characterized by specific areas of expertise contrasted with areas of marked difficulty (Wing, 2006). They perform least well on intellectual tasks that require language, abstract reasoning, integration, and sequencing, and best on tasks that require visual–spatial processing, attention to detail, and memory abilities. On standard intelligence tests, such as the Wechsler scales, most studies reported higher scores for Performance Intelligence Quotient (IQ) than for Verbal IQ, with substantial variability among subtests. Block design, object assembly, and digit span subtests are often the highest scores in a cognitive profile, while comprehension is often the lowest (Dennis et al., 1999; Goldstein, Johnson, & Minshew, 2001; Lincoln, Allen, & Kilman, 1995). Research on the development of writing skills is scarce, but some studies have shown that many individuals with ASD exhibit difficulties with written expression (Finnegan
Autism Spectrum Disorder (ASD) 163
& Accardo, 2018; Mayes & Calhoun, 2003; Whitby & Mancil, 2009). Several characteristics of students with ASD may affect their ability to write. For instance, they may have sensory processing difficulties (Baranek et al., 2006) that may impact handwriting (e.g. issues with sensory awareness of fingers; Feder & Majnemer, 2007). Thus, the act of writing can be a problem for individuals with ASD. If the act of writing by hand is too challenging, learners may have problems with the development of writing skills or they may avoid writing tasks (Graham & Harris, 2006; Graham et al., 2008). Additionally, research showed that individuals with ASD had lower legibility ratings and lower spelling scores than typically developing peers, they wrote slower and fewer words than their peers (Finnegan & Accardo, 2018), and they may have difficulties in referencing (e.g. pronouns do not agree with subjects and objects resulting in ambiguity; Norbury & Bishop, 2003). Regarding sentence construction, research found mixed results: syntactical abilities of individuals with ASD have been found to be similar to their typically developing peers (Norbury & Bishop, 2003), whereas other studies suggested that sentences written by individuals with ASD lack complexity (Myles et al., 2003). EF have been considered a central deficit in ASD (e.g. Ozonoff, Pennington, & Rogers, 1991), and these executive impairments may be the major reason for the reported link between writing problems and ASD. Specifically, studies have shown that individuals with ASD may have impairments in inhibitory control and working memory (O’Hearn, Asato, Ordaz, & Luna, 2008). Still, research suggested that cognitive flexibility problems may be the most impacted EF in ASD (Corbett et al., 2009; Zandt, Prior, & Kyrios, 2009) being particularly associated with the core symptoms of this disorder (D’Cruz et al., 2013; Lopez, Lincoln, Ozonoff, & Lai, 2005). These problems with cognitive flexibility were often observed in the form of perseverative errors in this population (Hughes, Russell, & Robbins, 1994; Pascualvaca, Fantie, Papageorgiou, & Mirsky, 1998). Importantly, cognitive flexibility impairments are also closely related to developments in working memory and inhibition (Blackwell, Cepeda, & Munakata, 2009; Marcovitch, Boseovski, Knapp, & Kane, 2010; Zelazo, Muller, Frye, & Marcovitch, 2003). When executing a task requiring cognitive flexibility (such as written a text), an individual need to, first, develop a strategy for problem solving using working memory, and second, shift to a new rule/criterion while inhibiting the previously created rule/criterion (Best & Miller, 2010; Garon, Bryson, & Smith, 2008). Indeed, there is increasing evidence that improvements in cognitive flexibility are associated to developments in other EF (Blackwell, Cepeda, & Munakata, 2009; Marcovitch, Boseovski, Knapp, & Kane, 2010; Zelazo, Muller, Frye, & Marcovitch, 2003). Thus, for ASD, impaired working memory and inhibitory control might also coexist and influence cognitive flexibility development. As problems with cognitive flexibility are a hallmark characteristic of autism (D’Cruz et al., 2013; Lopez et al., 2005), individuals with ASD may experience difficulties (a) in adjusting to unexpected change, (b) with the application of different strategies, and (c) in changing performance after feedback repeating unsuccessful problem solving approaches (see also Table 7.1).
Table 7.1 Writing problems linked to impairments in executive functions (viz. cognitive flexibility, inhibition, and working memory) Students with cognitive flexibility deficits (e.g. ASD) may have difficulties with:
Students with inhibition problems (e.g. ADHD) may present difficulties with:
Students with working memory impairments (e.g. ADHD, SLD) may experience difficulties with:
• application of different strategies to implement the writing plan;
• keeping ideas in mind while writing;
• starting or completing their written text independently;
• the repetition of unsuccessful problem- solving approaches;
• maintaining focus on the • the structural complexity of ‘train of thought’ that is their written texts; important for the writing flow;
• maintain the performance • keeping in mind the big • the organization of the when complexity picture of what they want written text; increases; to communicate, while manipulating the ideas, details, words, sentences, and paragraphs; • the use feedback to apply, monitor, and adjust the writing plan;
• the revision of details and corrections;
• paying attention and concentrating during writing;
• the transition from one • the focus and attention to • fully remember what they sequence/idea to another; details making errors in are supposed to be doing spelling, grammar, and/ while writing; or punctuation; • conducting adjustments to unexpected change;
• ‘careless’ mistakes;
• the monitorization of their own performance in writing;
• proofreading and editing • the cohesion words, process; sentences, paragraphs, and/ or texts;
• writing for an audience;
• sustaining the attention • retaining new words and required for writing over remembering the vocabulary a long period of time; for the subject matter;
• hyperfocus on the details of writing without regard to the larger goal picture;
• filter distractions;
• resistance to topic/idea • organization of words generation or resistance to and meaning. accepting topics/ideas of an outside source.
• following writing instructions with two or more parts;
• retaining information for later retrieval; • ideas that are quickly forgotten.
Attention Deficit/Hyperactivity Disorder (ADHD) 165
Attention Deficit/Hyperactivity Disorder (ADHD) ADHD is a neurodevelopmental disorder characterized by significant problems with attention and/or impulsiveness and hyperactivity (American Psychological Association, 2013). Importantly, ADHD is recognized as a neurodevelopmental disorder of EF, which arise from deficits in executive functioning (e.g. Barkley, 2015; Nigg, 2006; Rapport, Chung, Shore, & Isaacs, 2001; Sonuga-Barke, 2003; Willcutt, Doyle, Nigg, Faraone, & Pennington, 2005). Individuals with ADHD, compared to typically developing peers, exhibited significant impairments in inhibitory control, working memory, and planning (Willcutt et al., 2005), as well as problems in cognitive flexibility (Geurts et al., 2005; Lawrence et al., 2004; Yáñez-Téllez et al., 2012) and sustained attention (Trani et al., 2011; Yáñez-Téllez et al., 2012). Individuals with ADHD are known to have difficulties with academic achievement including writing (Barkley, 2006). Children with ADHD have a higher probability to fail in a writing task, compared to a reading or mathematics task (Mayes & Calhoun, 2007). Indeed, individuals with ADHD have been shown to be underachievers on measures of written expression (Barry, Lyman, & Klinger, 2002; Mayes & Calhoun, 2007). For instance, Yoshimasu et al. (2011) found that the incidence of written language disorders was significantly higher for individuals with ADHD compared to typically developing peers (boys: 64.5% vs. 16.5%; girls: 57.0% vs. 9.4%). Moreover, Mayes and Calhoun (2007) showed that 65% of children with ADHD had a disorder of written expression. They also found that the best predictors of written expression difficulties were two key aspects of EF, namely, working memory and processing speed. Specifically, research has suggested that students with ADHD have handwriting difficulties (e.g. Brossard-Racine et al., 2011; Fliers et al., 2009; Shen, Lee, & Chen, 2012). Interestingly, studies considering the effect of stimulant medication (the first- line treatment for ADHD, Cortese et al., 2018) on handwriting scores showed that medication alone is not sufficient to resolve these handwriting difficulties of children with ADHD (Brossard-Racine et al., 2015; Rosenblum, Epsztein, & Josman, 2008). Furthermore, substantial evidence concerning spelling and expressive writing difficulties associated with this disorder was also found (e.g. Cornoldi et al., 2010; Re, Pedron, & Cornoldi, 2007). Children with ADHD, compared to typically developing peers, present lower scores for adequacy, structure, grammar, and vocabulary in texts (Re, Pedron, & Cornoldi, 2007). Additional studies have shown that children with ADHD commit a high number of syntactic and coherence errors, as well as using a simple structure and a very basic vocabulary (García, Rodríguez, Pacheco, & Diez, 2009). Research also suggested that, although students with ADHD may have the expected knowledge about the basic rules of writing (Re & Cornoldi, 2010), they generate less organized written texts, write less words, and make more mechanical errors (Casas, Ferrer, & Fortea, 2013; Re, Pedron, & Cornoldi, 2007; Resta & Eliot, 1994). Graham, Fishman, Reid, and Hebert (2016) conducted a recent meta-analysis comparing the writing of students with ADHD to the writing of their typically developing peers (grades 1 to 12). The authors found that students with ADHD presented
166 7. Executive Functions, Writing, and Disorders difficulties on quality, output, genre elements, and vocabulary as well as problems with foundational writing skills (i.e. sentences, spelling, and handwriting). An important reason for the association between problems in writing and ADHD is the key role that working memory has in the processes required to produce a coherent text (Hayes & Flower, 1980). Swanson and Berninger (1996) proposed that writing ability in young children is related to individual differences in working memory skills, and other studies have shown that writers with higher working memory abilities are capable of achieving their goals more efficiently producing more coherent compositions (Alamargot & Chanquoy, 2001; Piolat, Roussey, Olive, & Amada, 2004). Specifically, working memory includes the following components (Baddeley, 2000): (a) central executive (a supervisory system); (b) phonological loop (related to sound or phonological information); (c) visuospatial sketchpad (related to visual/spatial information), and (d) episodic buffer (responsible for the integration of the information from the previous systems and from long-term memory). As an example, for writing, the phonological loop is important to translate ideas into sentences, the visuospatial sketchpad is crucial for planning (Kellogg, 1996), and the central executive is critical to regulate and control attention (Vanderberg & Swanson 2007). Kellogg’s model (1996) suggested that the monitoring process (the review process by Hayes, 1996) requires cognitive requirements upon the central executive— phonological loop. Furthermore, central executive significantly predicted threads planning, editing, and revision, as well as most microstructure measures of writing (Vanderberg & Swanson 2007). Although working memory is crucial for writing expression, another major reason for the reported link between writing problems and ADHD is the role of inhibition. Reduced inhibitory control is one of the most robust findings in the neuropsychology of ADHD. Barkley (2012, 2015) suggests that a deficit in inhibitory control leads to deficits in working memory, emotional regulation, and cognitive flexibility, subsequently entailing difficulties in self-regulation and thus in generating self-governed behaviours. Therefore, as difficulties with working memory and inhibition are characteristics of ADHD, students with this disorder may have writing problems such as (a) keeping ideas in mind while writing, (b) paying attention to details making errors in spelling, grammar, and/or punctuation, and (c) sustaining the attention required for writing (more examples presented in Table 7.1).
Specific Learning Disorder (SLD) SLD is an overall diagnosis that incorporates difficulties in learning specific academic skills (American Psychiatric Association, 2013). There are three types of Learning Disorders characterized separately by deficits in reading (i.e. dyslexia), in writing (i.e. dysgraphia), and/or deficits in mathematics (i.e. dyscalculia). SLDs can be further specified by descriptions (e.g. reading accuracy/fluency, spelling accuracy, written
Specific Learning Disorder (SLD) 167
expression competence and fluency, mastering number facts) and by severity ratings (i.e. determined as being mild, moderate, or severe). The severity ratings relate to the degree to which the child struggles to perform in comparison with his/her peers and the amount of support required (American Psychiatric Association, 2013). Difficulties with written expression in children with dyslexia (a reading and spelling disorder) may be related to handwriting skills. Research has shown that the handwriting of children with dyslexia is slower than typically developing peers (Berninger et al., 2008; Sovik & Arntzen, 1986; Sovik, Arntzen, & Thygesen, 1987) and continues to be slower in adulthood (Hatcher, Snowling, & Griffiths, 2002). Controversy, research also showed that slower writing in dyslexia is due to pausing more often when writing (Sumner, Connelly, & Barnett, 2013, 2014) suggesting that the handwriting act is not impaired in these individuals. Besides, the coding of phonological information in memory and the transformation of phonological information in written words is often problematic for students with dyslexia (Berninger et al., 2008; Gayan & Olson, 2001). The limited phonological skills of these children influence and inhibit the development of orthographic knowledge (Fayol, Zorman, & Lété, 2009). In fact, children with dyslexia continue to struggle with spelling even when the problems in reading seem resolved (Kemp, Parrila, & Kirby, 2009), and the essays of students with this disorder contain more spelling errors and write fewer words compared to typically developing peers (Connelly, Campbell, MacLean, & Barnes, 2006; Sterling et al., 1998). These results suggested that, for students with dyslexia, spelling difficulties make the writing process slower. Spelling development is a key predictor of writing composition quality for typically developing individuals but also for children with dyslexia (Abbott, Berninger, & Fayol, 2010; Berninger et al., 2008; Gregg, Coleman, Davis, & Chalk, 2007). As individuals with dyslexia have to concentrate more on spelling words, they produce less text compared to those without spelling problems (Connelly, Campbell, MacLean, & Barnes, 2006; Gregg, Coleman, Davis, & Chalk, 2007). Over time, children with dyslexia persist in their struggle with spelling (Puranik, Lombardino, & Altmann, 2007; Sumner, Connelly, & Barnett, 2011), and adults with dyslexia report that writing, not reading, is their biggest problem (Burden, 2005; Mortimore & Crozier, 2006). To explain the basis for dyslexia, traditionally, research has focused on language- based processes such as phonology (Morris et al., 1998; Wagner & Torgesen, 1987). However, more recently, EF has been analysed as a contributing factor to this disorder (Swanson, 2001). Individuals with dyslexia have difficulty with the organization and integration of multiple processes (e.g. having to contend with spelling and composing concurrently) as well as present impairments of inhibition, updating verbal working memory, and cognitive flexibility (Berninger et al., 2006; Brosnan et al., 2002; Denckla, 1996; Helland & Asbjørnsen, 2000; Kelly, Best, & Kirk, 1989; Purvis & Tannock, 2000; Reiter, Tucha, & Lange, 2005). For instance, Reiter and colleagues (2005) suggested that children with dyslexia exhibit difficulty in inhibit prepotent responses: children with this disorder were slower in their processing time on the colour naming and
168 7. Executive Functions, Writing, and Disorders word reading tasks but also exhibited problems in the number of errors and corrections on the inhibition (Interference) condition of the Stroop test. Thus, individuals with dyslexia are impaired in EF. Dysgraphia is a condition that may occur isolated or together with dyslexia (Berninger et al., 2008), and it is considered a SLD with impairment in written expression. This disorder may include deficits in spelling accuracy, grammar and punctuation accuracy, and clarity or organization of written expression (American Psychiatric Association, 2013). For some authors, dysgraphia is a language processing disorder, which not includes the motor component of writing (Berninger et al., 2008). Importantly, problems in any component of the writing process may affect writing skills (Berninger, 2008). Some authors suggested that dysgraphia results from problems in the verbal working memory from word sounds to written letters memory, as well as they proposed that EF contribute to the presentation of the disorder (Berninger, 2008). Indeed, handwriting automaticity requires EF since they are crucial skills for the integration of multiple processes, such as motor planning, orthography, ortho-graphic-motor integration via working memory, and processing speed (e.g. Berninger et al., 2008). Working memory impairments are widely being discussed and identified as being related to learning disabilities, thus, a widely reason for the association between writing problems and SLD is the role of this particular skill (Alloway & Gathercole, 2006; Pickering, 2006). Moreover, some researchers suggested that working memory deficits are the primary cause of learning disabilities (e.g. Swanson & Siegel, 2001). Given the working memory deficits, children with SLD can have difficulty with specific aspects of writing such as (a) fully remember what they are supposed to be doing while writing, (b) following writing instructions with two or more parts, retaining new words and remembering the vocabulary for the subject matter, (c) and retaining information for later retrieval (more examples reported in Table 7.1).
Implications for Practice When students have developmental problems or academic difficulties, their needs should be assessed in different ways. One approach is to search for a diagnostic label such as ASD, ADHD, and/or SLD. These diagnostic labels may provide valuable information about difficulties while producing written text. For instance, Berninger and O’Malley (2011) showed that non-responders to intervention can be transformed into responders to intervention when treatment is personalized to their specific needs identified by a differential diagnosis. However, teachers need to move beyond diagnostic labels and identify the areas in the writing process that are challenging the student. Therefore, teachers and clinicians should recognize that their students’ needs will be different, and they should be concerned with the identification of the unique educational needs of these individuals.
Implications for Practice 169
When assessing writing, teachers and clinicians should assess language and linguistic functions recruited throughout the writing process (e.g. vocabulary, phonological processing, orthographic coding, syntax, among others; see Hooper et al., 2011). However, they also need to be aware that inherent executive dysfunction may impact components of written performance because multiple processes are involved in writing performance (e.g. Berninger, García, & Abbot, 2009). Thus, EF should also be measured. In this regard, standardized assessment instruments are particularly valuable as they can be reliably administered across samples measuring differential cognitive abilities across ages and neurodevelopmental disorders. Knowing that writing requires EF and that a student with a neurodevelopmental disorder has impairments in those skills, educators and clinicians should consider using instructional methods and strategies that specifically address those problems (Kaplan, Lichtinger, & Gorodetsky, 2009). Three instructional components for writing interventions can lead to positive effects in the writing expression helping writers to better focus on the writing task itself: (a) explicit instruction for the different stages of the writing process; (b) explicit instruction of text structure; and (c) guided feedback from a technician, teacher, or peer (Gersten & Baker, 2001). Regardless of the main aim of the intervention, one focus should be on increasing the student’s awareness of the EF needed to achieve the target goal (Feifer & DeFina, 2002), as well as it is crucial to implement students’ compensatory strategies to overcome executive impairments. For instance, environmentally based strategies (such as a highly structured and well-organized classroom, Dawson & Guare, 2010; and an environment with few potential distractions, Graham, 1990) restrict the number of irrelevant stimuli and provide order that help the student to develop an increased understanding of environmental events. The use of checklists and computerized reminder systems (Yalçinkaya, Muluk, & Sahin, 2009) can also facilitate student performance during complex task performance. The limitation of the number of tasks that require updating at encoding and retrieval stages (Yalçinkaya, Muluk, & Sahin, 2009) can help with working memory demands. Grouping visual or verbal information into chunks (i.e. clusters of items that can be stored as a single unit) according to specific categories (McCloskey, Perkins, & Van Divner, 2009) may also be considered. For instance, it is easier to remember numbers in chunks (e.g. 916-908-544) than remembering the same numbers without being grouped (e.g. 916908544). Finally, the use of the mnemonic keyword method, a strategy to improve paired-associated learning as learning vocabulary words (Atkinson & Raugh, 1975) can be helpful. A keyword is a concrete and associated word acoustically similar to the information to be learned. This strategy combines verbal information and visual imagery. One well researched evidence-based teaching model that incorporates EF essential to written expression is the Self-Regulated Strategy Development (SRSD; Graham, Harris, & Mason, 2005; Mason & Graham, 2008; Mason, Harris, & Graham, 2002). SRSD is based on cognitive-behavioural modification, and it is a model for teaching strategies to improve writing skills facilitated by working memory, inhibition, and self-regulation (Harris & Graham, 2005; Mason & Graham, 2008). Teaching steps of
170 7. Executive Functions, Writing, and Disorders SRSD reduce demands on working memory using, for instance, mnemonics, cues, and graphs. This training addresses the EF problems of students with neurodevelopmental disorders. For instance, several studies support the use of SRSD to improve the writing skills of students with learning disabilities. SRSD instruction produced greater effects, for students with learning disabilities, than studies that did not use this approach (for a review and meta-analysis, see Gillespie & Graham, 2014; Graham & Harris, 2003) The SRSD model also improved the writing skills of students with ADHD (De La Paz, 2001; Jacobson & Reid, 2010; Jacobson & Reid, 2012; Lienemann, Graham, Leader-Janssen, & Reid, 2006; Lienemann & Reid, 2008; Reid & Lienemann, 2006;), and there are several possible reasons for these positive results. First, this approach has demonstrated effectiveness with children with learning disabilities (Graham & Harris, 2003). As there is considerable overlap between learning disabilities and ADHD populations (Schnoes, Reid, Wagner, & Marder, 2006), this may explain these encouraging results. Second, SRSD addresses the EF impairments that are common in students with ADHD, for instance, difficulties with establishing goals and holding them in memory, problems with persisting toward goal achievement, and/or modelling and directing behaviours to achieve aims. Indeed, in SRSD goal setting is discussed, the importance of goals is highlighted, and progress toward goals is monitored. Furthermore, SRSD develops self-regulation strategies that have demonstrated efficacy with ADHD students improving their ability to maintain focus and effort (Reid, Trout, & Schartz, 2005). Finally, SRSD model could also improve the writing skills of students with ADHD because it addresses working memory impairments that are common in students with ADHD. In fact, SRSD model could help to reduce demands on working memory because it presents instruction in small steps, teaches strategies to achieve automaticity, and provides systematic scaffolded practice (Lienemann & Reid, 2008). Across development, research has shown that SRSD model can be an effective method across development improving writing skills of elementary (e.g. Lienemann, Graham, Leader-Janssen, & Reid, 2006; Lienemann & Reid, 2008; Reid & Lienemann, 2006), middle school (De La Paz, 2001), and high school (Jacobson & Reid, 2010; Jacobson & Reid, 2012) students with ADHD. Research also suggested that SRSD may be effective for students with ASD (Asaro- Saddler & Bak, 2014; Asaro & Saddler, 2009; Asaro-Saddler & Saddler, 2010; Delano, 2007a, 2007b). Pennington and Delano (2012) reviewed 15 writing intervention studies for students with ASD (29 participants, ages 4 to 21 years), and these studies found that SRSD approach effectively increased the overall quality of written performance in ASD. Interventions for writing skills for students with ASD is critical as students with ASD could use written responses to make direct requests, to engage in social interactions, or to regulate their own behaviour using organizational strategies (e.g. list-making, labelling). Individuals with ASD who fail to develop adequate writing skills are likely to experience difficulties in their daily life (e.g. school and workplace). Despite these promising results found for these neurodevelopmental disorders, the overall findings were affected by the weaknesses in the studies presented (e.g.
Conclusion 171
lack of control for instructor effects, reliability and validity of outcome measures, and treatment fidelity data). More research is needed to establish an evidence-based set of practices to guide educators, clinicians, and researchers in the development of effective writing programmes for each specific population of students (i.e. for each neurodevelopmental disorder). Written language may be the most difficult academic skill for students to master, and, thus, implementing effective writing strategies for students with neurodevelopmental disorders is challenging. As students with neurodevelopmental problems may have difficulties related to EF deficits, an important goal for writing instruction is to support those EFs. Teachers’ and clinicians’ knowledge about the processes that support writing development as well as an understanding of the specific difficulties which will challenge students are needed. The recommendations made in this chapter should be considered as guidelines for planning writing instructions for students with neurodevelopmental disorders (such as ASD, ADHD, and SLD). However, there are a variety of strategies available for teaching writing skills. It is recommended the use of evidence-based practices, and teachers may proceed with caution and adjust their instruction if their students do not progress. The challenge for practitioners and researchers is to identify effective instructional methods.
Conclusion This chapter focused on individuals diagnosed with the most common neurodevelopmental disorders: ASD, ADHD, and SLD. Individuals with these disorders evidence problems in EF (e.g. working memory, inhibition of impulses, and mental set or task shifting) and writing difficulties. The previous sections intended to contribute to our understanding about the cognitive mechanisms (related with EF) that underlie writing development for atypical neurodevelopment. Although the relationship between EF and writing processes is a relatively recent area of research, several studies found difficulties in texts produced by students with executive dysfunction suggesting that executive functioning skills are critical for writing performance. In sum, it was highlighted how EF may contribute to writing difficulties. Importantly, findings from these studies may serve as the basis for future research and lead to a progress in the study of this topic. Furthermore, it is also important to consider that individuals with neuro developmental disorders represent a heterogeneous group, and from previous research, it is not clear whether EF, IQ scores, and/or functional levels influence the reported writing difficulties. As intelligence is considered a strong predictor of academic achievements (reviews: Gottfredson, 2002; Sternberg, Grigorenko, & Bundy, 2001), researchers need to consider any additional problem such as an intellectual disability in order to understand the unique traits of the development of written expression for individuals with neurodevelopmental disorders. Overall, any attempt to
172 7. Executive Functions, Writing, and Disorders cover the whole spectrum of these disorders is important and more research is needed to explore whether the writing difficulties are due to EF impairments.
References Abbott, R., Berninger, V., & Fayol, M. (2010). Longitudinal relationships of levels of language in writing and between writing and reading in grades 1 to 7. Journal of Educational Psychology, 102, 281–98. Alamargot, D., & Chanquoy, L. (2001). Through the Models of Writing. Amsterdam, the Netherlands: Kluwer Academic Publishers. Alloway, T.P., & Gathercole, S.E. (2006). Working Memory and Neurodevelopmental Disorders. New York, NY: Psychology Press. American Psychiatric Association (2013). Diagnostic and Statistical Manual of Mental Disorders (5th Ed.). Arlington, VA: American Psychiatric Publishing. Ardila, A., & Surloff, C. (2006). Dysexecutive agraphia: a major executive dysfunction sign. International Journal of Neuroscience, 116(5), 653–63. Arrington, C.N., Kulesz, P.A., Francis, D.J., Fletcher, J.M., & Barnes, M.A. (2014). The contribution of attentional control and working memory to reading comprehension and decoding. Scientific Studies of Reading, 18, 325–46. Asaro-Saddler, K., & Bak, N. (2014). Persuasive writing and self-regulation training for writers with autism spectrum disorders. The Journal of Special Education, 48(2), 92–105. Asaro, K., & Saddler, B. (2009). Effects of planning instruction on a young writer with Asperger syndrome. Intervention in School and Clinic, 44(5), 268–75. Asaro-Saddler, K., & Saddler, B. (2010). Planning instruction and self-regulation training: effects on writers with autism spectrum disorders. Exceptional Children, 77(1), 107–24. Atkinson, R.C., & Raugh, M.R. (1975). An application of the mnemonic keyword method to the acquisition of Russian vocabulary. Journal of Experimental Psychology: Human Learning and Memory, 104(2), 126–33. Baddeley, A.D. (2000). The episodic buffer A new component of working memory Trends in Cognitive Sciences, 4(11), 417–23. Baranek, G.T., David, F.J., Poe, M.D., Stone, W.L., & Watson, L.R. (2006). Sensory Experiences Questionnaire: discriminating sensory features in young children with autism, developmental delays, and typical development. Journal of Child Psychology and Psychiatry, 47, 591–601. Barkley, R.A. (1997). Behavioral inhibition, sustained attention, and executive functions: constructing a unifying theory of ADHD. Psychological Bulletin, 121, 65–94. Barkley, R.A. (2006). Attention-Deficit Hyperactivity Disorder: A Handbook for Diagnosis and Treatment (3rd Ed.). New York, NY: Guilford. Barkley, R.A. (2012). Executive Functions: What They Are, How They Work, and Why They Evolved. New York, NY: Guilford Press. Barkley, R.A. (2015). Executive functioning and self- regulation viewed as an extended phenotype: implications of the theory for ADHD and its treatment. In R.A. Barkley (Ed.). Attention-deficit Hyperactivity Disorder: A Handbook for Diagnosis and Treatment (pp. 405– 34). New York, NY: The Guilford Press. Barry, T.D., Lyman, R.D., & Klinger, L.G. (2002). Academic underachievement and attention deficit/hyperactivity disorder: the negative impact of symptom severity on school performance. Journal of School Psychology, 40(3), 259–83.
References 173 Berninger, V.W. (2008). Defining and differentiating dysgraphia, dyslexia, and language learning disability within a working memory model. In M. Mody & E.R. Silliman (Eds.). Challenges in Language and Literacy. Brain, Behavior, and Learning in Language and Reading Disorders (pp. 103–34). New York, NY: Guilford Press. Berninger, V.W. (2009). Highlights of programmatic, interdisciplinary research on writing. Learning Disabilities Research & Practice, 24(2), 69–80. Berninger, V.W. (Ed.) (2011). Past, Present, and Future Contributions of Cognitive Writing Research to Cognitive Psychology. New York, NY: Psychology Press/Taylor Francis Group. Berninger, V.W., Abbott, R., Thomson, J., Wagner, R., Swanson, H.L., Wijsman, E.M., & Raskind, W. (2006). Modeling phonological core deficits within a working memory architecture in children and adults with developmental dyslexia. Scientific Studies of Reading, 10(2), 165–98. Berninger, V.W., García, N.P., & Abbot, R.D. (2009). Multiple processes that matter in writing assessment and instruction. In G.A. Troia (Ed.). Instruction and assessment for struggling writers (pp. 15–50). New York, NY: Guilford Press. Berninger, V.W., Nielsen, K.H., Abbott, R.D., Wijsman, E., & Raskind, W. (2008). Writing problems in developmental dyslexia: under-recognized and under-treated. Journal of School Psychology, 46(1), 1–21. Berninger, V.W., & O’Malley M. (2011). Evidence-based diagnosis and treatment for specific learning disabilities involving impairments in written and/or oral language. Journal of Learning Disabilities, 44, 167–83. Berninger, V.W., & Winn, W.D. (2006). Implications of advancements in brain research and technology for writing development, writing instruction, and educational evolution. In C.A. MacArthur, S. Graham, & J. Fitzgerald (Eds.). Handbook of Writing Research (pp. 96–114). New York, NY: Guilford Press. Best, J.R., & Miller, P.H. (2010). A developmental perspective on executive function. Child Development, 81(6), 1641–60. Bishop, D., & Rutter, M. (2008). Neurodevelopmental disorders: conceptual approaches. In M. Rutter, D. Bishop, D. Pine, S. Scott, J. Stevenson, E. Taylor, & A. Thapar (Eds.). Rutter’s Child and Adolescent Psychiatry (pp. 32–41). Oxford, UK: Blackwell. Blackwell, K.A., Cepeda, N.J., & Munakata, Y. (2009). When simple things are meaningful: working memory strength predicts children’s cognitive flexibility. Journal of Experimental Child Psychology, 103(2), 241–9. Brossard- Racine, M., Majnemer, A., Shevell, M., Snider, L., & Bélanger, S.A. (2011). Handwriting capacity in children newly diagnosed with attention deficit hyperactivity disorder. Research in Developmental Disabilities, 32(6), 2927–34. Brosnan, M., Demetre, J., Hamill, S., Robson, K., Shepherd, H., & Cody, G. (2002). Executive functioning in adults and children with developmental dyslexia. Neuropsychologia, 40(12), 2144–55. Brossard-Racine, M., Shevell, M., Snider, L., Bélanger, S.A., Julien, M., & Majnemer, A. (2015). Persistent handwriting difficulties in children with ADHD after treatment with stimulant medication. Journal of Attention Disorders, 19(7), 620–9. Brown, T.E. (2006). Executive functions and attention deficit hyperactivity disorder: implications of two conflicting views. International Journal of Disability, Development and Education, 53(1), 35–46. Burden, R. (2005). Dyslexia and Self-concept: Seeking a Dyslexic Identity. London, UK: Whurr. Carpenter, L.A., Soorya, L., & Halpern, D. (2009). Asperger’s syndrome and high-functioning autism. Pediatric Annals, 38, 30–5. Casas, A., Ferrer, M., & Fortea, I. (2013). Written composition performance of students with attention-deficit/hyperactivity disorder. Applied Psycholinguistics, 34(3), 443–60.
174 7. Executive Functions, Writing, and Disorders Christensen, D.L., Baio, J., Braun, K.V., Bilder, D., Charles, J., Constantino, J. N., . . . & Centers for Disease Control and Prevention (2016). Prevalence and characteristics of autism spectrum disorder among children aged 8 Years—autism and developmental disabilities monitoring network, 11 Sites, United States, 2012. MMWR Surveillance Summaries, 65(SS– 3), 1–23. Collins, A., & Koechlin, E. (2012). Reasoning, learning, and creativity: frontal lobe function and human decision-making. PLoS Biology, 10(3), e1001293. Connelly, V., Campbell, S., MacLean, M., & Barnes, J. (2006). Contribution of lower order skills to the written composition of college students with and without dyslexia. Developmental Neuropsychology, 29(1), 175–96. Corbett, B.A., Constantine, L.J., Hendren, R., Rocke, D., & Ozonoff, S. (2009). Examining executive functioning in children with autism spectrum disorder, attention deficit hyperactivity disorder and typical development. Psychiatry Research, 166, 210–22. Cornoldi, C., Del Prete, F., Gallani, A., Sella, F., & Re, A.M. (2010). Components affecting expressive writing in typical and disabled writers. Advances in Learning and Behavioral Disabilities, 23, 269–86. Cortese, S., Adamo, N., Del Giovane, C., Mohr-Jensen, C., Hayes, A. J., Carucci, S., . . . & Cipriani, A. (2018). Comparative efficacy and tolerability of medications for attention-deficit hyperactivity disorder in children, adolescents, and adults: a systematic review and network meta-analysis. Lancet Psychiatry, 5(9), 727–38. Dawson, P., & Guare, R. (2010). Executive Skills in Children and Adolescents: A Practical Guide to Assessment and Intervention (2nd ed.). New York, NY: Guilford Press. D’Cruz, A.-M., Ragozzino, M.E., Mosconi, M.W., Shrestha, S., Cook, E.H., & Sweeney, J.A. (2013). Reduced behavioral flexibility in autism spectrum disorders. Neuropsychology, 27(2), 152–60. De La Paz, S. (2001). Teaching writing to students with attention deficit disorders and specific language impairment. The Journal of Educational Research, 95(1), 37–47. Delano, M.E. (2007a). Use of strategy instruction to improve the story writing skills of a student with Asperger syndrome. Focus on Autism and Other Developmental Disabilities, 22, 252–8. Delano, M.E. (2007b). Improving written language performance of adolescents with Asperger syndrome. Journal of Applied Behavior Analysis, 40, 345–51. Denckla, M.B. (1996). A theory and model of executive function: a neuropsychological perspective. In G.R. Lyon & N.A. Krasnegor (Eds.). Attention, Memory, and Executive Function (pp. 263–78). Baltimore, MD: Paul H Brookes Publishing Co. Dennis, M., Lockyer, L., Lazenby, A.L., Donnelly, R.E., Wilkinson, M., & Schoonheyt, W. (1999). Intelligence patterns among children with high-functioning autism, phenylketonuria, and childhood head injury. Journal of Autism and Developmental Disorders, 29(1), 5–17. Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64, 135–68. Durst, R., & Newell, G. (1989). The uses of function: James Britton’s category system and research on writing. Review of Educational Research, 59, 375–94. Fayol, M., Zorman, M., & Lété, B. (2009). Unexpectedly poor and good spellers too. Associations and dissociations in reading and spelling French. British Journal of Educational Psychology, 1(1), 63–75. Feder, K.P., & Majnemer, A. (2007). Handwriting development, competency, and intervention. Developmental Medicine and Child Neurology, 49(4), 312–17. Feifer, S.G., & DeFina, P.D. (2002). The Neuropsychology of Written Language Disorders: Diagnosis and Intervention. Middletown, MD: School Neuropsych Press. Finnegan, E.G., & Accardo, A.L. (2018). Written expression in individuals with autism spectrum disorder: a meta-analysis. Journal of Autism and Developmental Disorders, 48, 868–82.
References 175 Fliers, E., Vermeulen, S., Rijsdijk, F., Altink, M., Buschgens, C., Rommelse, N., . . . Franke, B. (2009). ADHD and poor motor performance from a family genetic perspective. Journal of the American Academy of Child & Adolescent Psychiatry, 48(1), 25–34. García, J.N., Rodríguez, C., Pacheco, D., & Diez, C. (2009). Influence of cognitive effort, sustained attention, working memory and ADHD symptoms in the process and product of written composition. An experimental study. Estudios de Psicología, 30(1), 31–50. Garon, N., Bryson, S.E., & Smith, I.M. (2008). Executive function in preschoolers: a review using an integrative framework. Psychological Bulletin, 134(1), 31–60. Gathercole, S.E., Alloway, T.P., Willis, C., & Adams, A.-M. (2006). Working memory in children with reading disabilities. Journal of Experimental Child Psychology, 93(3), 265–81. Gayan, J., & Olson, R.K. (2001). Genetic and environmental influences on orthographic and phonological skills in children with reading disabilities. Developmental Neuropsychology, 20(2), 483–507. Gersten, R., & Baker, S.K. (2001). Teaching expressive writing to students with learning disabilities: a meta-analysis. The Elementary School Journal, 101(3), 251–72. Geurts, H.M., Verté, S., Oosterlaan, J., Roeyers, H., & Sergeant, J.A. (2005). ADHD subtypes: do they differ in their executive functioning profile? Archives of Clinical Neuropsychology, 20(4), 457–77. Gillespie, A., & Graham, S. (2014). A meta-analysis of writing interventions for students with learning disabilities. Exceptional Children, 80(4), 454–73. Gioia, G.A., Isquith, P.K., Guy, S.C., & Kenworthy, L. (2000). Behavior rating inventory of executive function. Child Neuropsychology, 6(3), 235–8. Goldstein, G., Johnson, C.R., & Minshew, N.J. (2001). Attentional process in autism. Journal of Autism and Developmental Disorders, 31(4), 433–40. Gottfredson, L.S. (2002). g: Highly general and highly practical. In R.J. Sternberg, & E.L. Grigorenko (Eds.). The General Factor of Intelligence: How General Is It? (pp. 331–80). Mahwah, NJ: Lawrence Erlbaum Associates. Graham, S. (1990). The role of production factors in learning disabled students’ compositions. Journal of Educational Psychology, 82(4), 781–91. Graham, S., Fishman, E.J., Reid, R., & Hebert, M. (2016). Writing characteristics of students with attention deficit hyperactive disorder: a meta-analysis. Learning Disabilities Research & Practice, 31(2), 75–89. Graham, S., & Harris, K.R. (2000). The role of self-regulation and transcription skills in writing and writing development. Educational Psychologist, 35(1), 3–12. Graham, S., & Harris, K.R. (2003). Students with learning disabilities and the process of writing: a meta-analysis of SRSD studies. In L. Swanson, K.R. Harris, & S. Graham (Eds.). Handbook of Learning Disabilities (pp. 323–44). New York, NY: Guilford Press. Graham, S., & Harris, K.R. (2006). Preventing writing difficulties: providing additional handwriting and spelling instruction to at-risk children in first grade. Teaching Exceptional Children, 38(5), 64–6. Graham, S., Harris, K.R., & Mason, L. (2005). Improving the writing performance knowledge and self-efficacy of struggling young writers: the effects of self-regulated strategy development. Contemporary Educational Psychology, 30(2), 207–41. Graham, S., Morphy, P., Harris, K.R., Fink-Chorzempa, B., Saddler, B., Moran, S., & Mason, L. (2008). Teaching spelling in the primary grades: a national survey of instructional practices and adaptations. American Educational Research Journal, 45(3), 796–825. Gregg, N.G., Coleman, C., Davis, M., & Chalk, J.C. (2007). Timed essay writing: implications for high-stakes test. Journal of Learning Disabilities, 40(4), 306–18. Hayes, J.R. (1996). A new framework for understanding cognition and affect in writing. In C.M. Levy & S. Ransdell (Eds.). The Science of Writing: Theories, Methods, Individual Differences, and Applications (pp. 1–27). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
176 7. Executive Functions, Writing, and Disorders Hayes, J.R., & Flower, L. (1980). Identifying the organization of writing processes. In L.W. Gregg & E.R. Steinberg (Eds.). Cognitive Processes in Writing: An Interdisciplinary Approach (pp. 3–30). Hillsdale, NJ: Lawrence Erlbaum. Harris, K.R., & Graham, S. (2005). Improving the writing performance of young struggling writers: theoretical and programming research from the center on accelerating student learning. Journal of Special Education, 39(1), 19–33. Hatcher, J., Snowling, M.J., & Griffiths, Y.M. (2002). Cognitive assessment of dyslexic students in higher education. British Journal of Educational Psychology, 72, 119–33. Helland, T., & Asbjørnsen, A. (2000). Executive functions in dyslexia. Child Neuropsychology, 6(1), 37–48. Hooper, S.R., Costa, L.C., McBee, M., Anderson, K.L., Yerby, D.C., Knuth, S.B., & Childress, A. (2011). Concurrent and longitudinal neuropsychological contributors to written language expression in first and second grade students. Reading and Writing, 24, 221–52. Hughes, C., Russell, J., & Robbins, T.W. (1994). Evidence for executive dysfunction in autism. Neuropsychologia, 32(4), 477–92. Jacobson, L.T., & Reid, R. (2010). Improving the persuasive essay writing of high school students with ADHD. Exceptional Children, 76(2), 157–74. Jacobson, L.T., & Reid, R. (2012). Improving the writing performance of high school students with attention deficit/hyperactivity disorder and writing difficulties. Exceptionality, 20(4), 218–34. Kaplan, A., Lichtinger, E., & Gorodetsky, M. (2009). Achievement goal orientations and self-regulation in writing: an integrative perspective. Journal of Educational Psychology, 101(1), 51–69. Kellogg, R.T. (1996). A model of working memory in writing. In C.M. Levy & S. Ransdell (Eds.). The Science of Writing: Theories, Methods, Individual Differences and Applications (pp. 57–71). Mahwah, NJ: Lawrence Erlbaum Associates. Kellogg, R.T., Whiteford, A.P., Turner, C.E., Cahill, M., & Mertens, A. (2013). Working memory in written composition: an evaluation of the 1996 model. Journal of Writing Research, 5(2), 159–90. Kelly, M.S., Best, C.T., & Kirk, U. (1989). Cognitive processing deficits in reading disabilities: a prefrontal cortical hypothesis. Brain and Cognition, 11(2), 275–93. Kemp, N., Parrila, R., & Kirby, J. (2009). Phonological and orthographic spelling in high- functioning adult dyslexics. Dyslexia, 15(2), 105–28. Lawrence, V., Houghton, S., Douglas, G., Durkin, K., Whiting, K., & Tannock, R. (2004). Executive function and ADHD: a comparison of children’s performance during neuropsychological testing and real-world activities. Journal of Attention Disorders, 7(3), 137–49. Lehto, J.E., Juujärvi, P., Kooistra, L., & Pulkkinen, L. (2003). Dimensions of executive functioning: evidence from children. British Journal of Developmental Psychology, 21(1), 59–80. Lienemann, T.O., Graham, S., Leader-Janssen, B., & Reid, R. (2006). Improving the writing performance of struggling writers in second grade. The Journal of Special Education, 40(2), 66–78. Lienemann, T.O., & Reid, R. (2008). Using self-regulated strategy development to improve expository writing with students with attention deficit hyperactivity disorder. Exceptional Children, 74(4), 471–86. Lincoln, A.J., Allen, M.H., & Kilman, A. (1995). The assessment and interpretation of intellectual abilities in people with autism. In E. Schopler & G.B. Mesibov (Eds.). Learning and Cognition in Autism (pp. 89–117). New York, NY: Plenum Press. Lopez, B.R., Lincoln, A.J., Ozonoff, S., & Lai, Z. (2005). Examining the relationship between executive functions and restricted, repetitive symptoms of autistic disorder. Journal of Autism and Developmental Disorders, 35(4), 445–60.
References 177 Lunt, L., Bramham, J., Morris, R.G., Bullock, P.R., & Selway, R.P. (2012). Prefrontal cortex dysfunction and ‘jumping to conclusions’: bias or deficit? Journal of Neuropsychology, 6(1), 65–78. MacArthur, C., Graham, S., & Fitzgerald, J. (Eds.). (2006). Handbook of Writing Research. New York, NY: Guilford Press. Marcovitch, S., Boseovski, J.J., Knapp, R.J., & Kane, M.J. (2010). Goal neglect and working memory capacity in 4-to 6-year-old children. Child Development, 81(6), 1687–95. Mason, L.H., & Graham, S. (2008). Writing instruction for adolescents with learning disabilities: programs of intervention research. Learning Disabilities Research, Practice, 23(2), 103–12. Mason, L.H., Harris, K.R., & Graham, S. (2002). Every child has a story to tell: self-regulated strategy development for story writing. Education and Treatment of Children, 25(4), 496–506. Mayes, S.D., & Calhoun, S.L. (2003). Analysis of WISC-III, Stanford-Binet: IV, and academic achievement test scores in children with autism. Journal of Autism and Developmental Disorders, 33(3), 329–41. Mayes, S., & Calhoun, S.L. (2007). WISC-IV and WIAT-II profiles in children with high- functioning autism. Journal of Autism and Developmental Disorders, 38(3), 428–39. McCloskey, G., Perkins, L.A., & Van Divner, B. (2009). Assessment and Intervention of Executive Function Difficulties. New York, NY: Routledge. Miyake, A., Friedman, N.P., Emerson, M.J., Witzki, A.H., Howerter, A., & Wager, T.D. (2000). The unity and diversity of executive functions and their contributions to complex ‘frontal lobe’ tasks: a latent variable analysis. Cognitive Psychology, 41, 49–100. Morris, R.D., Stuebing, K.K., Fletcher, J.M., Shaywitz, S.E., Lyon, G.R., Shankweiler, D.P., . . . & Shaywitz, B.A. (1998). Subtypes of reading disability: variability around a phonological core. Journal of Educational Psychology, 90(3), 347–73. Mortimore, T., & Crozier, W.R. (2006). Dyslexia and difficulties with study skills in higher education. Studies in Higher Education, 31(2), 235–51. Myles, B.S., Huggins, A., Rome-Lake, M., Hagiwara, T., Barnhill, G.P., & Griswold, D.E. (2003). Written language profile of children and youth with Asperger syndrome: from research to practice. Education and Training in Developmental Disabilities, 38(4), 362–9. National Commission on Writing (2004). Writing: A Ticket to Work... Or A Ticket Out-A Survey of Business Leaders. New York, NY: College Board. Nigg, J.T. (2006). What Causes ADHD? Understanding What Goes Wrong and Why. New York, NY: Guilford Press. Norbury, C.F., & Bishop, D.V. (2003). Narrative skills of children with communication impairments. International Journal of Language and Communication Disorders, 38(3), 287–313. O’Hearn, K., Asato, M., Ordaz, S., & Luna, B. (2008). Neurodevelopment and executive function in autism. Development and Psychopathology, 20(4), 1103–32. Olive, T. (2011). Working memory in writing. In V.W. Berninger (Ed.). Past, Present, and Future Contributions of Cognitive Writing Research to Cognitive Psychology (pp. 485–503). New York, NY: Psychology Press. Ozonoff, S., Pennington, B.F., & Rogers, S.J. (1991). Executive function deficits in high- functioning autistic children: relationship to theory of mind. Journal of Child Psychology and Psychiatry, 32, 1081–105. Pascualvaca, D.M., Fantie, B.D., Papageorgiou, M., & Mirsky, A.F. (1998). Attentional capacities in children with autism: is there a general deficit in shifting focus? Journal of Autism and Developmental Disorders, 28(6), 467–78. Pennington, R.C., & Delano, M.E. (2012). Writing instruction for students with autism spectrum disorders: a review of literature. Focus on Autism and Other Developmental Disabilities, 27(3), 158–67.
178 7. Executive Functions, Writing, and Disorders Pennington, B.F., & Ozonoff, S. (1996). Executive functions and developmental psychopathology. Child Psychology & Psychiatry & Allied Disciplines, 37(1), 51–87. Pennington, B.F., Rogers, S.J., Bennetto, L., Griffith, E.M., Reed, D.T., & Shyu, V. (1997). Validity tests of the executive dysfunction hypothesis of autism. In J. Russell (Ed.). Autism as an Executive Disorder (pp. 143–78). New York, NY: Oxford University Press. Pickering, S.J. (Ed.) (2006). Working Memory and Education. San Diego, CA: Academic Press. Piolat, A., Roussey, J.-Y., Olive, T., & Amada, M. (2004). Text revision by undergraduate students: effects of the type of error and of working memory capacity. In L. Allal, L. Chanquoy, & P. Largy (Eds.). Revision of Written Language: Cognitive and Instructional Processes7 (pp. 21–38). Dordrecht, the Netherlands: Kluwer Academic Publishers. Puranik, C.S., Lombardino, L.J., & Altmann, L.J.P. (2007). Writing through retellings: an explanatory study of language-impaired and dyslexic populations. Reading and Writing, 20, 251–72. Purvis, K.L., & Tannock, R. (2000). Phonological processing, not inhibitory control, differentiates ADHD and reading disability. Journal of the American Academy of Child & Adolescent Psychiatry, 39(4), 485–94. Rapport, M.D., Chung, K.-M., Shore, G., & Isaacs, P. (2001). A conceptual model of child psychopathology: implications for understanding attention deficit hyperactivity disorder and treatment efficacy. Journal of Clinical Child & Adolescent Psychology, 30(1), 48–58. Re, A., & Cornoldi, C. (2010). ADHD expressive writing difficulties of ADHD children: when good declarative knowledge is not sufficient. European Journal of Psychology of Education, 25(3), 315–23. Re, A.M., Pedron, M., & Cornoldi, C. (2007). Expressive writing difficulties in children described as exhibiting ADHD symptoms. Journal of Learning Disabilities, 40(3), 244–55. Reid, R., & Lienemann, T.O. (2006). Improving the writing performance of students with ADHD. Exceptional Children, 73, 53–68. Reid, R., Trout, A.L., & Schartz, M. (2005). Self-regulation interventions for children with attention deficit/hyperactivity disorder. Exceptional Children, 71(4), 361–77. Reiter, A., Tucha, O., & Lange, K. W. (2005). Executive functions in children with dyslexia. Dyslexia, 11(2), 116–31. Resta, S.P., & Eliot, J. (1994). Written expression in boys with attention deficit disorder. Perceptual and Motor Skills, 79(3), 1131–8. Reynolds, C.R., & Goldstein, S. (Eds.) (1999). Handbook of Neurodevelopmental and Genetic Disorders in Children. New York, NY: Guilford Press. Rosenblum, S., Epsztein, L., & Josman, N. (2008). Handwriting performance of children with attention deficit hyperactive disorders: a pilot study. Physical & Occupational Therapy in Pediatrics, 28(3), 219–34. Schnoes, C., Reid, R., Wagner, M., & Marder, C. (2006). ADHD among students receiving special education services: a national survey. Exceptional Children, 72(4), 483–96. Scott, W.A. (1962). Cognitive complexity and cognitive flexibility. Sociometry, 25(4), 405–14. Shen, I., Lee, T., & Chen, C. (2012). Handwriting performance and underlying factors in children with attention deficit hyperactivity disorder. Research in Developmental Disabilities, 33(4), 1301–9. Sonuga-Barke, E.J.S. (2003). The dual pathway model of AD/HD: an elaboration of neuro- developmental characteristics. Neuroscience and Biobehavioral Reviews, 27(7), 593–604. Sovik, N., & Arntzen, O. (1986). A comparative study of the writing/spelling performances of ‘normal,’ dyslexic, and dysgraphic children. European Journal of Special Needs Education, 1(2), 85–101. Sovik, N., Arntzen, O., & Thygesen, R. (1987). Writing characteristics of normal, dyslexic and dysgraphic children. Journal of Human Movement Studies, 13(4), 171–87.
References 179 St Clair- Thompson, H.L., & Gathercole, S.E. (2006). Executive functions and achievements in school: shifting, updating, inhibition, and working memory. Quarterly Journal of Experimental Psychology, 59(4), 745–59. Sterling, C., Farmer, M., Riddick, B., Morgan, S., & Matthews, C. (1998). Adult dyslexic writing. Dyslexia, 4, 1–15. Sternberg, R.J., Grigorenko, E.L., & Bundy, D.A. (2001). The predictive value of IQ. Merrill- Palmer Quarterly, 47, 1–41. Sumner, E., Connelly, V., & Barnett, A. (2011, June). Writing Performance of Children with Dyslexia. Paper presented at the British Dyslexia Association: Beyond Boundaries— Harrogate International Conference Centre, UK. Sumner, E., Connelly, V., & Barnett, A.L. (2013). Children with dyslexia are slow writers because they pause more often and not because they are slow at handwriting execution. Reading and Writing: An Interdisciplinary Journal, 26(6), 991–1008. Sumner, E., Connelly, V., & Barnett, A.L. (2014). The influence of spelling ability on handwriting production: children with and without dyslexia. Journal of Experimental Psychology: Learning, Memory, and Cognition, 40(5), 144–7. Swanson, H.L. (2001). Research on interventions for adolescents with learning disabilities: a meta-analysis of outcomes related to higher-order processing. Elementary School Journal, 101(3), 331–48. Swanson, H.L., & Berninger, V.W. (1996). Individual differences in children’s writing: a function of working memory or reading or both processes? Reading and Writing, 8(4), 357–8. Swanson, H.L., & Siegel, L. (2001). Learning disabilities as a working memory deficit. Issues in Education, 7(1), 1–48. Toll, S.W., Van der Ven, S.S., Kroesbergen, E.H., & Van Luit, J.E. (2011). Executive functions as predictors of math learning disabilities. Journal of Learning Disabilities, 44, 521–32. Trani, M. Di, Casini, M.P., Capuzzo, F., Gentile, S., Bianco, G., Menghini, D., & Vicari, S. (2011). Executive and intellectual functions in attention-deficit/hyperactivity disorder with and without comorbidity. Brain and Development, 33(6), 462–9. Vanderberg, R., & Swanson, H.L. (2007). Which components of working memory are important in the writing process? Reading and Writing: An Interdisciplinary Journal, 20, 721–52. Wagner, R.K., & Torgesen, J.K. (1987). The nature of phonological processing and its causal role in the acquisition of reading skills. Psychological Bulletin, 101(2), 192–212. Whitby, P.J.S., & Mancil, G.R. (2009). Academic achievement profiles of children with high functioning autism and Asperger syndrome: a review of the literature. Education and Training in Developmental Disabilities, 44(4), 551–60. Willcutt, E.G. (2012). The prevalence of DSM-IV attention-deficit/hyperactivity disorder: a meta-analytic review. Neurotherapeutics, 9(3), 490–9. Willcutt, E.G., Doyle, A.E., Nigg, J.T., Faraone, S.V., & Pennington, B.F. (2005). Validity of the executive function theory of attention-deficit/hyperactivity disorder: a meta-analytic review. Biological Psychiatry, 57(11), 1336–46. Wing, L. (2006). What’s So Special About Autism? London, UK: The National Autistic Society. Yalçinkaya, F., Muluk, N.B., & Sahin, S. (2009). Effects of listening ability on speaking writing and reading skills of children who were suspected of auditory processing difficulty. International Journal of Pediatric Otorhinolaryngology, 73(8), 1137–42. Yáñez- Téllez, G., Romero- Romero, H., Rivera- García, L., Prieto- Corona, B., Bernal- Hernández, J., Marosi-Holczberger, E., . . . & Silva-Pereyra, J.F. (2012). Cognitive and executive functions in ADHD. Actas Españolas de Psiquiatría, 40(6), 293–8. Yoshimasu, K., Barbaresi, W.J., Colligan, R.C., Killian, J.M., Voigt, R.G., Weaver, A. L., & Katusic, S.K. (2011). Written-language disorder among children with and without ADHD in a population-based birth cohort. Pediatrics, 128, e605–e612.
180 7. Executive Functions, Writing, and Disorders Zandt, F., Prior, M., & Kyrios, M. (2009). Similarities and differences between children and adolescents with autism spectrum disorder and those with obsessive compulsive disorder: executive functioning and repetitive behavior. Autism, 13(1), 43–57. Zelazo, P.D., Muller, U., Frye, D., & Marcovitch, S. (2003). The development of executive function in early childhood. Monographs of the Society for Research in Child Development, 68, 1–124.
8 Promoting Executive Functions During the Writing Process Linda H. Mason and Stacie Brady
Introduction Good writers use conscious, purposeful, and thoughtful executive functions to activate the processes needed for producing a written product (Mason, Mamlin, & Stewart, 2019). Although most writers recognize the importance of skills such as handwriting/word processing, spelling, vocabulary, and grammar needed for writing, individuals who do not apply executive functions when writing are less aware of the strategic and self-regulatory behaviours needed to initiate and sustain the higher-level writing processes required for planning, composing, revising, and editing written composition (Harris, Graham, MacArthur, Reid, & Mason, 2011; Zimmerman & Risemberg, 1997). These writers often ‘knowledge tell’ in a linear fashion, with little thought toward recursive interaction with the text that is being written (Bereiter & Scardamalia, 1987). Poor application of executive functions skills is especially problematic in the context of increasing expectations and standards for written expression in schools. By the time students graduate from secondary school in the United States, for example, they are expected to write persuasive text that includes (a) valid reasoning and evidence to support claims; (b) organization that ‘logically sequences claims, counterclaims, reasons, and evidence’; (c) words, phrases, and sentences with varied syntax; (e) ‘a formal style and objective tone while attending to the norms and conventions of the discipline’; and (f) a concluding statement or paragraph (English Language Arts Standards, Writing, grades 11–12, National Governors Association Center for Best Practices, 2010). In addition, students are expected to write in both short and extended time frames; gather evidence to support writing while avoiding plagiarism; use and integrate multiple resources to support writing; and use technology to publish and share writing. To meet these expectations for all learners, intervention researchers have focused on required standards components or anchors in isolation (e.g. sentence writing for improved syntax variety), or on interventions focused on improving multiple standard components as the kind that are evaluated in students’ essays. Much of the Linda H. Mason and Stacie Brady, Promoting Executive Functions During the Writing Process In: Executive Functions and Writing. Edited by: Teresa Limpo and Thierry Olive, Oxford University Press. © Oxford University Press 2021. DOI: 10.1093/oso/9780198863564.003.0008
182 8. Promoting EFs During the Writing Process empirical research has focused on instruction to improve the writing performance of school-age writers, including low-achieving writers with and without executive functions-related disabilities (e.g. learning disabilities, attention-related disorders, speech/language disorders, high-functioning autism).
Supporting Executive Functions Skills in Writing Instruction Multiple theoretical models have influenced writing instruction in both elementary and secondary schools (e.g. Bereiter & Scardamalia, 1987; Hayes & Flower, 1986, 1996; Zimmerman & Risemberg, 1997). In these models, writing is considered a cognitive, linguistic, affective, behavioural, and physical process situated within a larger sociocultural context. Graham’s (2018) writer(s)-within-community model (WWC),1 for example, describes written expression as emerging from a complex relationship of multiple sociocultural and cognitive factors. Within WWC, the writer and their collaborators have control mechanisms or executive functions—attention, working memory, and executive control (i.e. intentions, plans, monitor, react)—‘to direct, maintain, and switch attention as needed; establish agency by making decisions about what to write and how; determine the degree of ownership over the writing task; regulate multiple aspects of writing (i.e. thoughts, beliefs, emotions, behaviours, writing tools, interactions with collaborators, and the arrangement of the writing environment); and monitor, react, and make adjustments for all of these actions’ (p. 267). These executive functions are critical and are strongly related to the skills needed for good writing. Many students have difficulties with producing, planning, and organizing ideas; self-regulating and implementing goals and self-monitoring; and maintaining the attention to finish a writing task or for improving writing quality over time (Taft & Mason, 2011). These students have been characterized as writers who cannot easily access, coordinate, or self-regulate multiple mental processes needed for good academic performance. Although these students are a heterogeneous group, they often need support in developing and sustaining executive functions (see Chapter 7 of this volume). For example, students with attention-related and/or learning-related difficulties may lack executive functions in self-regulation (e.g. monitoring performance for a writing goal), organization, and memory (Graham, Collins, & Rigby-Wills, 2017; Reid, Trout, & Schwartz, 2005), while students with language difficulties (e.g. speech/language impairments, autism) may lack strong executive functions in developing and using varied high-level vocabulary and syntax in their writing (De La Paz, 2001; Myles & Simpson, 2002).
1
See Graham, Chapter 3.
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Regardless of the neurological or environmental aetiology for the challenges, many students require specialized and often individualized instruction to support executive functions (Taft & Mason, 2011). To develop and maintain executive functions in writing, for example, instruction should include strategies to support students in (a) analysing a writing task, (b) making decisions about what to write, (c) planning what to write, (d) focusing and maintaining attention throughout the writing process, (e) selecting resources, and (f) understanding the recursive and flexible nature of the writing process (Harris et al., 2018). Strategy instruction is effective in increasing the overall quality of students’ writing, and has long-term impact (Fidalgo, Torrance, & García, 2008). In addition, students’ memory for strategy steps and procedures is supported when mnemonics are included (e.g. ‘Check your paper with COPS: Capitalization, Organization, Punctuation, Spelling’). Self-regulation. Writing proficiency is dependent on the development of students’ self-regulation and transcription skills (Limpo & Alves, 2018). Specifically, as it relates to developing executive functions for writing, students’ self-regulation—goal setting, self-monitoring, self-instructions, and self-reinforcement—should be fostered. Self-regulation prompts students to reflect about and manage the writing process and is a critical component in effective writing instruction (Mason & Reid, 2018). Students should be taught to set goals, goals that are specific, proximal, and appropriately challenging; these goals should be individualized to meet the executive functions needs of each student. Although goal setting begins prior to writing, goals are not meant to be static and should be revisited and revised throughout the writing process. Students should be taught to reflect on and evaluate their writing progress in meeting goals by self-monitoring performance. Charting and graphing progress in meeting goals is especially effective for low-achieving students, and provides the student and the teacher with information about specific areas in need of remediation. An important but often overlooked self-regulation procedure is self-instructions (i.e. self- directions/statements said in one’s head). Personal self-instructions can be developed for specific executive functions by addressing problem definition; focus of attention and planning; strategy use, self-evaluation, and error correcting; and coping and self- control. The final self-regulation procedure, self-reinforcement, is supported by findings from self-monitoring and self-reinforcement through positive self-instruction. Combining instructional components is especially effective for supporting and developing executive functions. Embedding procedures to support students’ self- regulation within strategy instruction, for example, has produced larger outcomes than strategy instruction, without the critical self-regulatory elements that support executive functions (e.g. Sawyer, Graham, & Harris, 1992). In addition, students’ motivation and interest in writing has been noted to increase when self-regulation is included within technology instruction (Regan et al., 2018). Given the importance of self-regulation as a critical element of executive functions for writing, our examination of research-based writing instruction is largely focused on although not limited to, interventions that include a self-regulation component. We begin with interventions for sentence writing. While writing effective sentences
184 8. Promoting EFs During the Writing Process is obviously critical in composing and revision processes, developing executive functions during sentence instruction fosters students’ formulation of main ideas or arguments, with supporting details and explanations, when organizing and planning a paper (e.g. Limpo & Alves, 2013). After the review of sentence writing instruction, developing, and supporting executive functions through instruction situated in the writing process for extended written composition is highlighted.
Supporting Executive Functions for Writing Sentences Students’ Sentence Development Begins in Kindergarten with Language Experience learning and teacher-led modelling, and continues through high school where students learn to focus on revision for improving written expression (Mason & Benedek- Wood, 2014). Because students with executive functions difficulties tend to produce short, simple sentences with grammatical errors, they require explicit instruction in sentence writing to build the skills needed for writing and revising text (Datchuk, 2016; Saddler & Graham, 2005). Instruction for developing these skills should be according to the student’s developmental level regarding proper syntax, mechanics, and variety of sentence structures. The relationship of oral language processing, transcription, and short-and long-term memory skills within executive functions for effective written expression at the sentence level should be considered when providing effective instruction (Berninger & Abbott, 2010). Graham et al. (2012) recommend three instructional practices for improving sentence writing deficits: (1) sentence framing—frames for simple to complex sentences to support sentence writing; (b) sentence expansion—use of a short sentence and parts of speech to write an expanded sentence; and (c) sentence combining—two short sentences are combined into one sentence.
Writing Simple Sentences A number of studies have investigated sentence framing and sentence expansion. In a single-subject design study for three students with moderate intellectual disability and autism (two students) and apraxia (one student), Pennington, Flick, and Smith- Wehr (2018) used response prompt strategies for teaching students to write simple sentences using sentence frames. Utilizing selection-based software as a technology accommodation for the two students with autism, and handwritten sentences for the third student with apraxia, students were taught to construct sentences with three sentence frames—‘I want _________, I see _____, The _____ is ______’ (p. 142).
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Consideration was given to the students’ oral language skills when scaffolding from the often-used requesting statement to the third descriptive sentence frame. Although variable across sentence types and students over time, visual analysis indicated that all students were able to use the sentence frames to correctly complete sentences. Researchers note that findings have implications for students who struggle with writing simple sentences—for example, individualizing the selection of sentence types and response mechanisms based on students’ developmental language level. Researchers noted that beginning sentence frame instruction with the simple requesting frame ‘I want’, a request often used orally by all children, has importance for developing skills with other struggling writers with significant language deficits. Datchuk and colleagues conducted a series of studies examining the impact of explicit sentence writing instruction (model-lead-test methods) with picture-word prompts and frequency building to a performance criterion (i.e. precision teaching) to increase elementary through secondary school students with poor writing skills performance in simple sentence construction. In five studies (Datchuk, 2016, 2017; Datchuk & Kubina, 2017; Datchuk, Kubina, & Mason, 2015; Datchuk & Rogers, 2018), explicit sentence instruction included performance feedback, error correction, praise, and supporting executive functions through self-regulation (e.g. goal setting and evaluation/graphing performance). In each study, after instruction and fluency practice, students showed a higher accuracy and frequency of average number correct word sequences minus incorrect word sequences (CIWS) written in 1-minute sentence construction probes. In all studies, both students and teachers reported feeling that intervention was helpful in improving sentence writing, and recommended no changes to instruction.
Compound and Complex Sentence Writing Sentence types range from simple sentences composed of at least a subject and a verb, as addressed earlier, to a variety of compound and complex sentence types. Two research-based approaches have been specifically developed to address students’ executive functions difficulties in writing compound and complex sentences—the Strategy Instruction Model (SIM) and sentence combining. Research in SIM for addressing executive functions difficulties in writing effective sentences began in the U.S. in the early 1980s. Three single-case design studies with students with learning disabilities in grades 7, 8, and 10 were conducted (Beals, 1983; Eads, 1991; Schmidt, Deshler, Schumaker, & Alley, 1988). Evaluations of the effects of SIM sentence writing instruction (e.g. Mason & Graham, 2008; Rogers & Graham, 2008) indicated that students’ complete sentence writing improved after SIM instruction, with effective to very effective percentage of non-overlapping data (PND).2 Eight stages for strategy acquisition are included in SIM
2 PND—the percentage of data points for a given treatment condition that exceeds the most positive value obtained during baseline. PND above 90% is considered a large effect, 70–90% PND a medium effect, and 50–70% PND a small effect (Scruggs & Mastropieri, 2001).
186 8. Promoting EFs During the Writing Process instruction: (1) pretest and make commitments by setting goals; (2) describe; (3) model; (4) verbal practice; (5) controlled practice; (6) advanced practice; (7) post-test and make commitments for generalization; and (8) generalization. Students are taught to apply a series of 14 different formulas, using the mnemonic PENS (Picks, Explores, Noted, and Subject) for remembering the steps for writing simple, compound, complex, and compound-complex sentences (Schumaker & Deshler, 2003). Sentence combining instruction has also been validated for improving students’ sentence writing (e.g. Saddler, Behforooz, & Asaro, 2008; Saddler & Graham, 2005). In sentence combining, students are taught how to combine two simple sentences into one sentence through writing and revising. For example, for writing a compound sentence from two sentences—‘The bell rang. The children entered the school.’—the following compound sentence can be written—‘The bell rang, and the children entered the school.’ During instruction, students are taught to write six different sentence types: compound sentences, sentences with adjective or adverb modifiers, sentences connected with coordinating or subordinating conjunctions, sentences that contain a modifying clause, sentences with two phrases referring to the same noun, and sentences that contain possessive nouns (Saddler, 2012). Effective sentence combining instruction requires (a) teacher modelling, (b) use of examples and non-examples, (c) practice in isolated activities, and (d) practice in applied activities during the writing process (e.g. planning, composing, and revision). Single-case research indicated that after instruction, the sentence writing of students with learning disabilities improved, with large PND (Saddler, Behforooz, & Asaro, 2008). In a randomized controlled trial, Saddler and Graham (2005) found that low-achieving fourth grade students receiving peer-assisted sentence combining instruction improved in the writing of more complex sentences (Effect Size: ES = 0.46)3 that resulted in improved story writing quality and revising skills. In sentence frame instruction and sentence instruction with precision teaching, and in both SIM for sentence writing and sentence combining, instruction explicitly addresses executive functions deficits by providing students with steps for applying strategies, mnemonics to support memory and organization, and/or procedures to self-regulate the writing of more accurate simple, compound, and complex sentences. Researchers note that the purpose and benefits of instruction should be clearly established, and that students should commit to individualized, developmentally- appropriate goals for improving sentence writing. The teacher should model how to write sentences using the strategies while talking all procedures out loud. Clear example and non-example sentences should be examined. Instruction should be scaffolded from simple to more complex sentences, based on students’ developmental language level, within guided group, peer, and individual practice. Sentence writing should be applied and generalized to authentic writing tasks.4 3 Effect sizes for group studies considered to be small (.20), medium (.50), or large (.80 or greater), as suggested by Cohen (Huck, 2000). 4 Instruction for sentence combining plus instruction for a planning strategy (Limpo & Alves, 2013) to be discussed later in this chapter.
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Supporting Executive Functions for the Writing Process Graham’s (2018) WWC model is situated within three major overlapping writing processes—planning, composing, and revision (see Chapter 3 of this volume). While planning, the writer creates a conceptual plan for completing the written task by generating and organizing ideas, and by setting goals. The writer then implements the conceptual plan by translating the ideas into written words, phrases, clauses, and sentences. During revision, the writer reads the written text and then makes revisions or modifications to content, syntax, and vocabulary. Writing involves complex problem solving, where information is processed through interpretation, reflection, and production. Long-term memory, short-term memory, and motivation have critical roles in the writing process. In addition, the writer must be able to differentiate task schemas, and must have knowledge related to the topic, audience, linguistic, and genre. Given the demands on cognitive and executive functions, self-regulating the writing processes is vital (Graham & Harris, 2000).
Self-Regulated Strategy Development One approach, self-regulated strategy development (SRSD), has been identified as an evidence-based practice for remediating and improving students’ executive functions during the writing process (e.g. Baker et al., 2009; Harris et al., 2018; Graham, Harris, & McKeown, 2013). In Gillespie and Graham’s (2014) meta-analysis of 43 studies for students with learning difficulties, for example, significant large effects were noted for writing quality (ES = 0.74). In SRSD, instruction for strategy acquisition and instruction for teaching students how to self-regulate their writing performance is taught explicitly, and is carefully scaffolded to improve students’ executive functions. SRSD has been researched with experimental, quasi-experimental, and single-case design studies supporting its effectiveness (Gillespie Rouse & Kiuhara, 2017). Research shows that all students, including those with disabilities, are able to make significant gains in written expression, writing quality, and writing motivation when provided with SRSD instruction. SRSD instruction includes an explicit focus on improving executive functions by teaching self- regulation procedures (i.e. goal setting, self- monitoring, self-instruction, and self-reinforcement) to support students’ use of writing strategies (see Harris, Graham, Mason, & Friedlander, 2008; Mason, Reid, & Hagaman, 2012 & 2016, for complete lesson plans and instructional materials). SRSD instruction is meant to increase motivation through embedded aspects of self-efficacy and knowledge on how to complete the specific writing task. In SRSD instruction, six stages for strategy acquisition are emphasized: develop background knowledge, discuss it, modelling it, memorize it, support it, and independent practice. See Box 8.1
188 8. Promoting EFs During the Writing Process
Box 8.1 Strategy acquisition stages in SRSD instruction: supporting executive functions Develop and Activate Knowledge • Focus students’ attention to the learning task by exploring and discussing writing strategies, emphasizing how strategy steps are related to improving writing. • Introduce and begin self-regulation by establishing a goal/commitment to learn the strategies and method for self-monitoring the goal. • Monitor and reinforce students’ knowledge about good writing. Discuss It • Explore students’ attitudes and beliefs about writing, and what they are saying to themselves as they write. • Discuss how and when the strategy can be used for the writing task and for the writing genre. • Establish each students’ commitment to learn the strategy and participate as a collaborative partner with the teacher and other students. • Introduce graphing (self-monitoring). Previously written papers may be used to begin goal setting and charting performance. • Read anchor or example papers to focus students’ attention on the strategy steps, genre elements, and goal for writing. Model It • Model applying the strategy and self- regulation procedures for the writing process—planning, composing, and revision. • Evaluate progress throughout modelling, drawing students’ attention to revising the plan and composition. • Model self-monitoring and graphing the targeted writing skill or goal. • Model self-instructions that target students’ executive functions deficits. Have students create their personal list of self-instructions. Memorize It • Support students’ memorization of strategy steps with mnemonics, self- instructions, and oral or written practice. • Support memorization in all strategy acquisition stages with the goal of having the strategy memorized before Independent Performance. Support It • Scaffold instruction with collaborative writing (with teacher and/or peers) and use of instructional materials such as strategy charts, self-instruction sheets, and graphic organizers.
Supporting Executive Functions for the Writing Process 189 • Scaffold each students’ writing goals for genre elements and characteristics of writing until criterion levels are met. Provide mini-lessons or booster sessions for skills requiring more support. • Monitor students’ application of all self-regulation procedures—goal setting, self- monitoring, self-instructions, and self-reinforcement. • Gradually fade use of instructional materials until the students can complete the writing process independently. • Discuss plans for maintenance and generalization. Independent Performance • Students demonstrate independence in applying the writing strategies and self- regulation procedures across the writing process. • Provide distributed practice. Monitor students’ application of strategy and self- regulation procedures. • Provide practice across settings and curriculum. Monitor students’ application of strategy and self-regulation procedures. • Continue to discuss plans for maintenance and generalization.
for how executive functions are supported throughout the six strategy acquisition stages in SRSD instruction. • Develop background knowledge. Prior to introducing the strategies, students’ background knowledge, and necessary pre-skills for the writing task and self- regulation strategies should be evaluated. At this time, the teacher discusses related vocabulary and concepts, such as the components of good writing and what good writers do to support the writing process. • Discuss it. Each step of the strategy, and how and when to use the strategy, is explained in ‘Discuss it’. Anchor or example papers are read, and strategy elements are identified. After introducing the strategies, the students make a commitment and set goals for learning and using the strategy. Students’ current performance can be reviewed and charted at this time or after ‘Model it’. • Model it. The teacher or a peer models how to complete each step of the strategy and how to apply the components of self-regulation by ‘thinking aloud’ while completing the writing process for the writing task. Modelling includes self- instructions for setting goals, planning and organizing notes, constructing the written response, evaluating and self-monitoring performance, and using self-reinforcement. • Memorize it. Students begin to memorize the strategy when it is introduced in ‘Discuss it’. Mnemonic charts can be used to support memorization, but these visual supports should be faded over time so that students can eventually apply the strategy independently. SRSD lessons often begin or end with memorization practice by asking students to recite steps.
190 8. Promoting EFs During the Writing Process • Support it. Students’ application of strategies and self-regulation should be scaffolded by gradually fading teacher and/or peer support. Booster sessions or mini-lessons to reinforce learning are often needed during ‘Support it’. • Independent performance. Providing opportunities for independent practice, across time and settings, is critical for maintenance and generalization. During students’ independent practice, use of writing strategies and self-regulation should be monitored to ensure a student has not drifted into ways that are ineffective. SRSD Strategies. Some strategies, such as the revising/editing strategy COPS (Capitalization, Organization, Punctuation, Spelling), can be used across writing tasks and genres and are useful for all students. Strategies such as COPS enhance students’ opportunities to apply executive functions skills to writing process components and genres. Students with executive functions difficulties, however, often have weaknesses in writing for a specific purpose and need to be explicitly taught the important elements and structures for each genre. In SRSD, genre-specific strategies are typically taught along with a generalizable organizing strategy such as POW (Pick ideas, Organize using the genre-specific strategy, Write and say more). A sampling of strategies used in SRSD instruction are included in the next two chapter sections—short constructed responses and extended writing tasks.
Short Constructed Responses Difficulties in expressing ideas in a short constructed written response (e.g. responses to questions; summaries) negatively impacts a student’s ability to maximize learning opportunities and their ability to demonstrate knowledge acquired. Summary writing following reading and learning activities, for instance, is typical across grade levels. Teachers expect students to demonstrate what they have learned in their writing. In secondary classes, for example, teachers often use writing-to-learn techniques such as quick-writes to provide students with an opportunity to recall, clarify, and question information, and to assess student understanding. SRSD for quick-writes . SRSD for quick-writes has value for supporting students’ executive functions needed for fluent writing. A good quick-write includes a brief but organized response to a topic or prompt written in a short time period (e.g. 10 minutes is typical). Quick-writing assignments provide teachers with information pertaining to student writing proficiency, as well as content learning, and align with cross-curricular writing expectations (Mason & Kubina, 2011). SRSD for quick-write lessons follow procedures outlined earlier for strategy acquisition and self-regulation; however, it also includes additional procedures supporting executive functions when writing in a specified time frame: (1) develop necessary prerequisite skills for strategy mastery, discuss the strategy, explain how the strategy will improve writing skills, and begin to memorize the strategy steps; (2) teacher cognitively models the strategy
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using all self-regulation procedures and instructional materials; (3) evaluate prior performance; (4) provide collaborative group and/or peer practice; (5) provide scaffolded guided practice; (6) cognitively model a second time to show students how to use the quick-write strategy within the time limit; and (7) provide ample independent practice and opportunities for generalization. As in all SRSD instruction, lessons are designed to be flexible, with stages of strategy instruction and procedures for self- regulation revisited to meet student needs. Quick-writing has been evaluated in six single-case design studies, one quasi- experimental study, and one randomized controlled trial study with students with executive-functions deficits (see Mason & Kubina, 2011, for additional research with students with emotional and behavioural disabilities). In each study, SRSD instruction was implemented in five to six 45-minute strategy acquisition stages, followed by shorter lessons for practising writing the response in 10 minutes. In all but two studies, students learned the open-ended POW plus the genre-specific TREE (Topic, Reasons—3 or more + one counter reason, Explanations—1 for each reason + a refute, Ending) strategy for persuasive quick-writing. The first two SRSD for quick-writing single-case design studies were conducted with seventh grade students in learning support classrooms for students with attention, learning, and/or speech and language disabilities (Mason, Kubina, & Taft, 2011). Graduate assistant researchers delivered the intervention to pairs of students in study one, while a special educator conducted study two with groups of students. Results indicated that students improved performance with large effects for the first study (94% PND for number of elements written at post-instruction and 100% PND at maintenance) and medium effects for the second study for number of elements written (77% PND at post-instruction and 67% PND at maintenance). Next, a single-case design study was conducted with high school students with learning disabilities (Hoover, Kubina, & Mason, 2012). Results for number of elements written ranged from 68 to 84% PND at post-instruction, and from 50 to 60% PND at maintenance. In the two group experimental studies, Mason et al. (2013) a quasi-experimental study with struggling writers and Mason et al. (2017) a randomized controlled study for whole classroom instruction, large effects were found (ES = 0.81 to 1.11) for number of elements and writing quality. One study has examined the effects of SRSD for quick-writing with content area material; 78 sixth grade students in four science classes participated (Benedek-Wood et al., 2014). The TIDE (Topic sentence, main Ideas, Details, Ending) strategy was used for informational writing to summarize science concepts. Mean scores increased in each classroom, and visual analysis revealed improvements in data level. Disaggregated data for students with learning disabilities indicated that these students wrote higher-quality essays (mean baseline range = 0.78–2.43; mean treatment range = 3.25–6.00) with eight of ten students writing additional content details after instruction. In summary, SRSD has been associated with improved quick-writing performance for students with disabilities in grades 6–12. Students with executive-function difficulties who have participated in quick-writing research studies have expressed
192 8. Promoting EFs During the Writing Process favourable perceptions about instruction, specifically noting that ‘It helped me become a better writer. It got me thinking about how to organize my thoughts and work faster than when I started’ (Hoover, Kubina, & Mason, 2012). The improvement in number of elements written in these studies highlights the improvement of students’ executive functions. Students learned to set a goal and monitor (i.e. self-regulate) taught, and memorized, strategy steps.
Extended Writing Tasks Instruction that addresses difficulties in executive functions for extended writing tasks (a) in the writing processes (e.g. planning, composing, revision), and (b) for genre-specific writing (e.g. essays, reports) is recommended and has strong support in the research literature (Graham, McKeown, Kiuhara, & Harris, 2012). Teaching students strategies within a writing process framework facilitates student executive functions in each writing process component. SRSD has been tested in multiple studies for each of the three major writing genres (narrative, informative, and persuasive). A few selected SRSD studies, focused on teaching multiple strategies, is highlighted next. This will be followed by a description of scaffolding strategies for persuasive writing. Planning strategies. Two early SRSD randomized controlled trial studies examined the effects of teaching second-(Harris, Graham, & Mason, 2006) and third grade (Graham, Harris, & Mason, 2005) students two genre-specific planning strategies over an academic year. SRSD small group instruction was taught first for the POW +WWW (Who, When, Where), What= 2, How = 2 story writing strategy (7 story elements), followed by instruction for the POW + TREE opinion writing strategy. Tree included either five or eight parts—Topic sentence, Reasons, Explanations, Ending for third grade students or Topic sentence, Reasons, Ending, Examine for second grade students (see explanation in Scaffolding Instruction section to follow). In Graham, Harris, and Mason (2005), 73 third grade struggling writers were assigned to one of three groups—SRSD instruction, SRSD plus peer support to foster generalization and maintenance, or a Writing Workshop business-as-usual comparison group. Results indicated students who received SRSD or SRSD with peer support instruction spent more time writing both stories (ES = 2.62 and 1.10, respectively) and opinion papers (ES = 1.88 and 2.34 respectively) than the comparison group; quality was also significantly better for stories (ES= 2.42 and 1.90, respectively) and opinion papers (ES = 2.80 and 2.14, respectively). Although there were no statistically significant differences between the two SRSD instructional groups on story or opinion writing, students in the SRSD with peer support did show improved performance, over comparison, on two generalization measures for narrative and informative writing. Harris, Graham, and Mason’s (2006) study with 66 second grade struggling writers had similar results. Students in the two SRSD conditions spent more time writing stories (ES = 1.83 and 0.97, respectively) and opinions (ES = 1.10 and 1.21,
Supporting Executive Functions for the Writing Process 193
respectively), and wrote better quality stories (ES = 0.81 and 0.87, respectively) and opinions (ES = 1.31 and 1.63, respectively). The large effect size results in these two studies highlight remediating executive functions with young developing/struggling writers. There were no statistically significant differences between the two SRSD instructional groups on story or opinion writing; however, students in the SRSD with peer support did show improved performance, over comparison, on three generalization measures—narrative and informative writing and writing in the general education classroom. In post-instruction interviewing with second grade students, 70% of the students noted liking the story writing strategy; 88% noted liking the opinion writing strategy. Students also enjoyed several self-regulation procedures: (a) all enjoyed graphing, 50% noted that graphing helped them remember the strategy parts, (b) 85% enjoyed the self-statements they had created because they were good reminders and were positive. Planning plus sentence combining. Limpo and Alves (2013) investigated the effects of SRSD instruction with 146 fifth and sixth grade students, classrooms were randomly assigned to SRSD for opinion essay instruction, to SRSD for sentence combining in opinion essay writing instruction, or to control. The Portuguese version of TREE, ‘CRÊS’ (tell what you believe, give three or more reasons, explain each reason, and wrap it up) was used to teach students how to write an opinion. The mnemonic ‘DICA’ (what do you want to say, what is the idea, choose the best connective, and enrich with adjectives and adverbs) was used to support sentence combining. In addition to examining opinion essay quality, effects of instruction were examined at three written language levels—discourse (e.g. essay coherence), sentence (e.g. clause length), and word (e.g. vocabulary diversity). A positive effect on opinion essay quality was found for students receiving planning, and for students receiving sentence combining in opinion writing, when compared to control at post-test (ES = 1.05 and 0.72 respectively). Students receiving planning instruction wrote more coherent essays when compared to students receiving sentence combining in opinion writing instruction (ES = 0.76) and control students (ES = 0.77). When compared to students receiving planning instruction and students in control, students receiving sentence combining in opinion writing instruction demonstrated better sentence construction (ES = 1.01 and 0.86, respectively). When compared to students receiving planning instruction and students in control, students receiving sentence combining in opinion writing instruction demonstrated better vocabulary skills (ES = 0.52 and 1.14, respectively). Limpo and Alves note that results support their hypotheses that students will learn the skills taught and encourage practices for combining instructional approaches such as planning and sentence combining. This research certainly has implications for future research in effective practice for remediating executive functions deficits. Reading comprehension + planning strategies. Mason and colleagues conducted a series of studies looking at the effectiveness of using SRSD instruction to teach reading comprehension strategies and planning strategies for informational
194 8. Promoting EFs During the Writing Process text writing (see Mason, 2013). The first strategy, TWA (Think before reading, think While reading, think After reading), incorporates nine previously validated cognitive reading strategies into a framework for active reading comprehension before (think about author’s purpose, what you want to know, and what you want to learn), during (think about reading speed, linking knowledge, and rereading parts), and after reading (think about the main idea, summarizing information, and what you learned) (Mason, 2004). The second strategy, PLANS (Pick goals, List ways to meet goals, And make Notes, Sequence notes), explicitly supports students’ executive functions by establishing students’ personal product writing goals as well as methods for self-monitoring writing performance (Graham, MacArthur, Schwartz, & Page-Voth, 1992). Three steps are included: (1) Do PLANS, (2) Write and say more, and (3) Test goals. Using the notes written for the main ideas and details during reading with TWA, students complete PLANS by selecting goals for writing and revising an informative essay. In a randomized controlled trial study (Mason et al., 2013), 77 low-achieving fourth grade students were assigned to TWA or TWA + PLANS small group instruction, or business-as-usual control. Results indicated that after instruction, students receiving TWA instruction and students receiving TWA + PLANS instruction outperformed the control group on writing quality (ES = 0.83 and 1.15, respectively); information units in an oral retell (ES = 0.63 and 0.59, respectively) and a written retell (ES = 0.62 and 1.11, respectively); a standardized reading test (ES = 0.88 and 0.55, respectively); and semantic measures (i.e. number of diverse words, ES = 1.12 and 1.29, respectively). Syntactic measures, however, did not show statistically significant differences. Findings suggest that explicit language instruction for syntax within multicomponent instruction are needed to support students’ application of executive functions for writing better sentences. Scaffolding instruction . Strategy instruction should be scaffolded, based on students’ developmental oral and written language level, from simple to more complex constructs and strategies, Persuasion, for example, begins with developing opinions (author takes a position) and builds to persuasion (author convinces reader to agree) and argument (author uses claims for analysing a topic) that include counterclaims and refutations (see Table 8.1 for persuasive writing strategy step procedures). As noted previously, POW + TREE for opinion writing for young developing writers includes five TREE strategy steps: Topic sentence, Reasons—3 or more, Ending, Examine—do I have all my parts? (Harris et al., 2008). The final step, prompting students to self-monitor and then graph parts, reinforces young students’ executive functions development. For elementary-aged students with stronger writing skills, TREE is modified to include eight strategy steps by adding explanations to support reasons—Topic sentence, Reasons—3 or more, Explanations, Ending. Once students have demonstrated understanding of the critical elements needed for an opinion, instruction for more sophisticated opinion writing, and for persuasive/argument writing, can begin. Researchers note that when asking students to
Supporting Executive Functions for the Writing Process 195 Table 8.1 Persuasive writing strategies Persuasive strategy Strategy steps mnemonics 5-Part TREE T—Topic Sentence R—Reasons E—Ending E—Examine
Tell what you believe! 3 or more. Why do you believe this? Will your readers believe this? Number your reasons. Wrap it up right! Do you have all your parts? Yes?___No? ___
8-Part TREE T—Topic Sentence R—Reasons E—Explain E—Ending
Tell what you believe! 3 or more. Why do you believe this? Will your readers believe this? Say more about each reason. Wrap it up right!
10-Part TREE T—Topic Sentence R—Reasons E—Explain E—Ending STOP and DARE S—Suspend Judgement T—Take a Side
O—Organize P—Plan and D—Develop A—Add R—Reject E—End STOP, AIM, and DARE S—Suspend Judgement T—Take a Side
O—Organize P—Plan and A—Attract I—Identify
Tell what you believe! 3 or more. Why do you believe this? Will your readers believe this? Do you have a counter reason? Say more about each belief. Does the counter reason change your belief? Wrap it up right! Did you list ideas for both sides? Can you think of anything else? Try to write more. Another point you haven’t considered is . . . Think of possible arguments. Place a ‘+’ at the top of one box to show the side you will take in your essay. Put a star next to ideas you want to use. Choose at least ___ideas that you will use. Star ideas on both sides. Choose at least one argument that you can dispute. Number your ideas in the order that you will use them. Plan More as You Write Develop Your Topic Sentence Add Supporting Ideas Reject Arguments for the Other Side End with a Conclusion
Did you list ideas for both sides? Can you think of anything else? Try to write more. Another point you haven’t considered is . . . Think of possible arguments. Place a ‘+’ at the top of one box to show the side you will take in your essay. Put a star next to ideas you want to use. Choose at least ___ideas that you will use. Star ideas on both sides. Choose at least one argument that you can dispute. Number your ideas in the order that you will use them. Plan more as you write. Remember to use AIMS and DARE. Attract the reader’s attention. Identify the problem of the topic so the reader understands the issues. (continued)
196 8. Promoting EFs During the Writing Process Table 8.1 Continued Persuasive strategy Strategy steps mnemonics M—Map S—State and D—Develop A—Add R—Reject E—End
Map the context of the problem or provide background information needed to understand the problem. State the thesis so the premise is clear. Develop Your Topic Sentence Add Supporting Ideas. Remember to use transition words and elaborate. Reject Arguments for the Other Side End with a Conclusion. Provide a recommendation.
write the required counterarguments for high-level arguments prior to instruction, many students write equally to both sides of the argument, negating their position (e.g. Mason et al., 2017). Given this problem, and to meet the demands of writing in a short time frame, POW + TREE for writing a quick-write paper was developed to explicitly address writing an opinion with only one counterargument—TREE (Topic, Reasons—3 or more + one counter reason, Explanations—1 for each reason + a refute, Ending). For extended argumentative writing, however, a more sophisticated strategy should be taught. STOP and DARE, developed by De La Paz and Graham (1997), supports persuasive writing by teaching students two strategies for developing both sides of an argument and for picking a side to supporting an argument. In STOP, students: (a) Suspend judgement by listing reasons for each side, (b) Take a side after reviewing the listed reasons, (c) Organize ideas by ranking reasons from strongest to weakest, and (d) Plan more as you write. As students write, they apply DARE: (a) Develop a topic sentence, (b) Add supporting ideas, (c) Reject arguments for the other side, and (d) End with a conclusion. In a 1997 study for three students with learning disabilities, STOP and DARE was noted to be effective with 100% PND for number of essay parts (De La Paz & Graham). In 2012, Kiuhara et al. modified and extended STOP and DARE by adding AIMS—‘Attract the reader’s attention, Identify the problem of the topic so the reader understands the issues, Map the context of the problem or provide background information needed to understand the problem, and State the thesis so the premise is clear’ (p. 336). Effects of SRSD for STOP, AIMS, and DARE were evaluated in a single-case design study with six tenth through twelfth grade students with disabilities (see Table 8.1 for additional modification to strategies). PND, calculated by the first author of this chapter, indicated 100% PND for functional persuasive elements and 72% PND for quality following intervention. In after intervention interviewing, students noted being more confident and being able to write more and being more organized, all goals for supporting executive functions in SRSD instruction.
Technology with Embedded Self-Regulation 197
Technology with Embedded Self-Regulation Research has established that both technology and self-regulation interventions yield positive effects for students’ composing processes and writing skills (Williams & Beam, 2019). Use of technology with self-regulation to support executive functions has also been noted to support students’ motivation and interest in writing. Significantly, students report positive effects of technology and self-regulation for improving their writing (e.g. Mason & Kubina, 2011; White, Wepner, & Wetzel, 2003). It is therefore logical that technology with self-regulation be integral to any computer- or application-based intervention. Technology can be used to support students’ writing difficulties in both the mechanics of writing and written expression (Cutler & Graham, 2008). Researchers have found that technology-based writing strategies enabled students to become more independent, shifting the support from the teacher to the technology (Englert, Wu, & Zhao, 2005). Computer-based concept mapping programs such as Inspiration (https://www.inspiration-at.com/inspiration-maps/), for example, allow students to construct, link, and revise concepts. Speech-to-text programs (e.g. Dragon Home, https://www.nuance.com/dragon/dragon-for-pc/home-edition.html) translate verbal dictation into typed text with a word processing program such as Microsoft Word and Google Docs. Software programs (e.g. Co:Writer, https://cowriter.com/) offer many writing support features: word prediction, flexible spelling, speech-to- text, dictionaries, and text-to-speech. Five studies have investigated technology, with embedded self-regulation components, for improving students’ executive functions deficits in writing (Asaro-Saddler, Knox, Meredith, & Akhmedjanova, 2015; Bouck et al., 2010; Evmenova et al., 2016; Regan et al., 2017; Regan et al., 2018). The first two studies included self-regulatory prompting (e.g. embedded prompt to support attention to the task) within technology to support students’ attention to writing and to reinforce writing. In 2010, Bouck and colleagues conducted a single-case design study to investigate the efficacy of using a pentop computer, FLYPenTM (LeapFrog Technologies, 2005a, b), to increase the quantity and quality of writing with two high school students with intellectual disabilities and one student with a learning disability. The students wrote eight essays in 13 to 14 sessions over the course of five weeks. A Likert-type scale was used to score the quantity of each student’s writing. Teachers recorded the number of planning details, number of planning details related to a topic, number of switches of topic, number of paragraphs, number of words, number of capitalization errors, number of grammatical errors, and number of spelling errors. As noted from the researchers’ visual analysis, all three students increased number of words, sentences, and paragraphs during the intervention phase; however, they also increased capitalization and spelling errors. The researchers reported that the use of technology with embedded self-regulation strategies assisted students with organizing their writing and working more independently. The teacher and students also believed FLYPenTM to be beneficial.
198 8. Promoting EFs During the Writing Process Asaro-Saddler and colleagues (2015) conducted a 6-week study to investigate the effectiveness of First Author® software (developed by Dr Janet Sturm and distributed by Don Johnston Incorporated) for improving writing quantity and quality for ten high school students with autism spectrum disorder. First Author software supports planning, composing, and revising by including self-regulatory prompts to staying on task. Descriptive results indicated mixed results, with the total number of intelligible words written increasing from a mean of 41.4 to 69.2 during intervention stage and decreasing at post-test to a mean of 65.1. The teacher also noted improved student writing and decreased behavioural ‘outbursts’ during writing time (p. 114). Although each study indicated promise, the additive effects of including self- regulatory prompting with the technology/software was not noted in teacher or student interviewing. Evmenova, Regan and colleagues (Evmenova et al., 2016, Regan et al., 2017; Regan et al., 2018) conducted three studies to evaluate the effects of computer-based graphic organizers (CBGO) on students’ persuasive writing. The CBGO, created in Microsoft Word (Evmenova & Regan, 2012), embeds explicit self-regulated strategies (e.g. drop-down menu for selecting a personal goal) and self-regulated prompts to support students throughout the writing process: (a) Pick your goal; (b) Fill in the chart/ table below; (c) Copy the text in the orange box; (d) Paste the text into the box below; and (e) Self-evaluate (see Figures 8.1–8.3). Each study included students identified as having significant writing difficulties. In the first single-subject study, thirteen 30-minute sessions were implemented for 10 students with high-incidence disabilities (i.e. learning disabilities, emotional and behavioural disorders, attention deficit hyperactivity disorder, and autism spectrum disorder). Results indicated that students increased the number of words written (80% PND), the number of sentences written (90% PND), and the number of transition words written (100% PND). After instruction, results of interviews indicated that students noted that goal setting was important (7 out of 10 students), and that recording the length of their essay in self- evaluation component was helpful. The second single-case study, Regan et al. (2017), was conducted in inclusive, self-contained, and co-taught classrooms with 17 struggling sixth and seventh grade writers. Four 50-minute lessons were used to introduce CBGO, followed by 16 writing sessions. Number of words, sentences, and transition words written and writing quality were evaluated. All participants produced more sentences and used more transition words. In a third study, Regan et al. (2018) utilized a quasi-experimental group pretest/ post-test design to measure the effectiveness of a mobile-based graphic organizer (i.e. MBGO on iPAD) with 94 middle school students in inclusion classes. The experimental group contained 43 students, of whom 26 were identified as struggling writers, while the control group contained 51 students, of whom 20 were identified as struggling writers. The participants were provided with four 30-to 40-minute instructional sessions and five practice sessions. Results indicated that all students receiving the intervention, when compared to control, improved in writing quality (ES = 0.063), number of sentences written (ES = 0.011), number of words written
Figure 8.1 Students use a drop menu to select a personal goal for writing. Retrieved from https://wego.gmu.edu/app/graphorg_sample1.html
Figure 8.2 A self-regulatory prompt is used for monitoring strategy use. Retrieved from https://wego.gmu.edu/app/graphorg_sample1.html
Conclusion: Implications 201
Figure 8.3 Students are prompted to evaluate their essay by counting words, sentences, and persuasive elements (e.g. reasons and examples). Retrieved from https://wego.gmu.edu/app/graphorg_sample1.html
(ES = 0.026), and transition words (ES = 0.677). Disaggregated scores for struggling writers indicated differing effects: writing quality (ES = 0.037), number of sentences written (ES = 0.013), number of words written (ES = 0.001), and transition words (ES = 0.80). Post-instruction interviews indicated that students like the MBGO, one student noting, ‘... it helps me like go through the steps that I’m writing about’ (p.11). Although all students writing improved after instruction, researchers noted that educators should consider the context of the classroom environment when implementing technology-based interventions. For example, teachers noted that students became distracted when a large group or whole class was using technology in the classroom.
Conclusion: Implications The literature reviewed in this chapter described the effectiveness of (a) strategy instruction with mnemonics to support memory and (b) procedures for fostering students’ self-regulation, for addressing students’ executive functions deficits in writing. Many of the interventions were situated in well-established theoretical-based
202 8. Promoting EFs During the Writing Process perspectives. The selected interventions, for example, targeted the control mechanisms—attention, working memory, and executive control for the writing process—noted in Graham’s (2018) Writer(s)-within-Community model (WWC). The research evidence in improving writing performance is strong for these mechanisms and is supported by our review of selected literature in this chapter and prior meta-analysis (e.g. Gillespie & Graham, 2014; Graham & Perin, 2007). Multicomponent studies, specifically Limpo and Alves (2013) and Mason et al. (2013), point to the need for including explicit sentence instruction within interventions for extended written expression tasks such as essay writing. In Mason et al., despite an intensive intervention for both reading comprehension and writing, and gains across reading comprehension, writing, and vocabulary measures, students had no significant gains in sentence writing measures. Limpo and Alves noted that students learned the specific skills taught in their study, either sentence combining or planning, and recommended that both skills should be explicitly taught in conjunction. Interventions that embed strategies, self-regulation, and self-regulatory prompting with technology have great promise (e.g. Asaro-Saddler et al., 2015; Evmenova et al., 2016). These interventions, as of this writing, have not been evaluated in randomized controlled study, so effects compared to other instructional approaches are unknown. In addition, the feasibility of technology for writing across the curriculum in schools, without the support of researchers, needs to be addressed. We look forward to seeing this line of research develop, especially as it applies to students with executive functions deficits. The majority of reviewed studies were conducted with individual students (e.g. Bouck et al., 2010), student pairs (e.g. Saddler & Graham, 2005), and small groups (e.g. Mason et al., 2013). Only three of the reviewed studies were conducted in the whole classroom (Benedek-Wood et al., 2014; Limpo & Alves, 2013; Mason et al., 2017). The sociocultural context critical for writing development (Bereiter & Scardamalia, 1987; Zimmerman & Risemberg,1997); however, was limited in studies’ research design, with only two studies explicitly examining sociocultural context, specifically the effects of peer support (Graham, Harris, & Mason, 2005; Harris, Graham, & Mason, 2006). In both studies, results indicated that peer support had an impact only on measures of generalization. Given this finding and the noted difficulties for students’ attention in Regan et al. (2018), more research is needed to determine how students with executive-function deficits can fully benefit from collaborative social environments. Finally, systematic assessment of students’ executive functions should be considered in future research (see Chapter 4 of this volume). In post-instruction interviews with teachers and students, in many of the reviewed studies, self-regulation components, mnemonics, and strategies were all noted to be helpful. What is not known is (a) how students have integrated executive functions into other learning tasks, or (b) how improving executive functions sustains over time as students writing expectations increase throughout schooling.
References 203
References Asaro-Saddler, K., Knox, H.M., Meredith, H., & Akhmedjanova, D. (2015). Using technology to support students with autism spectrum disorders in the writing process: a pilot study. Insights into Learning Disabilities, 12, 103–19. Baker, S.K., Chard, D.J., Ketterlin-Geller, L.R., Apichatabutra, C., & Doabler, C. (2009). Teaching writing to at-risk students: the quality of evidence for self-regulated strategy development. Exceptional Children, 75, 303–18. Beals, V.L. (1983). The Effects of Large Group Instruction on the Acquisition of Specific Learning Strategies by Learning Disabled Adolescents. Unpublished doctoral dissertation, University of Kansas, Lawrence, KS. Benedek-Wood, E., Mason, L.H., Wood, P., Hoffman, K., & MacGuire, A. (2014). SRSD for quick writing in four middle school science classrooms. Learning Disabilities: A Contemporary Journal, 12, 69–92. Bereiter, C., & Scardamalia, M. (1987). The Psychology of Written Composition. Hillsdale, NJ: Lawrence Erlbaum. Berninger, V.W., & Abbott, R.D. (2010). Listening comprehension, oral expression, reading comprehension, and written expression: related yet unique language systems in grades 1, 3, 5, and 7. Journal of Educational Psychology, 102, 635–51. Bouck, E.C., Doughty, T.T., Flanagan, S.M., Szwed, K., & Bassette, L. (2010). Is the pen mightier? Using pentop computers to improve secondary students’ writing. Journal of Special Education Technology, 25, 33–47. Cutler, L., & Graham, S. (2008). Primary grade writing instruction: a national survey. Journal of Educational Psychology, 100, 907–19. Datchuk, S.M. (2016). Writing simple sentences and descriptive paragraphs: effects of an intervention on adolescents with writing difficulties. Journal of Behavioral Education, 25, 166–88. Datchuk, S.M. (2017). A direct instruction and precision teaching intervention to improve the sentence construction of middle school students with writing difficulties. Journal of Special Education, 51, 62–71. Datchuk, S.M., & Kubina, R.M. (2017). A writing intervention to teach simple sentences and descriptive paragraphs to adolescents with writing difficulties. Education and Treatment of Children, 40, 303–26. Datchuk, S.M., Kubina, R.M., & Mason, L.H. (2015). Effects of sentence instruction and frequency building to a performance criterion on elementary-aged students with behavioral concerns and EBD. Exceptionality, 23, 34–53. Datchuk, S.M., & Rodgers, D.B. (2018). Text writing within simple sentences: a writing fluency intervention for students with high-incidence disabilities. Learning Disabilities Research & Practice, 34, 23–34. De La Paz, S. (2001). Teaching writing to students with attention deficit disorder and specific language impairment. Journal of Educational Research, 95, 37–47. De La Paz, S., & Graham, S. (1997). Effects of dictation and advanced planning instruction on the composing of students with writing and learning problems. Journal of Educational Psychology, 89, 203–22. Eads, J.R. (1991). Classroom Teacher Mediated Generalization of a Sentence Writing Strategy to the Regular Classroom by Nine Middle School Students with Learning Disabilities. Unpublished educational specialist thesis, Northeast Missouri State University, Kirksville, MO. Englert, C.S., Wu, X., & Zhao, Y. (2005). Cognitive tools for writing: scaffolding the performance of students through technology. Learning Disabilities Research & Practice, 20, 184–98. Evmenova, A.S., & Regan, K. (2012). Project WeGotIT! Writing Efficiently with Graphic Organizers: Teachers Integrating Technology. Technology and Media Services for Individuals
204 8. Promoting EFs During the Writing Process with Disabilities Stepping- Up Technology Implementation Grant, Office of Special Education, Washington, DC. Evmenova, A.S., Regan, K., Boykin, A., Good, K., Hughes, M., MacVittie, N., . . . & Chirinos, D. (2016). Emphasizing planning for essay writing with a computer-based graphic organizer. Exceptional Children, 82, 170–91. Fidalgo, R., Torrance, M., & García, J.N. (2008). The long-term effects of strategy-focused writing instruction for grade six students. Contemporary Educational Psychology, 33, 672–93. Gillespie, A., & Graham, S. (2014). A meta-analysis of writing interventions for students with learning disabilities. Exceptional Children, 80, 454–73. Gillespie Rouse, A., & Kiuhara, S.A. (2017). SRSD in writing and professional development for teachers: practice and promise for elementary and middle school students with learning disabilities. Learning Disabilities Research & Practice, 32, 180–8. Graham, S. (2018). A revised writer(s)-within-community model of writing. Educational Psychologist, 53, 258–79. Graham, S., Collins, A.A., & Rigby-Wills, H. (2017). Writing characteristics of students with learning disabilities and typically achieving peers: a meta-analysis. Exceptional Children, 83, 199–218. Graham, S., & R. Harris, K. (2000). The role of self-regulation and transcription skills in writing and writing development. Educational Psychologist, 35, 3–12. Graham, S., Harris, K.R., & Mason, L. (2005). Improving the writing performance, knowledge, and self-efficacy of struggling young writers: the effects of self-regulated strategy development. Contemporary Educational Psychology, 30, 207–41. Graham, S., Harris, K.R., & McKeown, D. (2013). The writing of students with LD and a meta-analysis of SRSD writing intervention studies: redux. In L. Swanson, K.R. Harris, & S. Graham (Eds.). Handbook of Learning Disabilities (2nd Ed.). New York, NY: Guilford Press. Graham, S., MacArthur, C., Schwartz, S., & Page-Voth, V. (1992). Improving the compositions of students with learning disabilities using a strategy involving product and process goal setting. Exceptional Children, 58, 322–34. Graham, S., McKeown, D., Kiuhara, S., & Harris, K.R. (2012). A meta-analysis of writing instruction for students in the elementary grades. Journal of Educational Psychology, 104, 879–96. Graham, S., & Perin, D. (2007). A meta-analysis of writing instruction for adolescent students. Journal of Educational Psychology, 99, 445. Harris, K.R., Graham, S., MacArthur, C., Reid, R., & Mason, L.H. (2011). Self-regulated learning processes and children’s writing. In B. Zimmerman & D. Schunk (Eds.). Handbook of Self-regulation of Learning and Performance, pp. 187–201. Danvers, MA: Routledge. Harris, K.R., Graham, S., & Mason, L.H. (2006). Self-regulated strategy development for 2nd- grade students who struggle with writing. American Educational Research Journal, 43, 295–340. Harris, K.R., Graham, S., Mason, L.H., & Friedlander, B. (2008). Powerful Writing Strategies for All Students. Baltimore, MD: Brooks Publishing Co. Inc. Harris, K.R., Graham, S., Mason, L.H., McKeown, D., & Olinghouse, N. (2018). Self-regulated strategy development in writing: a classroom example of developing executive functioning and future directions. In L. Meltzer (Ed.), Executive Functioning in Education (pp. 326–56). New York, NY: Guilford Press. Hayes, J.R., & Flower, L.S. (1986). Writing research and the writer. American Psychologist, 41, 1106. Hayes, J.R., & Flower, L.S. (1996). A new framework for understanding cognition and affect in writing. In M. Levy & S. Ransdell (Eds.). The Science of Writing: Theories, Methods, Individual Differences, and Applications (pp. 1–27). Mahwah, NJ: Lawrence Erlbaum.
References 205 Hoover, T., Kubina, R., & Mason, L.H. (2012). Effects of quick writing instruction for high school students with learning disabilities. Exceptionality, 20, 20–38. Huck, S.W. (2000). Reading Statistics and Research (3rd Ed.). New York, NY: Longman. LeapFrog Technologies (2005a). FLY Pentop Computer. [Educational software] Emeryville, CA: LeapFrog Enterprises, Inc. LeapFrog Technologies (2005b). FLY Through Writing: Master the Steps to Writing Essays, Stories, and Poems. [Educational software] Emeryville, CA: LeapFrog Enterprises, Inc. Limpo, T., & Alves, R.A. (2013). Teaching planning or sentence-combining strategies: effective SRSD interventions at different levels of written composition. Contemporary Educational Psychology, 38, 328–41. Limpo, T., & Alves, R.A. (2018). Tailoring multicomponent writing interventions: effects of coupling self-regulation and transcription training. Journal of Learning Disabilities, 51, 381–98. Mason, L.H. (2004). Explicit self-regulated strategy development versus reciprocal questioning: effects on expository reading comprehension among struggling readers. Journal of Educational Psychology, 96, 283–96. Mason, L.H. (2013). Teaching students who struggle with learning to think before, while, and after reading: effects of SRSD instruction. Reading and Writing Quarterly 29, 124–44. Mason, L.H., & Benedek-Wood, E. (2014). Writing instruction for the inclusive classroom. J. McLesky, N.L. Waldron, F. Spooner, & B. Algozzine (Eds.) Handbook of Research and Practice for Effective Inclusive Schools (pp. 247–60). Danvers, MA: Routledge. Mason, L.H., Dunn Davison, M., Hammer, C.S., Miller, C.A., & Glutting, J. (2013). Knowledge, writing, and language outcomes for a reading comprehension and writing intervention. Reading and Writing: An Interdisciplinary Journal, 26, 1135–58. Mason, L.H., & Graham, S. (2008). Writing instruction for adolescents with learning disabilities: programs of intervention research. Learning Disabilities Research & Practice, 23, 103–12. Mason, L.H., & Kubina, R.M. (2011). Developing writing fluency for adolescents with disabilities. In T.E. Scruggs & M.A. Mastropieri (Eds.). Intervention and Assessment: Advances in Learning and Behavioral Disabilities (vol. 2, pp. 296–319). Bingley, UK: Emerald. Mason, L.H., Kubina, R.M., Kostewicz, D., Mong Cramer, A., & Datchuk, S. (2013). Improving quick writing performance of middle school struggling learners. Contemporary Educational Psychology, 38, 236–46. Mason, L.H., Kubina, R., & Taft, R. (2011). Developing quick writing skills of middle school students with disabilities. Journal of Special Education, 44, 205–20. Mason, L.H., Mamlin, N., & Stewart, K. (2019). Evidence-based writing intervention: three tiers of instruction for elementary students. In P.C. Pullen & M.J. Kennedy (Eds.). Handbook on Response to Intervention (pp. 218–32). New York, NY: Routledge. Mason, L.H., Mong Cramer, A., Garwood, J., Varghese, C., Hamm, J., & Murray, A. (2017). The efficacy of SRSD instruction for developing writers with and without disabilities in rural schools: a randomized controlled trial. Rural Special Education Quarterly, 36, 168–79. Mason, L.H., & Reid, R. (2018). Individual and group differences in self-regulation of learning and performance self-regulation: implications for individuals with special needs. In D. Schunk & J. Greene (Eds.), Handbook of Self-regulation of Learning and Performance (2nd Ed.). New York, NY: Routledge. Mason, L.H., Reid, R., & Hagaman, J. (2016). L’enseignement Explicite de la Lecture et de L’écriture: 40 Leçons Pour Hisser Les Élèves Vers La Réussite. Adaptation: Lyne Legault. Quebec: Cheneliere Education. Mason, L.H., Reid, R., & Hagaman, J. (2012). Building Comprehension in Adolescents: Powerful Strategies for Improving Reading and Writing in Content Areas. Baltimore, MD: Brooks Publishing Co. Inc.
206 8. Promoting EFs During the Writing Process Myles, B.S., & Simpson, R.L. (2002). Asperger syndrome: an overview of characteristics. Focus on Autism and Other Developmental Disabilities, 17, 132–7. National Governors Association Center for Best Practices & Council of Chief School Officers (2010). English Language Arts Standards, Writing, Grade 11–12. Washington, DC: Author. Pennington, R., Flick, A., & Smith-Wehr, K. (2018). The use of response prompting and frames for teaching sentence writing to students with moderate intellectual disability. Focus on Autism and Other Developmental Disabilities, 33, 142–9. Reid, R., Trout, A.L., & Schwartz, M. (2005). Self-regulation interventions for children with attention deficit/hyperactivity disorder. Exceptional Children, 71, 361–77. Regan, K., Evmenova, A.S., Boykin, A., Sacco, D., Good, K., Ahn, S. Y., MacVittie, N., & Hughes, M.D. (2017). Supporting struggling writers with class-wide teacher implementation of a computer-based graphic organizer. Reading & Writing Quarterly, 33, 428–48. Regan, K., Evmenova, A.S., Good, K., Legget, A., Ahn, S.Y., Gafurov, B., & Mastropieri, M. (2018). Persuasive writing with mobile-based graphic organizers in inclusive classrooms across the curriculum. Journal of Special Education Technology, 33, 3–14. Rogers, L., & Graham, S. (2008). A meta-analysis of single subject design writing intervention research. Journal of Educational Psychology, 100, 879–906. Saddler, B. (2012). Teacher’s guide to effective sentence writing. Guilford Press. Saddler, B., Behforooz, B., & Asaro-Saddler, K. (2008). The effects of sentence-combining instruction on the writing of fourth-grade students with writing difficulties. The Journal of Special Education, 42(2), 79–90. Saddler, B., & Graham, S. (2005). The effects of peer-assisted sentence-combining instruction on the writing performance of more and less skilled young writers. Journal of Educational Psychology, 97, 43–54. Sawyer, R., Graham, S., & Harris, K.R. (1992). Direct teaching, strategy instruction, and strategy instruction with explicit self-regulation: effects on the composition skills and self- efficacy of students with learning disabilities. Journal of Educational Psychology, 84, 340–52. Schmidt, J.L., Deshler, D.D., Schumaker, J.B., & Alley, G.R. (1988). Effects of generalization instruction on the written language performance of adolescents with learning disabilities in the mainstream classroom. Reading, Writing, and Learning Disabilities, 4, 291–309. Schumaker, J.B., & Deshler, D.D. (2003). Can students with LD become competent writers? Learning Disabilities Quarterly, 26, 129–41. Scruggs, T., & Mastropieri, M. (2001). How to summarize single-participant research: ideas and applications. Exceptionality, 9, 227–44. Taft, R., & Mason, L.H. (2011). Examining effects of writing interventions: spotlighting results for students with primary disabilities other than learning disabilities. Remedial and Special Education, 32, 359–70. WeGotIT! Available at: https://wego.gmu.edu/app/graphorg_sample1.html White, E.A., Wepner, S.B., & Wetzel, D.C. (2003). Accessible education through assistive technology. THE Journal (Technological Horizons in Education), 30, 24–32. Williams, C., & Beam, S. (2019). Technology and writing: review of research. Computers & Education, 128, 227–42. Zimmerman, B.J., & Risemberg, R. (1997). Research for the future: becoming a self-regulated writer: a social cognitive perspective. Contemporary Educational Psychology, 22, 73–101.
9 Executive Functions in Skilled Writers Thierry Olive
Why Are Executive Functions Involved in Writing? Executive functions are critical for efficient functioning in daily life. They are top- down mechanisms that supervise cognitive functioning. Different definitions and different subprocesses of executive functions can be found in the literature. For example, Miyake et al. (2000) proposed at least three separate major executive functions: inhibition, updating of working memory, and shifting mental sets. A more recent proposal by Diamond (2013) also includes three core executive functions: inhibitory control (selective attention, sustained attention, and response inhibition), working memory (holding information in mind while processing it), and cognitive flexibility (being able to switch between mental sets, processes, or perspectives, and to adjust goals) which builds on the two other functions. Despite slight differences in labels and scope of the executive functions, all authors share the same assumption that executive functions play an important role in regulating dynamics of human cognition (see Chapter 2 of this volume). Of importance for the present purpose, executive functions are particularly involved in complex and long cognitive activities. Such activities indeed require intensive supervision of their unfolding, as any activity that unfolds over time requires holding in mind previous information, future goals, current and transient mental representations, and coordinating flow and course of processing. In addition, as Diamond (2013) notices, this is necessary to relate and integrate information, to consider alternatives, in other words to create meaning and to be creative as elaborated texts require. As a consequence, executive functions are likely to intervene during text composition by skilled writers. Experimental data on executive functions in skilled writers are very scarce. Therefore, the role of executive functions in these writers can only be inferred from indirect but related empirical findings, or from analytical or theoretical descriptions of the cognitive demands of writing. For example, involvement of executive functions in skilled writing may arise from the cognitive complexity of writing. When composing a text, skilled writers have indeed to flexibly (i.e. thoughtfully) apply and coordinate a variety of resources, including strategic decision-making and planning processes, knowledge, and writing processes (Graham, Harris, & Olinghouse, 2007). In addition, writing engages multiple cognitive, linguistic, and motoric processes which Thierry Olive, Executive Functions in Skilled Writers In: Executive Functions and Writing. Edited by: Teresa Limpo and Thierry Olive, Oxford University Press. © Oxford University Press 2021. DOI: 10.1093/oso/9780198863564.003.0009
208 9. Executive Functions in Skilled Writers operate at different levels of mental representation. For instance, planning and structuring the text content involves processes for retrieving and organizing knowledge, therefore operating on conceptual and semantic mental representations. It also requires formulating segments of language by selecting syntactic frames, accessing the mental lexicon, finding the correct spelling of the words. Formulating a text therefore engages linguistic knowledge and representations. Prepared segments of language are transcribed by handwriting or by typing; both processes involve motor representations of letters. Finally, writers also need to control the content of their production by assessing adequacy of the text that is still in their working memory or by revising the text they have already written. Another argument in favour of an important involvement of executive functions in writing is that writing is one of the most effortful activities in which adults engage. Effortful control indeed overlaps with self-regulation skills and with top-down control of attention, two other concepts used to refer to executive supervision, and particularly to inhibitory control (Diamond, 2013). For instance, Piolat, Olive, and Kellogg (2005; see also Kellogg, 1994) compared cognitive effort (indexed by length of secondary reaction times) associated to different tasks. They showed that writing (as well as note taking) appears more demanding than reading a text or sentences, than game playing in chess by novice players, or than incidental or intentional learning of syllables. This makes that writers are considered to be in permanent overload (Flower & Hayes, 1980). Such an overload is mainly due to the important demands of the high-level processes of planning and revising. Being more related to the mechanics of writing, than to text composition, low-level processes such as handwriting or spelling are indeed more prone to become automatic (Berninger & Swanson, 1994; McCutchen, 2000). Given that high-level writing processes are in direct relation with the expressive and communicative components of writing, learning to write, and becoming a skilled writer cannot lead to general automatization of the writing processes. Rather, planning or revising require deliberate control from the writer, and composing requires constant control from the writer to assess whether the text is relevant to the goals of the writing tasks. Thus, learning to write should not lead to an automatization of writing processes, but rather to an amplification of performance (Kellogg, 1994). In other words, while learning and practising, writers have to keep their performance at the highest level, therefore devoting high attention to unfolding of the writing processes. In Kellogg’s (2008) terms, this means that the writers’ ‘central goal is to gain executive control over cognitive processes so that one can respond adaptively to the specific needs of the task at hand’ (pp. 2–3). A final argument that can be raised in favour of involvement of executive functions in skilled writers is that the various writing processes and subprocesses have to be orchestrated throughout the writing process by deciding their order, and by monitoring their concurrent coordination. It is indeed admitted that coordination of writing processes is flexible and can change in a continuum between sequential and parallel supervision of the writing processes (Olive, 2014). This point will be illustrated in
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detail in ‘Executive Demands for Orchestrating the Writing Processes’, which deals with orchestration of the writing processes. It can nevertheless be retained that activating concurrently multiple processes requires intensive controlling of how attention is shared between writing processes. Additionally, because coordination of writing processes is flexible, it requires constant supervision and control to adapt the flow of processing and transmit information in a timely manner between different processes. As can be figured out from this brief introduction, the involvement of executive functions of writing presumably comes from the high processing demands of the writing processes, and particularly those planning and revising place on working memory, but also from a need to control processing: writing indeed requires simultaneously juggling or coordinating multiple constraints and low-and high-level cognitive processes. To account for the high demands of writing, Kellogg (1996) and McCutchen (1996) developed two conceptions of working memory in writing. The next section present how these two models of working memory depict the role of executive functions. The precise relation between executive functions and the main writing processes in skilled writers is addressed later on. However, because executive functions are not only devoted to control operations of each writing process but also to supervise unfolding of writing, involvement of the executive functions also stems from orchestration of the multiple writing processes. The chapter hence addresses how the multiple writing processes are coordinated towards the end of the chapter and how such modes of coordination may involve executive functions, particularly with parallel processing, as it requires high control for supervising the processing flow.
What Do Models of Writing and Working Memory Say About Executive Functions? Working memory entails the ability to temporarily store and simultaneously process information (for a review, see Baddeley & Hitch, 2001). Working memory thus provides a temporary memory register for either storing content retrieved in the environment or from long-term memory, or for transient information that results from operations of the writing processes. For example, while writers are transcribing a sentence, they may need to keep in mind an idea that they just thought about or to memorize temporarily a long sentence while beginning to write it down. Similarly, when revising, writers have to compare the text they have already produced with the mental representation of the text they intend to compose. Working memory is therefore involved for regulating processing of knowledge necessary to compose a text. It is the place where writing processes are activated and coordinated, and where the representation(s) of the developing text is constructed and updated. In sum, working memory is the cognitive space where writing operations take place. The relationship between working memory and writing is well documented (e.g. Beninger & Swanson, 1994; Gathercole & Pickering, 2000a, 2000b; 2000; Olive,
210 9. Executive Functions in Skilled Writers 2004) and two models of working memory in writing illustrate this relation: the model proposed by Kellogg (1996) which relies on Baddeley’s (1986) componential model of working memory, and the capacity model of writing adapted by McCutchen (1996, 2000) from the capacity model of comprehension described by Just and Carpenter (1992). Although conceptually different, these two models share the same assumption about working memory: it is a limited-capacity system (or function) that temporarily stores information and supervises processing.
The Componential Model of Working Memory in Writing Kellogg’s (1996) model, which focuses on the role of working memory in skilled writers, depicts the relationship between each writing process and the different components in terms of Baddeley’s (1986) model of working memory, that is, the phonological loop, the visuospatial sketchpad, and the central executive. This model describes three writing components, each involving different writing processes. Formulating which includes planning and translating, execution that requires programming and executing movements, and monitoring which involves reading and editing. Interestingly, editing does not intervene in modifying a text but send a signal to the process that is responsible to the error in order it tries to provide a correct solution to the diagnosed problem. All these components impose short-term memory demands on either the phonological loop or the visual spatial sketchpad for storing transient information. The model also points out that formulating and monitoring place important demands on the central executive, as it is evidenced by the high cognitive effort devoted to each of these processes (Olive, 2004). More specifically, during process planning (for the distinction between process planning and content planning see Hayes & Nash, 1996), the central executive would be engaged when defining action plans, goals and subgoals, and during content planning when retrieving information from long-term memory. The cognitive effort of translating also indicates that formulating language requires the central executive. It would be particularly involved in lexical retrieval and when creating syntactic strictures according to Kellogg (1996). Finally, revision is expected to also pose high demands on the central executive, and particularly error detection. Indeed, when detecting errors in a text, writers must find inaccuracies which can be very different in nature and therefore must change the focus of their attention to different aspects of the text. Kellogg et al. (2013) proposed more specific links between the writing processes and the different executive functions. These authors suggest that coordination of writing processes during writing depends on flexibility and that inhibition is necessary when retrieving content from long-term memory to select relevant knowledge. Similarly, inhibition is required when formulating language for inhibiting lexical items and syntactical structures that writers do no judge relevant. Another executive function involved in writing is updating of working memory content, at least to keep the evolving text representation updated. Kellogg et al. (2013) also propose to
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investigate how individual differences in the different executive functions contribute to overall writing performance. Finally, as they suggest, the 1996 model ‘could be profitably extended by fractionating the central executive into specific executive functions’ (p. 167). Indeed, distinguishing the different facets of executive functioning (inhibition, working memory or updating, flexibility) should make it possible to better clarify their links with the various writing processes as they are likely to involve these functions in different ways. This issue will be dealt with in section ‘Executive Functions and the Writing Processes of Skilled Writers’ on the relationship between writing processes and the various executive functions.
The Capacity Model of Working Memory in Writing By contrast to Kellogg’s proposals, McCutchen’s (1996, 2000) claims about working memory are more related to novice writers but her developmental perspective also applies to skilled writers. The capacity theory of writing she proposed is a direct transposition of Just and Carpenter’s (1992) model of working memory in comprehension to writing. This model aims at explaining how the limited capacity of working memory constraints text comprehension. According to Just and Carpenter, working memory is a single and general pool of cognitive resources (i.e. attention or activation) that is limited and that has to be shared between the processing and short-term storage demands related to text processing. Individual differences in working memory capacity for language comprehension therefore results from high processing demands (e.g. in readers being less skilled for decoding or for processing syntactic ambiguities) which may prevent interactions between the various processing involved in comprehension. In McCutchen’s perspective, the limited working memory (WM) resources have also to be shared among the multiple processes that are required at a given time when composing a text. They also have to be shared between the short-term storage and processing demands of these processes. In this way, the difficulties encountered when composing a text, especially by young writers, would therefore be related to the high demands of the writing processes in this limited-capacity processing system, which, as in comprehension, may prevent simultaneous consideration of the constraints of each writing process. Therefore, efficient writing requires freeing working memory resources by automatizing low-level processes such as transcription and spelling to allow interactions between the high-level writing processes. This is supported by McCutchen, Covill, Hoyne, and Mildes’ (1994) study that showed that writers with high working memory capacity produced better texts than writers with low working memory. Importantly, this difference was less predicted by working memory capacity when it was assessed with a reading span task, which relied less on efficiency of sentence generation than when assessed with a writing span task (memorizing words and composing sentences from this words). Writing span was even more closely related to writing quality when the sentences to produce in this task had to be coherently tied to form a story. In addition, writing span was related to speed of lexical retrieval.
212 9. Executive Functions in Skilled Writers McCutchen et al. concluded that greater efficiency in translating results in freeing up working memory capacity, and thus, in better writing performance. Development of handwriting also illustrates well how a change in efficiency of one writing process can affect another one (see Berninger & Swanson, 1994). For example, the high demands of handwriting in children or of cursive uppercase handwriting in adults reduced performance at a written serial recall task compared to oral serial recall (Bourdin & Fayol, 1994). Similar results were found with adults who perform a writing span task (memorizing increasing lists of words and composing text with these words) based on words that were semantically related or not (Bourdin & Fayol, 2001). Specifically, the number of ideas and coherence of the texts were lower when the words were few related and when the texts were handwritten rather than spoken. As the authors suggested, little semantic relatedness between words imposed more demand on ideas elaboration, which resulted in more difficulties for storing and integrating in a text the memorized words. By providing more available working memory capacity, automatization provides opportunities for interactions among writing processes (McCutchen, 1988, 1994). This is of major importance for McCutchen’s perspective, as she considers writing to be interactive in nature given that writing subskills are not independent and need to interact. However, such interactions can occur only when enough working memory resources are available. McCutchen therefore introduces a distinction between fluency and automatization: when writing processes are sufficiently efficient, fluency is the result of constant interactions. Such fluency cannot occur with automatized processes as automatization usually leads to apparent encapsulation, therefore preventing interactions. In sum, but in terms different than those used by Kellogg, by showing the importance of interactions between processes McCutchen puts the emphasis on deliberate control in skilled writers, and particularly on the role of metacognition or self-regulation (see Chapter 3 by Graham). Executive functions are not described in McCutchen’s model. For instance, the terms ‘executive functions’ are absent in the 1996 and 2000 papers. So, how does this model consider supervision of writing, for example shifting between writing (sub) processes? As it is the case for the capacity theory of comprehension (Just & Carpenter, 1992), attentional mechanisms are at the core of supervision, and allocation of attention is under the guidance of high-level planning and decision-making processes. As shown by Diamond (2013), attentional control and executive functions are interchangeable terms that often overlaps in the literature. However, in McCutchen’s model, attention is considered as a unitary resource, while executive control is now admitted to rely on different latent functions (Diamond, 2013; Miyake et al., 2000). To conclude this section, the two models of working memory and writing that are present in the literature do not really specify the role of executive functions in writing. This is particularly the case with McCutchen’s model. In the last update of the componential model, Kellogg et al. (2013) however make more proposals about the role of executive functions in skilled writers. They suggest integrating the separability of executive functions by investigating how the different functions intervene in writing,
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and how they contribute to overall writing performance. The following section addresses this point by detailing the links between each writing process and the various executive functions.
Executive Functions and the Writing Processes of Skilled Writers If theoretical claims about executive functions in skilled writers are rare, published research on the engagement and role of executive functions in these writers is even more rare. Several studies have however been conducted in children learning to write, underscoring the role of the core executive functions in writing performance of beginning writers (e.g. Cordeiro, Limpo, Olive, & Castro, 2019). Writing indeed appears more related to the attentional functions of working memory than to short-term storage of information in novice writers (Vandenberg & Swanson, 2007). Additionally, different facets of executive functioning are related to writing of poor and good novice writers composing a narrative (Hooper et al., 2002; see Chapter 6 of this volume). For example, inhibition and planning contribute to integration of writing and reading in third to fifth graders (Altemeier, Jones, Abbott, & Berninger, 2006). The different executive functions also contribute directly and indirectly to narrative composition in fourth graders. In Drijbooms, Groen, and Verhoeven’s (2015) study, inhibition and updating, but not planning, contributed directly to the length of narratives, and indirectly, through handwriting, to text length, syntactic complexity, and story content. To account for the intervention of executive function in beginning writing, Berninger and Amtmann (2003) and Berninger and Winn (2006) proposed the simple view and the Not-So-Simple view of writing. Both these models consider three core skills, transcription, text generation, and executive functions, which are constrained by working memory limitations. In addition to self-regulation processes, executive functions include planning and reviewing. These high-level writing processes may indeed be conceived as driving writing, and consequently as triggering executive processes. Turning back to skilled writers, despite the little available research, one possible way to examine executive functions in skilled writers is through the cognitive effort of the different writing processes which may inform of their respective executive demands. The level of cognitive effort devoted to a particular process or task directly depends on computational complexity1 of the task, practice, and on writers’ individual characteristics (e.g. writing apprehension, emotional state), all factors which intervene in executive control. In this perspective, cognitive effort would correspond to the amount of attention devoted to the writing processes, and would consequently reflect 1 Computational complexity refers to inherent difficulty of cognitive tasks. In language, it refers to computational efficiency of a language system (see how Chomsky tried to reduce computational complexity in his theory, e.g. Chomsky, 2000). Applied to the field of language production, it can be conceived as the number of processing step that is required to process a linguistic information. See Robinson’s (2007) and Skehan’s (1998) theories for task complexity issues in second language learning.
214 9. Executive Functions in Skilled Writers general involvement of executive functions. Cognitive effort of the writing processes has been mainly assessed with the triple task technique that associates secondary reaction times (i.e. collected while composing a text) to verbalization about writing processes (more details about this method can be found in Olive, Kellogg, & Piolat, 2002 and in Piolat et al., 1999). Length of secondary reaction times is considered reflecting intensity of a writer’s cognitive effort, that is executive control devoted to writing. The replicated pattern of cognitive effort of the three main writing processes is the following: planning and revision are the most effortful writing processes, and translating is the less demanding process (for reviews, see Olive, 2004, 2011). In parallel, Flower and Hayes’s (1980) claim about the overloaded writer clearly suggests, in executive terms, that executive demands remain high throughout writing, and do not decrease with learning and practice (see earlier). This is also coherent with the simple and Not-So-Simple view of writing (Berninger & Amtmann, 2003; Berninger & Winn, 2006) that include planning and revision (or monitoring in Kellogg’s terms) as executive processes. These two writing processes indeed plays a role in self-regulation by determining goals associated to process planning and production and revision cycles as explicated in more details in the next sections on writing processes.
Planning The cognitive effort of planning is generally found to be very high. This is because this writing process involves two types of planning: process planning and text (content) planning (Hayes & Nash, 1996). Process planning refers to the supervision of unfolding of writing. With this process, writers set goals based on different parameters such as integration of the reader, the type of text, the instructions, etc. For that purpose, writers create an initial representation of the task in terms of goals and subgoals that determine the nature of the writing processes to implement. Then, they select an adequate writing strategy for reaching the goals they have defined. This strategy results in the creation of an action plan that guides knowledge retrieval in long-term memory, as well as its organization (Flower et al., 1989). For instance, creating a plan before composing reduces the overall cost of production and leads to producing texts of better quality (Rau & Sebrechts, 1996). Obviously, by allowing writers to set goals and subgoals, to plan writing strategies by retrieving adequate actions plans and text structures, process planning triggers executive functions. In that sense, the high cognitive effort of planning is likely to, at least partially, reflect this procedural aspect of planning. The cognitive effort of planning also comes from content planning. Content planning allows writers recovering the knowledge they will use in their text from their long-term memory or from the environment. However, retrieving ideas is not sufficient for composing a quality text. The retrieved knowledge has to be organized in a different order from the one in which it has been retrieved. Organization of ideas
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is then carried out on the basis of text schemata or structures which guide the organization of the content and result in a macrostructural representation of the text specifying the relationships between different ideas (Hayes & Nash, 1996). Cognitive effort of text planning (and consequently its executive demands) is therefore also determined by familiarity with topic and domain of the text to compose. Several studies have indeed shown that it is the case. For instance, cognitive effort of writers with low domain knowledge is higher than that of writers with high domain knowledge (Kellogg, 1987). Regarding writing strategies and text structures, Kellogg (1988, 1994) experimentally tested the impact of various types of drafting strategies and of organizing modes (e.g. plan in the form of written or mental list of topics, or in conceptual networks). Overall, he found that cognitive effort did not vary but that only use of the writing processes varied according to the writing strategy. These findings suggest that using text structures and plans changes how writers supervise the writing process. In terms of executive functions, the cognitive effort of text planning may therefore reflect control of retrieval in long-term memory of declarative knowledge, as well as inhibitory processes for inhibiting irrelevant knowledge and text structures that has been automatically activated by diffusion. Obviously, working memory (updating) is also needed for storing and processing the retrieved semantic and declarative knowledge before it is written.
Translating Translation has been shown to be systematically less expensive than planning and revising, presumably because this process shares language skills with speaking and involves less high-level decision-making about the writing task. Actually, few studies have evaluated how difficulties encountered in text formulation affect the cognitive effort of translation. Following Kellogg (1996; Kellogg et al., 2013), the cognitive effort of translating suggests that translating engages executive functions, even if it is at a lesser extent than planning and revising, for lexical retrieval, and syntactic preparation. Regarding spelling, although the longitudinal study by Altemeier et al. (2008) showed that rapid automatized switching predicted spelling in English in the first 3 years of school, it may not involve executive functions in skilled writers who implement automatic spelling processes. One particular feature of writing that suggests the involvement of executive functions is its slowness (compared to speaking). The slow pace of writing indeed leaves writers with the possibility to control more intensively their lexical and syntactic choices. Retrieval of a lexical item or of a syntactic structure when composing a text should involve executive functions particularly when writers have to choose the word or syntactical structure that best suits their communicative goals. This is confirmed by Medimorec and Risko (2016) who showed that decreasing transcription demands (typing speed in the present case) resulted in increased lexical sophistication, sentence complexity, and cohesion of the essays. In other words, when search in
216 9. Executive Functions in Skilled Writers long-term memory is less constrained by time, selected knowledge is less trivial, less frequent, and less typical. Therefore, the need to select adequate words and relevant syntactical structures stored in long-term memory should involve controlled retrieval in long-term memory when translating conceptual content into language. Corollary, translating also requires inhibition for suppressing dominant or prepotent responses, here the more prototypical words or syntactic patterns. Composing a good text indeed requires writers to use language in a creative way, which means avoiding frequent forms of language and use sophisticated vocabulary and syntactic forms. Because frequent words are more prone to be activated (for a review see Perret & Bonin, 2019), writers need to inhibit these frequent words and retrieve words with controlled searches in their mental lexicon. Studies of subject-verb agreement also show how a prepotent response may lead to an error if it is not inhibited (e.g. see Hupet, Fayol, & Schelstraete, 1998). Studies on subject-verb agreement and more specifically on proximity errors clearly demonstrate that the presence of an agreement mark of a potential subject close to the verb implicitly activates the agreement mark of the verb. For example, in a syntactic structure like ‘the dog of the neighbours + [to eat]’, the plural mark of the second name can lead to an error of agreement of the verb by automatic activation of its plural form (i.e. ‘the dog of the neighbours eat’ instead of ‘eats’). This has been shown to occur in adults who are overloaded because they rely on automatic agreement processes that activate prepotent agreement markers, but less often in children who apply controlled agreement algorithms. More intensive research has to be conducted in this direction to explain how translating involves executive functions. Furthermore, investigating the factors that affect the cognitive effort of translating would enable to better understand the specific executive processes that may be involved when selecting words and creating syntactic structures.
Revising Revision involves two basic processes of reading and editing and is generally found to be at least as demanding as planning (Olive, 2004). Revising a text requires first reading it for evaluating whether it fits the expected quality. Reading for assessing is however different from reading for comprehending (which nevertheless requires executive functions, see the meta-analytic review by Follmer, 2018). To better understand critical reading (i.e. reading for evaluative purpose), Roussey and Piolat (2008) investigated whether reading a text in order to evaluate it is more expensive than reading a text to understand it. They also examined whether the nature of errors contained in the text affected writers’ cognitive effort. In this study, students performed a comprehension task and a revision task on a text containing either syntax errors or spelling errors. Analysis of the cognitive effort associated with the two types of reading showed that critical reading was more effortful than
Executive Functions and the Writing Processes of Skilled Writers 217
comprehension reading. It also showed that it was more effortful with syntax errors than with spelling ones. McCutchen, Francis, and Kerr (1997) argued that a significant amount of working memory resources should be allocated to error detection when reading. The involvement of the central executive in error detection has been confirmed by Larigauderie, Gaonac’h, and Lacroix (1998) who showed that the degree of involvement of executive functions increased with size of processing span: errors that involved processing large spans of words (within or between sentences) required more executive working memory than did errors at the word level. More recently, Larigauderie, Guignouard, and Olive (2020) investigated how different executive functions are involved in error detection by undergraduate students. Before detecting errors in texts, participants completed a battery of tasks that evaluated non-executive functions (the verbal and visuospatial short-term registers) and executive functions (coordination of verbal and of visuospatial storage and processing, strategic retrieval in long-term memory, selective attention, shifting) of working memory. Larigauderie, Guignouard, and Olive (2020) found that visuospatial storage as well as coordination of verbal storage and processing were significant predictors of the detection of phonological and orthographical errors. Effortful shifting was a significant predictor only of the detection of orthographical errors, while strategic retrieval from long-term memory was the only predictor of the detection of grammatical errors. In addition, in the verbal domain, the executive component of working memory appeared to be more involved than the non-executive component, whereas in the visuospatial domain, the non-executive component appeared to be more involved than the executive component. This study shows that different executive functions are needed for detecting different types of spelling and grammatical errors. It also shows that the type of executive functions that is required depends on whether participants selected a visual or verbal strategy to detect the errors. It has however to be mentioned that in this study the participants did not compose the texts they had to evaluate. Moreover, the study only concerned error detection and did not investigate error correction since participants only detected errors and were not asked to correct them. Different findings may be observed when detecting errors in a text written by the reader. In coherence with the simple and the Not-So-Simple view of writing (Berninger & Amtmann 2003; Berninger & Winn, 2006), the evaluative nature of revision makes this process a highly plausible candidate to trigger executive functions. This is also coherent with Kellogg’s model (1996). This model indeed suggests that the monitoring processes—the label Kellogg gave to the set of processes involved in revision—are not directly responsible for applying effective corrections to solve the problems that a writer has detected, as it is usually the case in models of revision processes (for a review of revision models, see Chanquoy, 2009). For instance, in Hayes and Flower’s (1980) model, editing is conceived as a system of rules used to solve the detected errors (see also Hacker et al., 1994). Monitoring only involves two subprocesses: reading for evaluating the presence of errors or problems, and editing to determine the type of error detected. Once the nature of the error is diagnosed, then a signal is launched
218 9. Executive Functions in Skilled Writers to the process that was at its origin, which in responsible for correcting it. For instance, when a semantic problem occurs, correction of the problem is attributed to planning, and similarly with translating when a language problem happens or with execution when writers have to correct errors on the written trace. In this perspective, monitoring acts as an executive process, at least for supervising and activating other processes. By triggering other writing processes (planning, translating, execution), monitoring thus acts as an executive supervisor of the unfolding of writing.
Transcription Although handwriting is generally considered relatively automatic among adult writers and should therefore not pose executive demands, the use of new writing technologies (keyboards, soft keyboards, digital inks . . . ) may require writers to adapt to these new tools with which they are not necessarily familiar. For example, Bouriga and Olive (in press) showed that the cognitive effort of undergraduate students who copied a text with a computer keyboard was higher than with a pen and paper. They also showed that these additional demands interfered with the ongoing activity (a serial recall task in this case). Thus, greater executive control may be needed to allow writers to adapt to the additional demands imposed on working memory by a less familiar mode of transcription (Berninger, 1999). Corollary, the automatization of handwriting in adults provides large available resources in WM which allows skilled writers to activate high-level writing processes (planning, translating, and revising) simultaneously with transcription (Olive & Kellogg, 2002, see the next section for a detailed explanation of how this was demonstrated). By contrast, unskilled transcription takes a large part of WM resources and therefore prevent higher level processes to be simultaneously activated. This leads to a more sequential strategy of writing constituted of stages of text preparation followed up by stages of transcription, instead of being simultaneously coordinated (the thinking-then-writing and thinking-while-writing strategies described by Olive 2014; see the following section). The same phenomenon is observed with different levels of typing skills: low typists do not succeed in coordinating concurrently text preparation and text transcription (Alves, Castro, & Olive, 2008) which results on shorter burst of writing (e.g. Alves, Castro, Sousa, & Strömqvist, 2007). So, although skilled transcription does not appear to require executive functions, writers resorting to transcription modes they are not familiar with have to change how they supervise coordination of the writing processes. This surely imposes new demands on working memory and engages more executive functions. How different modes of coordination may change the executive demands in addressed in next section. To conclude, this section on executive demands of the writing processes offers a general view on how each writing process may engage executive functions. However, executive demands of writing do not only come from the writing processes themselves.
Executive Demands for Orchestrating the Writing Processes 219
Supervising all the processes engaged for processing different types of knowledge is also expected to engage executive functions.
Executive Demands for Orchestrating the Writing Processes In addition to the specific demands each writing process place on working memory and executive functions, coordinating these processes also requires executive control. Composing a text cannot be reduced to the linear implementation of planning, translating, transcription, and revision. Skilled writers indeed compose texts with frequent fluent phases made up of short pauses and long bursts of language that can combine different clauses or sentences (Cislaru & Olive, 2015). Furthermore, a linear and sequential strategy would reduce the opportunity for rapid interactions between high-level writing processes. Yet, such interactions are fundamental in skilled writing (McCutchen, 1988). Concurrent coordination of low-and high-level writing processes seems more plausible. Efficient concurrent coordination of low-and high-level writing processes is central to producing good-quality texts, and is a fundamental component of writing skill. This relationship between writers’ performance and the way they supervise the writing processes arises out of the considerable demands that writing places on working memory (Berninger & Swanson, 1994; St Clair-Thompson & Gathercole, 2006; Kellogg, 1996; McCutchen, 2000). In order to avoid overloading their limited working memory capacity and to be able to devote their full working memory capacity to high-level processes, writers have to decrease the demands of low-level processes (e.g. handwriting and spelling). When these processes are automatized, then it is possible to elicit planning, translating, and reviewing concurrently to transcription. Olive and Kellogg (2002) provided evidence that writers are able to activate high-level processes concurrently to transcription, once the latter is automatized. They asked children, adults using their familiar handwriting, and adults using cursive uppercase handwriting to compose a text and then to copy it. Secondary reaction times assessed processing demands of high-level writing processes only (pausing), transcription only (transcribing while copying), and transcribing while composing. For the adults who used their familiar handwriting, the reaction times associated with the periods of transcription during composition were longer than those associated to either transcription only or high-level processing only. They interpreted the high level of processing demands when transcribing as a sign of the concurrent activation of transcription and high-level writing processes. Conversely, for children and for adults writing in an unfamiliar style, handwriting was as much effortful when composing than when copying, indicating the absence of concurrent activation. Presumably, they were unable to activate high-level writing processes while handwriting, and therefore had to suspend their handwriting to think about their texts. Thus, the strategy for coordinating the writing processes may shift from sequential to more or less concurrent
220 9. Executive Functions in Skilled Writers activation (see Figure 9.1). Alves, Castro, and Olive (2008) further showed that translating occurred mostly during handwriting, whereas revising and planning were mainly activated during the pauses. However, none of the writing processes could be described as being typical of pauses, as translating occurred to a similar extent than the other processes. Finally, Olive and Kellogg (2002) showed that an increase in cognitive demands of handwriting made writers shifting from a parallel strategy to a more linear one (see also Olive, Alves, & Castro, 2009). Such flexibility in coordination of low-and high-level writing processes is a key for understanding executive demands (for evidence of such flexibility at the syllable level, see Sausset, Lambert, Olive, & Larocque, 2012). As Olive (2014) proposed, writing should indeed be conceived on a continuum of coordination with, at one pole, linear implementation and, at the opposite pole, parallel/concurrent processing, and writers being able to adopt either a thinking-then-writing strategy or a thinking-while- writing strategy depending on working memory capacity and level of automatization of the writing processes (see Figure 9.1). When composing with the writing-while- writing strategy, each segment of text is sequentially processed from central to peripheral processes, but different levels of processing can operate (or not) simultaneously
Thinking-then-writing coordination
Planning
segment n+1
segment n
n+1
n
Translating
n
Transcribing Time
n+1 chapter on writing”
“I write this
Thinking-while-writing coordination
Planning
segment segment n n+1 n
Translating
n+1 n
Transcribing Time
n+1
“I write this chapter on writing”
Figure 9.1 From sequential (or thinking-then-writing) to parallel (or thinking-while- writing) coordination of the writing processes. The striped area indicates a pause in transcription (top panel), and a need for buffering segment n+1 before it can be sent to translating (bottom panel).
Conclusion 221
on different segments of text. Because information cascades between levels of processing, operations at a particular level may interact with a subsequent level of processing. Additionally, because the different processes that operate simultaneously require to share working memory capacity, operations at low levels of processing may affect higher levels due to their respective demands. Of importance for the involvement of executive functions is flexibility of coordination of writing processes. Indeed, depending on tasks’ demands and writers’ characteristics, the writing processes can overlap to a greater or lesser degree. When adopting a more sequential mode of coordination (Figure 9.1, top panel), executive demands may come mainly from demands of each writing process, as one process is only activated at a given moment and does not require strong supervision. By contrast, when writers coordinate several writing processes concurrently, more supervision is needed for controlling processing, coordinating outputs, buffering, etc. For example, as can be seen in Figure 9.1 (bottom panel), thinking-while-writing coordination requires to buffer segment n + 1 between planning and translating because of different processing times, which is not the case with the thinking-then-writing coordination. In sum, concurrent coordination of the writing processes—which is typical of skilled writers—requires executive control for monitoring not only process switching, but also information flow and the related processing and short-term storage demands. However, this results in more fluent writing. As can be seen in Figure 9.1, the sentence is written in two bursts separated by a pause with the thinking-then-writing mode of coordination of the writing processes but in a single burst and in shorter time with the thinking-while writing coordination mode. These high executive demands of skilled cascading coordination certainly explain why self-regulation techniques are beneficial for children learning to reach skilled writing (Graham, McKeown, Kiuhara, & Harris, 2012; see Chapter 8 of this volume). Furthermore, individual differences in coordination of writing processes and intraindividual changes in coordination may differently involve executive functions.
Conclusion This chapter delineated, from a cognitive point of view, the demands that skilled writers composing texts pose on executive functions. Interestingly, although two models of working memory in writing have been proposed (Kellogg, 1996; McCutchen, 1996), none of these models precisely described the involvement and the role of executive functions. It is shown that understanding the executive demands of writing requires analysing the complexity of writing which is related to the fact that writing requires several high-level (central) cognitive processes that remain highly effortful in skilled writers. It is particularly highlighted the fact that writing a text cannot be completed without extended effort (Kellogg, 1994, 2008) and therefore constantly poses huge demands on working memory. Next, the cognitive effort or demands related to the writing processes is examined, an effort that is supposed to reflect engagement of
222 9. Executive Functions in Skilled Writers the executive functions. Initial proposals about the executive functions the different writing processes presumably engage are finally raised. Complexity of skilled writing also comes from the concurrent coordination of the writing processes, and particularly from the flexibility of coordination, which, depending on the task demands, may shift from more sequential to more parallel processing. Concurrent coordination of the writing processes indeed requires strong executive supervision. It has nevertheless to be recognized that writers usually compose texts in more or less linear stages, each stage focusing either on planning, translating, or revising (Kellogg et al., 2013). Findings from verbalization studies have indeed demonstrated a predominance of planning in the first third of writing, of translating in the second third, and of revision in the last third of composing. This does not imply that only one process is involved in each writing phase. Rather, verbalization studies have evidenced that one feature of skilled writing is recursion (Hayes & Flower, 1980; Levy & Ransdell, 1995). Recursion means that during writing, each process can be used at any moment, and can follow any other processes. As can be inferred from research reviewed in this chapter, in terms of cognitive mechanics, skilled writing poses huge processing demands to working memory, and therefore presumably highly engages the different core executive functions. At least planning and translating are expected to engage controlled retrieval in long-term memory since writers need to search for semantic and linguistic knowledge when composing a text. Corollary, when planning and translating, inhibition is required to inhibit unselected knowledge that has been activated by diffusion in the long-term memory network (Anderson & Green, 2001). For example, inhibition has to be engaged during planning to suppress knowledge that writers do not want to include in their text. Writers’ working memory content has to be very frequently updated with new content in order to support current processing. Updating (or working memory) is therefore also presumed to be highly activated. Updating should be involved during construction of the mental representation of the content of the text. Interference studies with the n-back task would certainly be useful to better understand the role of updating in writing. Flexibility is presumably used for controlling concurrent coordination of the writing processes and the flow of information between levels of processing. In addition, recursion and interaction of processes in working memory requires writers to shift frequently between processes and knowledge. Flexibility and inhibition may thus play a fundamental role in skilled writing to allow for efficient transitions between processes, and shifting cost (Rubinstein, Meyer, & Evans, 2001) might also be reflected in writers’ cognitive effort. Reviewing a text might also engage flexibility for juggling between the different representations of a text (from conceptual to visual through linguistic levels). Finally, planning, is probably one component of writing as underlined by the problem solving and decision-making facets of process planning (Hayes & Nash, 1996). It therefore appears that at least theoretically, almost all executive functions should be engaged when composing a text. It now remains to begin investigating how the writing processes, the different writing tasks and situations, as well as writers’ interindividual differences require the various executive functions, and at which extent.
References 223
References Altemeier, L., Abbott, R., & Berninger, V. (2008). Executive functions for reading and writing in typical literacy development and dyslexia. Journal of Clinical and Experimental Neuropsychology, 30, 588–606. Altemeier, L., Jones, J., Abbott, R.D., & Berninger, W.V. (2006). Executive functions in becoming writing readers and reading writers: note taking and report writing in third and fifth graders. Developmental Neuropsychology, 29, 161–73. Alves, R.A., Castro, S.L., & Olive, T. (2008). Execution and pauses in writing narratives: processing time, cognitive effort and typing skill. International Journal of Psychology, 43, 969–79. Alves, R.A., Castro, S.L., Sousa, L., & Strömqvist, S. (2007). Typing skill and pause-execution cycles in written composition. In G. Rijlaarsdam (Series Ed.), M. Torrance, L. van Waes, & D. Galbraith (Vol. Eds.). Writing and Cognition: Research and Applications (Studies in writing Vol. 20, pp. 55–66). Amsterdam: Elsevier. Anderson, M.C., & Green, C. (2001). Suppressing unwanted memories by executive control. Nature, 410(6826), 366–9. Baddeley, A.D. (1986). Working Memory. Oxford, UK: Oxford University Press. Baddeley, A.D., & Hitch, G. (2001). Working memory in perspective: foreword. In J. Andrade (Ed.). Working Memory in Perspective (pp. xv–xix). Hove, UK: Psychology Press. Berninger, V.W. (1999). Coordinating transcription and text generation in working memory during composing: automatic and constructive processes. Learning Disability Quarterly, 22, 99–112. Berninger, V.W., & Amtmann, D. (2003). Preventing written expression disabilities through early and continuing assessment and intervention for handwriting and/or spelling problems: research into practice. In H.L. Swanson, K.R. Harris, & S. Graham (Eds.). Handbook of Learning Disabilities (pp. 345–63). New York, NY: Guilford Press. Berninger, V.W., & Swanson, H.L. (1994). Modifying Hayes and Flower’s model of skilled writing to explain beginning and developing writing. In E.C. Butterfield (Ed.). Advances in Cognition and Educational Practice, Vol. 2. Children’s Writing: Toward a Process Theory of the Development of Skilled Writing (pp. 57–81). Greenwich, CT: JAI Press. Berninger, V.W., & Winn, W.D. (2006). Implications of advancements in brain research and technology for writing development, writing instruction, and educational evolution. In C.A. MacArthur, S. Graham, & J. Fitzgerald (Eds.). Handbook of Writing Research (pp. 96–114). New York, NY: Guilford Press. Bourdin, B., & Fayol, M. (1994). Is written language production more difficult than oral language production? A working memory approach. International Journal of Psychology, 29, 591–620. Bourdin, B., & Fayol, M. (2001). Even in adults, written production is still more costly than oral production. International Journal of Psychology, 37(4), 219–27. Bouriga, S., & Olive T. (in press). Is typewriting more resources-demanding than handwriting in undergraduate students? Reading and Writing. Chanquoy, L. (2009). Revision processes. In R. Beard, D. Myhill, J. Riley, & M. Nystrand (Eds.). The SAGE Handbook on Writing Development (pp. 80–97). Thousand Oak, CA: SAGE Publications Ltd Chomsky, N. (2000). Minimalist inquiries: the framework. In R. Martin et al. (Eds.). Step by Step. Essays on Minimalist Syntax in Honor of Howard Lasnik (pp. 89–155). Cambridge, MA: MIT Press. Cislaru, G., & Olive, T. (2015). Linguistic forms at the process-product interface: analysing the linguistic content of bursts of production. In G. Cislaru (Ed.). Writing(s) at the
224 9. Executive Functions in Skilled Writers Crossroads: The Process/Product Interface. Amsterdam, the Netherlands: John Benjamins Publishing. Cordeiro, C., Limpo, T., Olive, T., & Castro, S.L. (2019). Do executive functions contribute to writing quality in beginning writers? A longitudinal study with second graders. Reading and writing. Reading and Writing, 33, 813–33. Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64, 135–68. Drijbooms, E., Groen, M.A., & Verhoeven, L. (2015). The contribution of executive functions to narrative writing in fourth grade children. Reading and Writing, 28(7), 989–1011. Flower, L.S., & Hayes, J.R. (1980). The dynamics of composing: making plans and juggling constraints. In L.W. Gregg & E.R. Steinberg (Eds.). Cognitive Processes in Writing (pp. 31–49). Hillsdale, NJ: Lawrence Erlbaum Associates. Flower, L.S., Schriver, K., Carey, L., Haas, C., Hayes, J.R. (1989). Planning in Writing: The Construction of a Constructive Process. Technical Report n° 34. Berkeley, CA/Pittsburgh, PA: Center for the Study of Language. Follmer, D.J. (2018). Executive function and reading comprehension: a meta-analytic review. Educational Psychologist, 53, 42–60. Gathercole, S.E., & Pickering, S.J. (2000a). Assessment of working memory in six-and seven- year old children. Journal of Educational Psychology, 92, 377–90. Gathercole, S.E., & Pickering, S.J. (2000b). Working memory deficits in children with low achievements in the national curriculum at seven years of age. British Journal of Educational Psychology, 70, 177–94. Graham, S., Harris, K.R., & Olinghouse, N. (2007). Addressing executive function problems in writing: an example from the self-regulated strategy development model. In L. Meltzer (Ed.). Executive Function in Education: From Theory to Practice (pp. 216–36). New York, NY: Guilford Press. Graham, S., McKeown, D., Kiuhara, S., & Harris, K.R. (2012). A meta-analysis of writing instruction for students in the elementary grades. Journal of Educational Psychology, 104, 879–96. Hacker, D.J., Plumb, C., Butterfield, E.C., Quathamer, D., & Heineken, E. (1994). Text revision: detection and correction of errors. Journal of Educational Psychology 86, 65–86. Hayes, J.R., & Nash, G.J. (1996). On the nature of planning in writing. In M. Levy & S. Ransdell (Eds.). The Science of Writing. Theories, Methods, Individual Differences, and Applications (pp. 28–56), Mahwah, NJ: Lawrence Erbaum Associates. Hooper, S.R., Swartz, C.W., Wakely, M.B., de Kruif, R.E.L., & Montgomery, J.W. (2002). Executive functions in elementary school children with and without problems in written expression. Journal of Learning Disabilities, 35, 37–68. Hupet, M., Fayol, M., & Schelstraete, M. (1998). Effects of semantic variables on the subject- verb agreement processes in writing. British Journal of Psychology, 89, 59–75. Just, M.A., & Carpenter, P.A. (1992). A capacity theory of comprehension: individual differences in working memory. Psychological Review, 99, 122–149. Kellogg, R.T. (1987). Effects of topic knowledge on the allocation of processing time and cognitive effort to writing processes. Memory and Cognition, 15, 256–66. Kellogg, R.T. (1988). Attentional overload and writing performance: effects of rough draft and outline strategies. Journal of Experimental Psychology: Learning, Memory, & Cognition, 14, 355–65. Kellogg, R.T. (1994). The Psychology of Writing. Oxford, UK: Oxford University Press. Kellogg, R.T. (1996). A model of working memory in writing. In C.M. Levy & S. Ransdell (Eds.). The Science of Writing: Theories, Methods, Individual Differences, and Applications (pp. 57– 71). Mahwah, NJ: Lawrence Erlbaum Associates. Kellogg, R.T. (2008). Training writing skills: a cognitive development perspective. Journal of Writing Research, 1, 1–26
References 225 Kellogg, R.T., Whiteford, A.P., Turner, C.E., & Cahill, M. (2013). Working memory in written composition: an evaluation of the 1996 model. Journal of Writing Research, 5(2), 159–90. Larigauderie, P., Gaonac’h, D., & Lacroix, N. (1998). Working memory and error detection in texts: what are the roles of the central executive and the phonological loop? Applied Cognitive Psychology, 12, 5050–527. Larigauderie, P., Guignouard, C., & Olive, T. (2020). Implication of executive and non-executive components of working memory in detection of typographical, lexical, or grammatical errors. Reading and Writing, 33, 1015–36. Levy, C.M., & Ransdell, S.E. (1995). Is writing as difficult as it seems? Memory and Cognition, 23, 767–79. McCutchen, D. (1988). ‘Functional automaticity’ in children’s writing: a problem of metacognitive control. Written Communication, 5, 306–324. McCutchen, D. (1994). The magical number three, plus or minus two: working memory in writing. In J.S. Carlson (Series Ed.), & E.C. Butterfield (Vol. Ed.). Advances in Cognition and Educational Practice, Vol. 2: Children’s Writing: Toward a Process Theory of the Development of Skilled Writing (pp. 1–30). Greenwich, CT: JAI Press. McCutchen, D. (1996). A capacity theory of writing: working memory in composition. Educational Psychology Review, 8, 299–325. McCutchen, D. (2000). Knowledge, processing, and working memory: implications for a theory of writing. Educational Psychology, 35, 13–23. McCutchen, D., Covill, A., Hoyne, S.H., & Mildes, K. (1994). Individual differences in writing: implications of translating fluency. Journal of Educational Psychology, 86, 256–66. McCutchen, D., Francis, M., & Kerr, S. (1997). Revising for meaning: effects of knowledge and strategy. Journal of Educational Psychology, 89, 667–76. Medimorec, S., & Risko, E.F. (2016). Effects of disfluency in writing. British Journal of Psychology, 107(4), 625–50. Miyake, A., Friedman, N.P., Emerson, M.J., Witzki, A.H., Howerter, A., & Wager, T. (2000). The unity and diversity of executive functions and their contributions to complex ‘frontal lobe’ tasks: a latent variable analysis. Cognitive Psychology, 41, 49–100. Olive, T. (2004). Working memory in writing: empirical evidence from the dual task technique. European Psychologist, 9, 32–42. Olive, T. (2011). Working memory in writing. In V.W. Berninger (Ed.). Past, Present, and Future Contributions of Cognitive Writing Research to Cognitive Psychology (pp. 485–503). New York, NY: Psychology Press. Olive, T. (2014). Toward an incremental and cascading model of writing: a review of research on writing processes coordination. Journal of Writing Research, 6, 173–94. Olive, T., & Kellogg, R.T. (2002). Concurrent activation of high-and low-level production processes in written composition. Memory and Cognition, 30, 594–600. Olive, T., Alves, R.A., & Castro, S.L. (2009). Cognitive processes in writing during pause and execution periods. European Journal of Cognitive Psychology, 21, 758–85. Olive, T., Kellogg, R.T., & Piolat, A. (2002). The triple-task technique for studying the process of writing. In T. Olive & C.M. Levy (Eds.). Contemporary Tools and Techniques for Studying Writing (pp. 31–58). Dordrecht, the Netherlands: Kluwer Academic Publishers. Perret, C., & Bonin, P. (2019).Which variables should be controlled for to investigate picture naming in adults? A Bayesian meta-analysis. Behavior Research, 51, 2533–45. Piolat, A., Olive, T., & Kellogg R.T. (2005). Cognitive effort of note taking. Applied Cognitive Psychology, 19, 291–312. Piolat, A., Olive, T., Roussey, J.-Y., Thunin, O., & Ziegler, J.C. (1999). Scriptkell: a computer assisted tool for measuring the relative distribution of time and cognitive effort in writing and other tasks. Behavior Research Methods, Instruments, & Computers, 31(1), 113–21.
226 9. Executive Functions in Skilled Writers Rau, P.S., & Sebrechts, M.M. (1996). How initial plans mediate the expansion and resolution of options in writing. The Quarterly Journal of Experimental Psychology, 49A(3), 616–38. Robinson, P. (2007). Task complexity, theory of mind, and intentional reasoning: effects on L2 speech production, interaction, uptake and perceptions of task difficulty. International Review of Applied Linguistics, 45(3), 193–213. Roussey, J.-Y., & Piolat, A. (2008). Critical reading effort during text revision. European Journal of Cognitive Psychology, 20, 765–92. Rubinstein, J.S., Meyer, D.E., & Evans, J.E. (2001). Executive control of cognitive processes in task switching. Journal of Experimental Psychology: Human Perception and Performance, 27, 763–97. Sausset, S., Lambert, E., Olive, T., & Larocque, D. (2012). Processing of syllables during handwriting: effects of graphomotor constraints. The Quarterly Journal of Experimental Psychology, 65, 1–9. Skehan, P. (1998). A Cognitive Approach to Language Learning. Oxford, UK: Oxford University Press. St Clair-Thompson, H.L.S., & Gathercole, S. (2006). Executive functions and achievements in school: shifting, updating, inhibition, and working memory. Quarterly Journal of Experimental Psychology, 59(4), 745–59. Vandenberg, R., & Swanson, H.L. (2007). Which components of working memory are important in the writing process? Reading and Writing, 20, 721–52.
10 The Ageing Writer São Luís Castro and Regina Abreu
Introduction Writing is a cognitive demanding ability (Olive, this volume). Can we expect it to change significantly in older years? As we will show in this chapter, people do change their writing styles as years go by, but at an advanced age they remain able to convey relevant and precise information through writing. Expertise, cognitive reserve, and adaptive mechanisms play a role in this positive outcome, as they mitigate age-related cognitive decline. However, writing performance is in part determined by the efficiency of executive processes, and age does exert a toll on these. In considering the ageing writer, our standpoint will be that, as other cognitive demanding abilities, writing relates to development in a two-way street: it is both a reflex and an enhancer of cognitive functioning. On the one hand, lifespan developmental constraints must be taken into account. On the other hand, the potential of writing as a tool for cognitive enhancement deserves to be examined. This idea of writing as a reflex of, and a stimulus for, cognitive and executive functions guides the four sections of this chapter. We will first consider the characteristics of older adults’ writing and age- related changes in executive control during writing, then writing markers of dementia and writing-based interventions for healthy ageing.
Characteristics of Writing in Older Ages Age-Related Changes in Cognition and Language Ageing is a multidimensional process where multiple factors intervene differently across individuals (Hofer & Sliwinski, 2006). Age-related changes occur in physical (i.e. biological functions, such as reproductive capacity, immune system response, brain function), social (i.e. social meanings, values, and expectations) and psychological (i.e. cognitive functions, beliefs, and behaviours) dimensions (Morgan & Kunkel, 2007). In psychological approaches to ageing, researchers look for patterns of continuity and change over time based on the idea that development occurs throughout the entire lifespan. This is a complex investigation because the ageing São Luís Castro and Regina Abreu, The Ageing Writer In: Executive Functions and Writing. Edited by: Teresa Limpo and Thierry Olive, Oxford University Press. © Oxford University Press 2021. DOI: 10.1093/oso/9780198863564.003.0010
228 10. The Ageing Writer process unfolds with noticeable individual differences and is affected by multiple variables: factors like smoking, obesity, depression, and anxiety accelerate psychophysical decline, while others, like exercise, social support, sense of control, and emotional balance, reduce it (Aldwin, Spiro, & Park, 2006). This intersection of genetic, psychological, and social variables combines to form different patterns of ageing processes (Hofer & Sliwinski, 2006). A well-known pattern of how ageing differentially affects cognition relates to accumulated knowledge (i.e. crystalized intelligence) versus the ability to generate and manipulate information (i.e. fluid intelligence): as one gets older, vocabulary and factual knowledge tend to increase, whereas memory, reasoning, learning, and problem solving abilities tend to decrease (Salthouse, 2010). In an analysis of data from neuropsychological assessments across multiple studies, Salthouse (2010; 2012) established that until 60 years of age there is a gradual increment in measures of accumulated knowledge, but starting at 20 years there is a slow but steady decline in process measures, up to two standard deviation units at 70 years. These age-related changes in cognition have been linked to structural and functional brain changes. Increasing age correlates with loss in grey and white matter integrity, mainly in prefrontal, parietal, and temporal regions and, compared to younger adults, older ones show lower activations in specific brain regions during different tasks, either because they are underrecruiting appropriate areas or recruit brain areas non-specifically (Kramer, Fabiani, & Colcombe, 2006). However, it is not always clear if age-related functional brain changes are due to cortical decline, to compensatory strategies during performance or to adaptive plasticity (e.g. Greenwood, 2007; Gutchess, 2014; Williams et al., 2006). For example, older adults may compensate the lack of resources by resorting to homologous bilateral, or other, brain regions for a given task (Reuter-Lorenz & Mikels, 2005). In language, the effects of ageing also follow a differential pattern: input processes are relatively preserved and output processes relatively impaired (Abrams & Farrell, 2010), and, mutatis mutandis, the same goes for syntactic processing, preserved, and word production, impaired (Shafto & Tyler, 2014). Age-related changes in language abilities can be observed at different linguistic levels, namely the word, sentence, and discourse levels (Thornton & Light, 2006). Older adults are more likely to have impairments in speech perception, due to worse phoneme discrimination and word identification difficulties, and in vocabulary retrieval, where tip-of-the-tongue states increase with age; however, these impairments do not necessarily translate into diminished verbal fluency, probably due to adaptive compensatory strategies such as more planning and slower speech rate. Although sentence production and comprehension are generally preserved, syntactic complexity in speaking may suffer from working memory limitations. Discourse comprehension tends to be affected by hearing loss, but discourse production is structurally complex (stories from older people are rated as elaborate, clear, and rich as those from younger adults), with off-topic excursions limited to when conveying personal information. Faced with age-dependent sensory and memory constraints, older people are more prone to rely on contextual cues
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and semantics. However, this strategy has the downside of requiring the allocation of high-level processes, such as working memory, to language processing.
Older People’s Writing Across Different Levels and Output Forms Writing activities are performed by older adults on a daily basis and include writing notes, shopping lists, and doing crossword puzzles (Rosenblum & Werner, 2006; Van Drempt, McCluskey, & Lannin, 2011a; participants’ age 65+ yrs1). Though some of these activities are easier than others, in all of them writing involves multiple processes—attention, executive functions, memory, language (Graham, 2018; this volume)—which may have been affected by the biological decline of older years. On the bright side, as people age their writings tend to reflect increasing wisdom and deeper understanding of human experience (Pennebaker & Stone, 2003). Indeed, the characteristics of writing covary with age to such an extent that Pennebaker and Stone (2003) have proposed that people consistently change their linguistic styles as they age. We looked for evidence in the writing literature and were able to sketch a profile of the ageing writer as depicted in Table 10.1, and more fully presented next. Lexical level. Studies on the linguistic content of older adults’ written productions have revealed a mix of extensive factual and experiential knowledge together with progressive working memory decrements. Focusing on the lexical level, its main characteristics are a rich vocabulary encumbered by difficulties in orthographic wordform retrieval. In one of the first empirical studies of writing, Bromley (1991) asked over 200 people aged between 20 and 86 years to write personality self-descriptions. The number of words used was similar across ages, but word length in syllables, frequency of long words, and vocabulary diversity (i.e. type-to-token ratio, the number of unique words in a given numbers of tokens), all increased significantly with age. Later studies have shown that vocabulary size also augments with age (e.g. Jackson & Kemper, 1993). Interestingly, words seem to be used differently by younger and older participants: in a computerized analysis of spoken and written language samples from over 3 000 participants reporting on emotional experiences (Pennebaker & Stone, 2003), increasing age was associated with using more positive, and less negative, emotion words, more verbs in present-and future-and less in the past-tense, and more complex words (e.g. longer than 6 letters, cognitive words, words indicating insight) than simple ones (shorter, concrete, non-reflective). Additionally, the use of first-person plurals decreased until about 70 years, when it increased sharply to the level of 8-to 14-year-olds. Pennebaker and Stone (2003) proposed that these lexical changes result from gains in self-and world-knowledge, as well as from ease in detaching from the
1 Throughout the chapter we indicate the age of participants whenever relevant because the labels older/ younger may refer to very different ages across studies. For the sake of brevity, we refer to the age of participants using [number] yrs.
230 10. The Ageing Writer Table 10.1 A profile of the ageing writer Main age-related characteristics of elders’ writing Content /Central Processes Lexicon
Vocabulary: frequent use of positive emotion words; verbs in present-and future-tense; large vocabulary size Orthography: more misspellings; impaired retrieval (but preserved recognition) of correct and incorrect spellings
Syntax
Complexity: less clauses per sentence; reduced embedding Correctness: preserved, except in difficult essays
Discourse
Textual cohesion: less cohesive and more ambiguous structure Narrative complexity: more complex and elaborate Summarization: more use of central ideas; more concision
Form/Output Processes Handwriting
Fluency: longer writing time (on-paper and in-air measures); reduced speed; longer decelerative phase Spatial features: inconsistent stroke size; preserved legibility Pen measures: reduced pen pressure; more pen lifts
Typing
Fluency: longer writing time; less editing time Editing: more mistypings and mispellings; fewer corrections
Note: Results for older writers when compared to younger ones.
self when writing. Notice however the non-linearity in the use of first-person plurals, that appears to shift from less to much more around the age of 70+ years. Difficulties in retrieving orthographic wordforms when writing occur frequently in older ages (Abrams & Farrell, 2010). For example, in a spelling to dictation task with difficult-to-spell words, adults aged above 60 years produced more misspellings than younger ones, irrespective of word frequency, but only the oldest adults (73–88 yrs) were aware of this difficulty (MacKay & Abrams, 1998). The results of this study could not be accounted for by educational level nor reading and writing habits, but other studies suggest that poor spellers might suffer more than good spellers from age-related impairments in orthographic retrieval (e.g. Margolin & Abrams, 2007). Thus, even though accessing orthographic representations is adversely affected by age, it is not clear if this effect is general or impacts mostly on poor spellers. Another point is whether this difficulty affects perception as it does production, and the answer seems to be no. MacKay, Abrams, and Pedroza (1999) presented participants with high-frequency words that were either correctly or incorrectly spelled, and asked them first to indicate whether the spelling was correct (perception task) and then to reproduce the spelling they had just seen by writing it down (production task). No age differences were found in the perception task, but in the production task older subjects (62–85 yrs) had more difficulty than younger ones in retrieving both correct and incorrect spellings.
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Syntactical level. In an analysis of adults’ diaries using a longitudinal and a cohort sample, Kemper (1987) found an age-related decline in the syntactic complexity of sentences. As age increased from 20 to 80 years, diary writers used fewer relative clauses, that-and wh-clauses, infinitives, and double and triple embeddings; they also wrote less clauses per sentence (but not less words per sentence). The reduction in complexity touched similarly complex and simpler structures: left-branching embedded structures where a subordinate clause interrupts the main clause, as in ‘The dog who the boy watched chased after the ball’, were as infrequently produced as simpler right-branching structures, where one clause follows another, as in ‘The boy watched the dog who chased after the ball’. Interestingly, this pattern was not observed in elders’ oral production, where complex left-branching embeddings were the most affected by age (Kynette & Kemper, 1986). This unexpected advantage of writing over speech indicates that older adults’ written outcomes may benefit from their slower pace of writing (see fluency next) and from the possibility to revise and edit afforded by writing, but less by speaking (Kemper, 1987). In another large-scale study of autobiographical written language samples obtained in the Nun Study over 60 years, grammatical complexity in number and type of embedded clauses and propositional density (number of interconnected ideas relative to total word count) declined with age; embedded and subordinate sentences were used less often, and more words were needed to convey an idea. Although the finding of less grammatical complexity with increasing age has been replicated (e.g. Bromley, 1991), other studies failed to get it. For example, Byrd (1993) reported that younger (21 yrs on average) and older (68 yrs on average) adults produced similar texts in overall and, importantly, sentence length, and were equally proficient at correctly producing verb tenses, grammatical forms, and the sentences as a whole. Yet, older adults wrote less correct sentences when composing a more difficult type of essay, persuasive arguments, than when composing easier ones such as descriptions and comparisons, a difference that was not seen in younger adults. So the difficulty of the writing task plays a role, and probably the age range of participants too. The ability to write complex sentences seems to be stable in middle age, from 45 to 61 years (Spencer, Craig, Ferguson, & Colyvas, 2012), and in Byrd’s study the older subjects were younger than in Kemper’s 1987 and 2001 studies. For comparison, in speaking it was only after the age of 74 years that an accelerated decline in the syntactical complexity of utterances was observed (Kemper, Thompson, & Marquis, 2001b), an example of how syntax is spared of ageing effects (Shafto & Tyler, 2014). In writing, then, major syntactical impairments seem to appear only in later years, an hypothesis that remains to be systematically tested. Discourse level. Diaries have provided a rich source of data for the analysis of discourse-level characteristics of older people’s writings. These characteristics can be traced to textual cohesion (how sentences relate to each other), narrative complexity, and text sumarization. One important study is Kemper’s (1990), who examined eight diaries covering a 70-year period. She found that narratives became less cohesive across the lifespan, as revealed by a decline in the number of anaphoras (use
232 10. The Ageing Writer of pronouns whose referent is supplied previously) and conjunctions (sentence connectives that establish relationships among events), and an increase in ambiguous anaphoras (pronouns whose referent is not clearly linked to the preceding text). Nonetheless, as diarists aged, their stories were rated as more interesting and technically better accomplished, and their narrative structures became more complex. Indeed, it was only 70-and 80-year-olds who produced stories that included complex chains of multiple embedded episodes and epilogues that communicated moral conclusions. Moreover, narratives tended to be more complex when recounting remote significant past events. Another important study is Byrd’s (1993), a non-diary study. Byrd asked younger (21 yrs on average) and older (68 yrs on average) adults to write three types of essays, from easy to difficult: descriptive, comparative, and persuasive texts. He also found less cohesion in the texts from the older adults than in those from the younger ones, but only in the most difficult essays, the persuasive ones, not in the descriptive or comparative texts. Older adults’ persuasive texts were also less compact than the younger adults’, that is, cohesive elements were more distant from one another. Additionally, there were semantic differences between the groups: younger adults made more reference to abstract topics in the comparative and persuasive texts, but older adults kept to concrete topics irrespective of text type. In narratives written in diaries, 70-and 80-year-olds tell stories about people who were meaningful in their lives, and turn away from a concern with death that had peaked earlier in their 60s (Kemper, 1990). Interestingly, while younger diarists focus mostly on present events, older ones write equally about present and past: reference to concurrent events decreases, and the past, especially the remote past which is virtually absent in younger adults’ diaries, takes the lead. In expressive writing sessions, people aged above 65 years tend to review past events with a certain detachment, mentioning positive as well as negative emotional aspects and switching easily from past to present, a change in focus that was associated with less negative affect at the end of the session (Devereux et al., 2016). Writing summaries is an important ability that involves understanding the text macrostructure (Jackson & Kemper, 1993), and a few studies have examined how it develops after adulthood. An initial study by Byrd (1985) reported that 64-to 70- year-olds were less selective in the inclusion of topics than 18-to 26-year-olds, but later studies uncovered a different picture. Older people’s summaries were briefer and more concise (Adams, 1991) or more complete and of better quality (Jackson & Kemper, 1993) than those of younger people. Specifically, in Jackson and Kemper’s study (1993) older writers (70 yrs) included twice as many central ideas (but also a slightly more non-central ones) as younger writers (20 yrs), and were able to convey one central idea with one sentence only, while young adults needed two or more sentences to do it (Jackson & Kemper, 1993). The discrepancy between Byrd’s and the findings from the two other studies cannot be attributed to differences in educational level, as participants in the three studies had about 15 years of schooling. It may have been due to differences in experimental procedure, that made clear what was required of participants—summarize, not recall—in the case of Adams’ and Jackson and
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Kemper’s studies (here, participants even practised how to write a summary), but not in Byrd’s. So, a tentative conclusion on summarization is that, compared to middle- agers, older adults (60–87 yrs) seem to produce summaries which are more integrative and abstract in nature. In sum, regarding discourse characteristics an emerging picture is that ageing writers are skilled storytellers whose narratives tend to be more complex than those from younger people. Gains in narrative complexity may however trade off with textual cohesion, that tends to diminish in older years (Kemper, 1990). Handwriting. Not surprisingly, handwriting is not immutable across the lifespan: fluency, spatial features, and online pen measures of handwriting undergo age-related changes. A wealth of studies on objective measures of speed have shown that fluency decreases from adulthood to older years (e.g. Caligiuri, Kim, & Landy, 2014; Rosenblum & Werner, 2006). The effect is more marked for unfamiliar tasks, such handwriting the letter h as many times as possible for 20 seconds, than for familiar ones such as word and sentence copying (Dixon, Kurzman, & Friesen, 1993). Older age is associated with longer on-paper time (when the pen is in contact with the writing surface) and longer in-air time, and people over 60 years take significantly longer than younger adults to draw a stroke (Rosenblum & Werner, 2006). Surprisingly, even after factoring out years of education, age accounts for 32% of the variance of in-air stroke time (Rosenblum, Engel-Yeger, & Fogel, 2013). Older adults (64–81 yrs) spend more time than younger ones in the decelerative phase (i.e. from peak to zero velocity) of the movement (Slavin, Philips, & Bradshaw, 1996). Results on accelerative phase (time to peak velocity) are not as clear, but elders seem to perform more acceleration cycles for each movement especially if visual cues such as lines are present (Caligiuri et al., 2014; Slavin et al., 1996). Indeed, younger and older adults might use visual feedback differently during handwriting, older ones resorting more to external visual cues to compensate for less movement efficiency (Slavin et al., 1996). Finally, in the special case of natural signature writing, pen stroke velocity declines linearly and stroke duration increases between 60 and 91 years of age, but changes only reach statistical significance at age 80 (Caligiuri et al., 2014). Turning now to spatial features, of interest are stroke length, cursive vs. print handwriting style, and legibility. An age-related increase in strike length has been observed, but it has not been supported unequivocally. Rosenblum and colleagues (2013) found that participants aged over 76 years wrote significantly longer strokes than middle- aged adults. On the other hand, Slavin et al. (1996) did not find any age effects in stroke length, maybe because some of their older participants fell in the younger-old range (64+ yrs). Another reason for these somewhat inconsistent findings is that variable letter size seems to be characteristic of older writers. For example, compared with 57-to 74-year-olds, participants aged over 75 did not write bigger letters, yet letter size within one word was more variable (Yoon et al., 2013). With regard to cursive vs. print handwriting styles, adults aged above 59 years use cursive more often than younger adults, but both age groups prefer this style for writing quickly (Dixon et al., 1993). Interestingly, older adults (65+ yrs) tend to mix printed and cursive script, and
234 10. The Ageing Writer this mixed style enhances legibility (Van Drempt et al., 2011a). Legibility per se is not affected by increasing age, although handwriting neatness might be (Baxter, 2004; Dettrick-Janes, McCluskey, Lannin, & Scanlan, 2015; Van Drempt et al., 2011a). Error corrections increase with age, with older adults producing around 3 corrections per 100 words, but not do impair legibility (ibid.). Pen pressure is a functional measure of hand strength, whose handwriting components, such as finger-pinch strength and posture, decline with age and compromise not only writing but also other activities of daily living (Rosenblum & Werner, 2006). Older adults (ibid.) maintain their ability to use an adequate tripod pen grip (Van Drempt et al., 2011b). However, the pressure exerted on the pen while writing decreases across the lifespan, with age predicting up to 13% of its variability (Engel- Yeger, Hus, & Rosenblum, 2012), and age effects being more meaningful after 80 years (Caligiuri et al., 2014). Pen lifts is another measure that has been examined in relation to ageing. The number of pen lifts within words of a sentence tends to increase over the years: it doubles from middle age to 75 years (Walton, 1997). Finally, one issue about older adults’ handwriting remains open: are there gender differences? Some studies indicate that women write faster and more legibly than men (Van Drempt, McCluskey, & Lannin, 2011b), and that correlations between age and parameters such as stroke duration, amplitude, and velocity, are statistically significant only in men (e.g. Caligiuri et al., 2014). Nonetheless, other studies reveal no gender differences (e.g. Rosenblum & Werner, 2006) and studies with large samples indicate that patterns of cognitive ageing are similar in men and women (Salthouse, 2010). To sum up, the effect of advancing age on handwriting has been extensively studied and major findings are reduced pen pressure and preserved legibility, possibly at the cost of longer writing time. It is nonetheless important to keep in mind that older persons’ handwriting is more variable (Slavin et al., 1996), and that their own awareness of handwriting difficulties seems to be limited (Rosenblum & Werner, 2006). Typing. In contrast to handwriting, age-related changes in typing have not been subject to much research. A seminal work on skilled typists from 19 to 72 years of age (Salthouse, 1984) revealed improvements in performance well into the seventies. Skilled older typists made fewer transposition errors (so, better control over keystroke sequencing), and had a larger eye-hand span (enhanced anticipation of upcoming characters) than younger ones. Although they were slower in choice reaction time and tapping rate—a sign of age-related perceptuo-motor decline—their typing speed measured by interkeystroke interval (i.e. duration between successive keystrokes) was as good as that of their younger colleagues. Preserved typing speed in the older typists probably comes from enhanced eye-hand span, or advanced planning of the next strokes, which is sign of their domain-specific expertise. Indeed, in non- experts typing speed declines with age. Recruiting from a general population sample, Kalman, Kavé, and Umanski (2015) asked younger (21–31 yrs) and older (65–83 yrs) adults to perform typing tasks that were either simple (e.g. writing the days of the week) or complex (e.g. writing a response to a complaint). Compared with the younger group, older adults typed more slowly and in less quantity and, even though
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they took longer to complete the complex tasks, they spent less time editing, made fewer corrections, and presented more misspellings and mistypings in the final text. Furthermore, older adults edited simple and complex texts for about the same time, whereas younger adults spent more time editing complex texts. Note, however, that Kalman et al.’s (2015) findings cannot be totally attributed to age because there might have been a cohort effect. So, overall, typing speed and accuracy are likely to decrease with age, but typing expertise offsets this effect. Expertise, writing habits, and education influence how writing ability is maintained or changed over time—but age also plays a role. Ageing writers take longer to write, produce more mispellings and less complex sentences, and may suffer from impediments in fine motricity. They are nonetheless skilful storytellers, whose complex narratives make use of a richer lexicon and have a more positive tone.
Age-Related Changes in Executive Control During Writing Different models have been proposed to explain age-related changes in language abilities (for a revision, see Abrams & Farrell, 2010). These models have been thought for language in general but they also apply to the ageing writer, and some of them call upon executive functions as an explanatory factor. Executive control is an integral part of the writing process in that it allows writers to direct and regulate their thoughts and behaviours (Graham, 2018; Olive, this volume). Executive functions can be defined as ‘control mechanisms that modulate the operation of various cognitive subprocesses and thereby regulate the dynamics of human cognition’ (Miyake et al., 2000; for a comprehensive overview, see Chapter 2 of this volume). Researchers agree on at least three major components that are related but contribute separately to executive functioning: attention switching or shifting of mental sets; monitoring and updating of working memory representations; and inhibition of prepotent responses (Miyake et al., 2000). Executive functions are thought to be a key mediator of age-related decline, a relation that may have its biological roots in the volume loss of frontal white matter tracts (Colcombe, Kramer, Erickson, & Scalf, 2005) and in altered midbrain to prefrontal cortex projections of the dopamine system—a neurotransmitter associated with attention and working memory (Braver & Barch, 2002). Indeed, executive functions are so strongly affected by ageing that advanced age has even been considered a model of executive control deficits (West, 1996). There is evidence that executive control diminishes after 60 years of age, gradients of decline depending upon task difficulty and executive process (Treitz, Heyder, & Daum, 2007): inhibitory control and task management or attention switching are particularly affected, but deficits might start to become evident as early as 46 years of age in more difficult tasks, such as processing two sensory channels in parallel. Other factors are years of education and reading and writing habits: both could predict executive functions after 60 years of age (Branco, et al., 2014).
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Explanatory Models for Age-Related Changes in Writing According to general slowing models of ageing (e.g. Salthouse, 1996), as people grow older progressive loss of neural connectivity and neurotransmitters leads to slower information processing (Krampe, 2002). This slowing effect would be independent of the task or mental operations involved (Burke, MacKay, & James, 2000), and the reason why it is more apparent in difficult tasks is because they involve more processing steps (Krampe, 2002). However, others have argued that general slowing models, precisely because they are general, are not able to adequately account for asymmetries in age-related language deficits, such as impaired production of correct spellings and preserved perception of spelling errors (MacKay et al., 1999). It could even be the other way around: older adults do not make more spelling errors because they write more slowly, they write more slowly to avoid making spelling errors (Kalman et al., 2015). In the domain of fine motor skills, general slowing models also have trouble accounting for the reliance on low-vs. high-level processes by healthy older adults. Older adults rely more on low-level timing mechanisms, such as central timekeeping and peripheral motor implementation, that are less affected by age, than on high-level sequencing and executive control processes (Krampe, 2002). By favouring a less age-sensitive component mechanism, healthy older adults are able to maintain adequate performance in tasks involving fine motor skills. This pattern explains why it is only in unfamiliar tasks that older adults’ handwriting is slower compared to younger adults: higher-level executive control is required to perform an unfamiliar than a familiar task (Dixon et al., 1993). Working memory model. An influential explanatory model of age-related changes in writing is the working memory model, based on Baddeley and Hitch’s (1974) notion of working memory. According to the revised version of this prominent theory, working memory refers to ‘a limited capacity system allowing the temporary storage and manipulation of information necessary for such complex tasks as comprehension, learning and reasoning’ (Baddeley, 2000, p. 418). The system involves four components: the central executive which controls attention and integrates multisource information; a phonological loop and a visuospatial sketchpad to temporarily hold verbal-acoustic or visuo-spatial information, respectively; and an episodic buffer that interfaces these two temporary stores with long-term memory. Working memory is crucial for writing—it can be viewed as the space where writing itself develops, or more precisely where text composition happens as a result of the interaction and integration of knowledge, beliefs, and external information (Graham, 2018). According to Kellogg (2008), the most critical component is the central executive. The capacity of the central executive determines the development of writing skills from childhood to adulthood, as it sets the boundaries of the writing space. In order to keep within these boundaries, it is necessary that knowledge can be quickly retrieved from long-term memory and that the writing process is automated. The working memory model has been extensively used to explain changes in writing across the lifespan. In advanced ages, when reading span and the number
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of sentences that can be formulated at each moment are less than in younger years (Kemper et al., 2001b), the importance of working memory capacity and processing become evident. At the lexical level, it might explain the asymmetric pattern of preserved perception, but slower production, of correct and incorrect spellings (production demands more working memory than perception). At the syntactic level, a direct link has been established between working memory and grammatical simplification: people with higher working memory when young show greater decline in grammatical complexity as they age (Kemper et al., 2001b). And discourse complexity is also limited by working memory. This is the case for older adults (64–89 yrs), where age-related changes in working memory predict discourse complexity even when vocabulary, spelling, and handwriting speed are taken into account (Hoskyn & Swanson, 2003). Due to its impact on the planning phase, working memory impairments could also explain the difficulty to compose persuasive arguments that has been observed in older people (Byrd, 1993). In sum, important writing processes may suffer from working memory limitations in late life, from idea generation to sentence and word production. On the bright side, Kellogg (2008) underlines that highly skilled writers aged over 70 maintain very good writing abilities despite working memory deficits. The author proposes that these abilities are based on unceasing deliberate practice and heightened reliance on long-term memory, two aspects that concur to reduce the demands on working memory. It is also plausible that highly skilled older writers use adaptive compensation strategies to reduce working memory load, such as breaking down the writing task into subtasks and defining beforehand the composition goals and plan (Byrd, 1993). A competent use of strategies might also be at the basis of other positive outcomes. Adams (1991) proposed that older people’s ability to write integrative and abstract summaries is due to a highly effective allocation of resources: when task demands overflow working memory resources, older adults direct their attention to the wider themes of the information at hand, and this allows them to focus on the most relevant aspects and discard irrelevant detail. Inhibitory control model. The capacity to voluntarily suppress dominant, automatic, or prepotent responses is, generally speaking, inhibition (Miyake et al., 2000). Inhibitory mechanisms are a ‘narrowly focused processing system’ that ensures accurate and fast information retrieval (Hasher, Lustig, & Zacks, 2007, p. 227). Inhibitory efficiency is a major determinant of cognitive performance. It varies between groups and within individuals, for example according to the circadian rhythm. Impaired inhibitory processes lead to the inability to regulate the contents of working memory and thus irrelevant information may enter there and interfere with ongoing processes (Abrams & Farrell, 2010). Inhibitory control is significantly affected by ageing (e.g. Hasher et al., 2007; McDowd, 1997). For example, in a typical Stroop task where participants are asked to name aloud the colour in which colour words are printed (an action that requires to inhibit the preponderant response of reading the colour word itself), older adults over 61 years present 30% slower reaction times than 20–45 years olds (Treitz et al., 2007).
238 10. The Ageing Writer Inhibitory control, or lack thereof, is a plausible explanatory mechanism for some of the age-related changes in central and output writing processes that we reviewed in the first section of this chapter. Age-related difficulties in orthographical information retrieval in writing tasks (e.g. MacKay & Abrams, 1998; MacKay et al., 1999) might be explained, at least in part, by inhibition deficits: access to orthographical and phonological information might be affected if irrelevant information gains access to working memory and reaches the focus of attention. Reduced syntactic complexity (Kemper, 1987; Kemper et al., 2001b) and increased use of ambiguous anaphoras (not clearly specified pronouns; Kemper, 1990) might also be accounted for lack of inhibitory control, in that working memory might be overloaded with irrelevant contents that add to the difficulty of orchestrating the various steps to produce writing. In output processes, impairments in inhibitory control might also explain why older people have trouble discarding from working memory representations that they know to be inadequate for the ongoing task (Hasher et al., 2007), and why they make fewer corrections and use less time for editing in typing tasks (Kalman et al., 2015). Writer(s)-within-community model. Steve Graham (2018; see Chapter 3 of this volume) proposes the writer(s)-within-community model of writing, an approach that emphasizes executive control mechanisms as part of a system that includes not only writers but also the broader community where they belong. The model expands the cognitive perspective on writing development by proposing that the written product is influenced by the interaction between the writer’s cognitive abilities and the social context of the writing process. This context involves a writing community, that is ‘a group of people who share a basic set of goals and assumptions and use writing to achieve their purposes’ (p. 282). Writing is shaped not only by the capabilities, resources, and intentions of the one who actually composes the text, but also by the others who are involved in the process at large. According to this model, during the writing process both the writer and those who collaborate in text construction (e.g. provide direction, give feedback) make multiple decisions based on their own beliefs, motivations, and abilities, which are, in turn, influenced by previous experiences in writing communities. Writing is constrained by the cognitive mechanisms of writers and their collaborators such as long-term memory resources (e.g. knowledge), control mechanisms (e.g. executive control), production processes (e.g. conceptualization, translating) and modulators (e.g. emotions). Particularly relevant for the present discussion is Graham’s perspective on the importance of executive functions in the writing process, that he views as one of three writing control mechanisms (the others are attention and working memory). According to his view, all components of executive control—namely formulating intentions, planning, monitoring, and reacting—direct and regulate writing actions, and are involved in all writing processes and phases, from content planning and organization, sentence and text composition, to evaluation and reformulation. They also direct and regulate the writers’ emotions and the interaction with collaborators during the writing process. Graham’s views on the link between executive functions and writing set a framework for understanding age effects. Deficits in the formulation of writing intentions
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could lead to hierarchically less complex and structured goals, to the inclusion of irrelevant detail in summaries and to fewer reformulations during the editing phase. Impairments in the planning of writing actions could lead to poor selection or poor creation of schemas for text construction. Monitoring deficits might weaken the cohesion among text sections and compromise the relation between content, writing intentions, and text structure. Finally, impairments in the reacting component would lead to difficulties in the ability to change writing goals, plan, and structure, when needed. The writer(s)-within-community model is a good candidate to provide a conceptual paradigm regarding executive-control abilities of ageing writers, and its predictions should be tested in future experimental studies. In sum, executive control explanations of age-related changes in writing seem able to account for several findings. However, empirical studies to directly examine how executive functions impact writing in older years are scarce, making it difficult to disentangle how age and executive control relate to each other and account for writing performance. In fact, one such study (Rosenblum et al., 2013) found that, beyond age, executive control did not add predictive value to explain handwriting performance, suggesting that the impact of executive control in writing is highly dependent on age. Developmental studies in this research area focus mainly in understanding how younger students’ writing processes are supported by executive functions (e.g. Graham, Harris, & Olinghouse, 2007), a line of research that, to our knowledge, has not been applied to ageing adults. A final comment on the positive aspects of writing in older years, such as elaborate discourse structures (Kemper, 1990) and concise, abstract summaries (Adams, 1991). An interesting idea has been put forward by Adams, Smith, Nyquist and Perlmutter (1997). According to these authors, older adults are better able to comprehend and synthesize the meaning of a narrative thanks to an adaptive cognitive mechanism, through which abstract knowledge structures are developed across the lifespan to make meaning of life events. These positive age-related changes are viewed as an adaptation to counteract lower-level losses, or as a developmental process in cognition that enhances information encoding and storing in higher-level, more integrative, and less fragile units of meaning.
Writing Markers of Dementia In addition to healthy ageing, neurodegenerative diseases are an important source of variability in cognition and, consequently, in writing-related abilities. Indeed, when such diseases are present, the alterations in cognitive abilities are better predicted by disease progression than simply by age (Ganz et al., 2018; Sliwinski, Hofer, & Hall, 2003). We will consider here the impact of dementia and dementia-related infirmities. Dementia-related deficits become apparent in language comprehension and production at relatively early stages of the disease. According to a literature review by Taler and Phillips (2008), neurodegenerative processes impact on all aspects of language, more strongly so at the lexical level and least on syntax. For example, in a
240 10. The Ageing Writer sample of older adults (72 yrs on average, n = 52) diagnosed with mild cognitive impairment (MCI), more than two-thirds had deficits in at least one complex language task, and comprehension of non-literal text such as proverbs and idiomatic expressions was affected the most (Cardoso et al., 2014). Writing impairments show up in early dementia and get worse as the disease progresses. They can be more severe than oral language deficits, and for this reason written descriptions might be a more sensitive and reliable test of language abilities in Alzheimer’s disease than spoken ones (Croisile, 1999; Croisile et al., 1996). On the other hand, written production before the onset of disease may provide markers for predicting dementia later on. Low idea density (average number of ideas per 10 words) and less grammatical complexity are associated with a higher risk of cognitive impairment and Alzheimer’s disease later in life, even for college-educated individuals (Kemper et al., 2001a; Snowdon et al., 1996). These two sides of the coin show that the relationship between writing and dementia is long-term and intricate. Writing processes in dementia no doubt deserve a closer look.
Central Processes in Writing and Dementia Dementia- related writing impairments are complex in nature, and changes in the various components of the writing process are progressive and non-linear. Neurodegenerative diseases are likely to affect first central processes, namely orthographic retrieval, and only later output processes such as typing or handwriting (Croisile, 1999; Hughes, Graham, Patterson, & Hodges, 1997). Nonetheless, the probability of both central and output impairments is likely to increase as the disease worsens (Hughes et al., 1997). Let us first consider the impact on central processes, where it has been shown that dementia initially affects lexico-semantic aspects leading into later effects on discourse and syntax (Croisile et al., 1996). In the less severe case of MCI, writing difficulties show up in sentence length: patients with this disease write shorter sentences than healthy older adults (Press et al., 2012). In Alzheimer’s disease, writing impairments are more striking: not only are sentences shorter, but they also contain more content word errors (e.g. incorrect, incomplete, or omitted words, neologisms, perseverations) and more spelling errors (i.e. missed, added, or substituted letters; Neils, Boller, Gerdeman, & Cole, 1989). Alzheimer’s patients also write less words of all types (nouns, verbs, adjectives, adverbs, and function words), produce fewer information units and include more implausible detail in their sentences and texts (Croisile et al., 1996). On the other hand, these patients (56–89 yrs) do not produce more repetitions nor more semantic errors (replacing a target word by an associate), and attempt error correction as much as same-age healthy controls do (Neils et al., 1989). So, it seems that Alzheimer’s patients cope with difficulties in lexical access by producing less nouns and monitoring their writing performance as their ability to correct errors is preserved.
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Dementia is also associated with an increase in spelling and capitalization errors, as well as errors in punctuation that—interestingly—appear already at the earliest stages of the disease (LaBarge, Smith, Dick, & Storandt, 1992). More specifically, in comparison to healthy controls Alzheimer’s patients produce more spelling errors for homophones (Neils, Roeltgen, & Constantinidou, 1995) and irregular words (Carthery et al., 2005), more so as the disease aggravates. They have trouble retrieving correct spellings and resort to phoneme-grapheme conversion to write a word (Rapcsak, Arthur, Bliklen & Rubens, 1989). The phonological route, or writing by phoneme-to-grapheme matching, seems to be mostly intact, as Alzheimer’s patients can spell regular words and non-words accurately, and their irregular word mispellings preserve phonological correctness (e.g. spelling ONER for ‘honour’; Hughes et al., 1997; Rapcsak et al., 1989). However, other patterns of impairment have also been reported. Preservation of the lexical route (direct retrieval of orthographic representations) and impairment of the phonological one, and impairments in the phonological route and in the semantic system have been described by Luzzatti, Laiacona, & Agazzi (2003). And there are cases too of unimpaired spelling performance for irregular words, indexing an intact lexical route, even in mild stages of dementia (Hughes et al., 1997). Syntax simplifications are a conspicuous marker of Alzheimer’s disease (Croisile et al., 1996). Even very mildly demented patients write sentences with fewer clauses, fewer verbs, and conjunctions, and as dementia progresses embedded and subordinate clauses become less frequent (Kemper et al., 1993). The loss of grammatical complexity that accompanies the disease may be due to diminished working memory capacity, and/or to semantic impairments that would constrain sentence production to simple single clauses (Kemper et al., 1993). Note however that simplicity does not mean incorrectness: Alzheimer’s patients do not produce more grammatical errors than healthy controls (Croisile et al., 1996), and even moderately demented patients are able to write grammatically correct sentences (Kemper et al., 1993). Finally, disease-related impairments in writing also show up at the discourse level. When asked to write a story about a picture, older adults with Alzheimer’s disease sometimes repeat whole sections of the story, a mistake that healthy elders do not commit (Neils et al., 1989).
Output Processes in Writing and Dementia Illegible words, letters crossed out or incorrectly formed, stroke omission or misplacement, and inconsistent lines (sentences written in fragments without keeping to the line) can be collectively referred to as graphic errors. Graphic errors are not common in the early stage of dementia, but they start to be more frequent from middle-stage on, and increase with the severity of the disease (Croisile, 1999; Forbes, Shanks, & Venneri, 2004). However, kinematic measures reveal subtle changes that may already be present in MCI.
242 10. The Ageing Writer MCI patients typically spend longer with the pen off the writing surface than healthy controls, some with writing latencies that are as long as Alzheimer’s (Afonso, Álvarez, Martínez, & Cuetos, 2017). Pen pressure, on the other hand, seems to be preserved in some patients but not in others (Werner et al., 2006). As cognitive functions decline, changes in writing latency, pen pressure and pause length become more apparent, and deficits in all of these measures are common in later stages of dementia (Werner et al., 2006). Regarding writing styles, findings on disease-related changes are mixed. Early- stage Alzheimer’s patients have difficulty in copying single letters and in transcribing them cross-case, i.e. from upper-to lower-case and vice versa (Hughes et al., 1997). There is some evidence that incorrectly mixing upper-and lower-case letters becomes more common as the disease progresses, and that at some point cursive writing may be altogether replaced by writing only in printed style. For example, Forbes, Shanks, & Venneri (2004) reported that mildly impaired patients used a cursive writing style, but half of the moderately impaired ones only wrote in print characters, a shift that probably occurred due to the inability to maintain appropriate case during writing. However, when classifying writing styles as categories instead of using a rating scale with higher scores assigned to cursive style, as did Forbes et al., LaBarge et al. (1992) did not find any differences in style depending on severity of disease. In sum, written language impairments are an important criterion for screening and diagnosing dementia. In early phases, spelling errors, syntactical simplifications, and reduced information units are a sign of concern. Punctuation errors and increased writing latency, when observable, may provide further indices of early disease-related cognitive impairments.
Markers of Dementia in Literary Fiction Writing Researchers have soon taken interest in understanding how real-world texts might reflect pathological conditions of their writers. Already in 1957, the developmental psychologist Madorah Smith (1957) published a case study where she analysed lexical and syntactical characteristics of personal letters written over 40 years by a woman who had been diagnosed with dementia a few years before dying. And more recently, in the context of the Nun Study, Kemper et al. (2001a) examined how written language evolved over a 60-year period in people who aged with, or without, a diagnosis of dementia. But the impact of dementia on writing can also be seen in professional writers, namely authors of fiction writing. An original case study by Garrard, Maloney, Hodges, and Patterson (2005) set the stage. Garrard and colleagues analysed the effects of neurodegenerative processes in the books by Iris Murdoch, a British writer who met criteria for Alzheimer’s disease a few years before her death. They questioned whether her last novel, which had received negative critical reviews and had very likely been written at the first stages of Alzheimer’s disease, would present consistent changes relatively to earlier works,
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namely her first novel and a mid-career novel. Compared to earlier works, Murdoch’s final novel was characterized by a more restricted lexicon: unique word types were fewer and increased more slowly from the start to the end of the text, while already used words were repeated more often. The novel was also syntactically less complex, with significantly less words and clauses per sentence than her earlier novels. On the other hand, other syntactic features such as proportion of word tokens in each grammatical category remained stable. A subsequent study by Van Velzen and Garrard (2008) did a similar analysis on the books by Gerard Reve, a Dutch writer who was diagnosed with Alzheimer’s disease briefly after his last novel was published; again, the earliest stages of Alzheimer’s disease were associated with a decline in lexical diversity. In a recent extension of this research paradigm, linguistic changes in 51 novels by three British writers—one who suffered from Alzheimer’s (Iris Murdoch), one who was suspected of suffering from it (Agatha Christie) and one who aged healthily (P.D. James, a mystery novelist)—were subject to a longitudinal analysis (Le, Lancashire, Hirst, & Jokel, 2011). By comparing the authors’ novels, it was possible to establish a clear distinction between dementia-related language decline and changes associated with healthy ageing, particularly in lexical measures. Both Christie’s and Murdoch’s later novels revealed reduced type-to-token ratio, slower word-type introduction rate, increased repetition of phrases and content words, reduced number of noun tokens and increased number of fillers, a pattern that was absent from James’ novels. Murdoch’s novels presented irregular syntactic changes over the years: syntactic complexity and use of passive voice declined in her 50s, then returned to normal values, and finally declined in her later novels. Nonetheless, over the years the three authors wrote increasingly longer utterances and more clauses per sentence, suggesting that syntax is preserved in the earlier stages of dementia. Linguistic analyses might accurately predict a future diagnosis of dementia, and these markers might be observable from very early on (Snowdon et al., 1996). This applies to the work of professional writers, whose outputs might already present signs of the disease in their 50s (Le et al., 2011). On the other hand, good language abilities as well as engagement in reading and writing, both contribute to cognitive reserve and have a protective role in cognitive ageing (Wilson et al., 2013). Active cognitive interventions can thus be seen as an appropriate method to increase quality of life in later years.
Writing-Based Interventions for Healthy Ageing Successful ageing involves three components: low probability of disease, cognitive and physical functional capacity, and active engagement with life (Rowe & Kahn, 1997). Cognitive activity across the entire lifespan is especially important, as it is associated with slower cognitive decline in later years, and helps build up cognitive reserve— that is, it contributes to delay the negative impact of neuropathological lesions on
244 10. The Ageing Writer cognition (Stern, 2013; Wilson et al., 2013). For example, engaging at least once a week in using the computer, reading books, and writing diaries or letters, is accompanied by reduced prevalence of cognitive impairment (Kurita et al., 2019). And productive writing activities are associated with good mental health (e.g. Chan et al., 2017; Freitag & Schmidt, 2016), possibly due to positive changes in self-concept (Schuster, 1998). A recent systematic review showed that interventions using cognitive leisure activities, such as programmes based on arts, board games, or reading and writing, can improve older adults’ cognitive functions—but to be effective such interventions must have three characteristics. They must afford more intellectual stimulation than daily activities, involve learning new skills and involve communicating with others (Iizuka et al., 2019; see also Aichele, Rabbitt, & Ghisletta, 2016; McDonough et al., 2015). Interventions focused on writing might be particularly relevant because older people usually spend little time in writing activities, and when they do it is mostly in familiar, non-challenging tasks (Van Drempt et al., 2011b). However, studies focusing on understanding the benefits of writing interventions for older adults are scarce. A few have been conducted using autobiographical writing, writing groups, and calligraphy.
Autobiographical Writing Reminiscence activities are considered an important part of the last stage of psychosocial development, because reviewing one’s life cycle is an important step to integrate and accept one’s life (Elford et al., 2005). One specific form of reminiscence that has been used in interventions is life review. It consists of a structured life revision and sense-making process that can be carried out in orally or in writing, solitarily or in group (Chippendale, 2011). Among the psychosocial benefits of life review for older people are cognitive stimulation, namely in relation to memory and handwriting skills, the opportunity to share one’s stories with others and, importantly, emotional insight or catharsis, providing a sense of meaning and purpose (Bohlmeijer, Smit, & Cuijpers, 2003; Elford et al., 2005). Elford and colleagues (2005) proposed an individual life review intervention protocol which can be particularly useful in nursing homes. In each week of a 4-week intervention, participants receive a booklet containing prompts to help them recall memories (e.g. questions regarding childhood), which they fill in at their own pace choosing what to say and share; at the end, they receive a typed booklet with their own complete narrative. Another example is ‘Share your life story’ (Sierpina, 2002, cited by Chippendale, 2011), a life review intervention protocol in group format. In each session of a 8-week intervention, participants receive writing tips, are encouraged to write on the spot and during the corresponding week about a certain decade of their life, and then to read aloud their work to the group. Communication skills are emphasized by encouraging active listening and giving positive feedback to the fellow writers in the group. In a randomized control trial to test the efficacy of this programme to ameliorate depression in institutionalized adults (over 65 yrs), the treatment group had a significant decrease in depressive
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symptoms at post-test, when compared to pre-test and to the wait-list control group (Chippendale & Bear- Lehman, 2012). However, another randomized control trial with healthy older adults failed to find benefits of a different autobiographical writing intervention: participants were introduced to various autobiographical literary genres and were encouraged to produce texts of each genre; neither autobiographical memory nor well-being improved at the end of the intervention (Medeiros et al., 2011). According to the authors, the negative findings might have been due, at least in part, to how autobiographical memory was tested (participants were asked to write extensively at pre and post test). Also, the demand to fit into literary genres might have biased participants to attend to formal aspects, to the detriment of reminiscing proper; and, contrary to the Chippendale and Bear-Lehman’s study (ibid.) participants were healthy adults—probably less liable to improvement than impaired people, for an equivalent dosage of treatment. A more recent study (Freitag & Schmidt, 2016) was conducted with almost 200 community-dwelling adults from 64 to 91 years of age. The authors analysed the effects on frailty and health, physical and mental, of an autobiographical disclosure intervention where participants chose to do it orally (oral reminiscence group) or in writing. For six weeks, participants in the writing conditions would write at home about their daily experiences (daily diary writing group), about their biography in chronological order (unstructured biographical writing group) or about their biography in chronological order following specific questions (structured biographical writing group; participants were randomly assigned to each of the writing groups). Compared to a no-treatment control group and to the unstructured biographical writing group, participants in the other groups improved their scores on frailty and mental health from pre-test to post-test; baseline physical health scores did not change. So, autobiographical life review programmes, either in speaking or in writing with some structure, seem to be beneficial to well-being in older ages.
Writing Groups Writing groups are a challenging form of writing activity. In a writing group intervention, texts are produced, read aloud, and analysed on the spot; they become public immediately after being produced, and receive feedback that can have immediate impact, for instance in altering the direction of the story being created (Blake et al., 2016). Writing groups may encourage older adults’ sense of agency and purpose, and present them with an opportunity to develop a sense of making a relevant contribution or to get recognition from family members and significant others (Schuster, 1998). In the context of nursing homes, being a member of a writing group can create a sense of community within the larger institution, a ‘community bound by words’, with specific common goals and identity (ibd.). As early as 1989, Supiano, Ozminkowski, Campbell, and Lapidos (1989) explored the outcomes of an 8-week writing group intervention in six nursing homes. In each session, the participants
246 10. The Ageing Writer (82 yrs on average) of each nursing home listened to read-aloud poetry or prose on a certain topic (e.g. nature, love, ageing, childhood experiences, memories of war), discussed it, and subsequently engaged in collaborative or individual writing on that topic. Volunteers assisted in text editing, and at the end of each session the texts that had been composed were read aloud to the group and commented upon. The results were promising for well-being: at post-test, compared to a passive control group, the intervention group scored lower on depression indices. But the effect did not extend to cognition, where no differences were found between the two groups. Interestingly, participants whose initial scores of depression or cognitive function were higher were also the ones with lowest scores of depression at post-test—so they may have benefited the most from the intervention. This suggests that writing group interventions hold promise as tools to enhance socioemotional status. But there is still a lot to be learned about the target groups to which writing group interventions would be more suitable.
Other Writing Interventions Could training in calligraphy offer an effective intervention to counteract cognitive impairment? This hypothesis has been tested for MCI using Chinese, a writing system that requires elaborate handwriting skills. Chan and colleagues (2017) designed a randomized control trial where Chinese older people (69 yrs on average) learned Chinese calligraphy with an ink brush (experimental group), or learned how to use a tablet (control group) during an 8-week period. Calligraphy training involved learning to transform the regular Kai script into Hang, a cursive script from the Han dynasty, also known as Xingshu, that is more elaborate and difficult to execute. At post-test, the experimental group had consistently higher scores in divided attention and working memory indices than the tablet group, an advantage that was maintained after a 6- month follow-up. The encoding of visual stimuli and mnemonic strategies involved in the Kai to Hang character transformation seem to have transferred to more general attention and working memory abilities—an interesting case of near transfer effects from learning a challenging calligraphy. Another intervention tool that might be useful is journal writing, which refers to the daily log of personal experiences, typically in a reflective and creative fashion (Shepherd & Aagard, 2011). Journaling is often the way chosen by older adults to make sense of their life-long experiences, since it is a tool for remembrance, reflection, and integration of past events (Brady & Sky, 2003). It offers a space to cope with daily situations and difficult feelings, to experience self-discovery and to find a confident and meaningful inner voice. Journaling activities can be enhanced through the use of web-technologies (e.g. wikis, social networks, photo and video sharing tools, blogs), which may reduce feelings of isolation associated with solitary writing, promote collaboration, and establish learning communities (Shepherd & Aagard, 2011).
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However, to our knowledge there is yet no study that systematically tested journal writing as an intervention tool for healthy ageing. Summing up, several studies have attested the potential of writing-based interventions on socio-emotional aspects in late life. Despite promising results so far, writing interventions to alleviate age-related cognitive impairments are still in an early stage. Because the relation between cognitive activities and cognitive preservation in old age is well-established, one can only expect that writing will become a more common activity for older adults in the coming years.
Concluding Remarks To date, existing studies allow for a relatively well-defined distinction between younger and older adults’ writings, although it should be remarked that age-related changes owe much to individual, contextual, and task differences. A pertinent, still open question is whether cognitive alterations reflected on writing performance change from the middle years on, or undergo an abrupt decline after some point in time. In any case, it becomes increasingly clear that older adults’ writing characteristics are not only modulated by risk factors, such as biological ageing, but also by protective factors, such as adaptive strategies fine-tuned with practice and experience. Evidence is also being gathered to support the role of executive processes, such as working memory and inhibitory control, as predictors of one’s ability to maintain efficient writing performance as one grows older. Importantly, healthy ageing changes in writing performance should be clearly distinguished from dementia-related ones, since neurodegenerative processes present specific, age-independent features in writing tasks. The relevance of using these tasks when assessing dementia emerges from these specificities, which encompass both content and output level writing processes. Besides its potential as a neuropsychological assessment tool, writing might also contribute to the practice and training of cognitive and executive functions, particularly to the specific processes involved in each writing assignment. Moreover, studying the ageing writer in its various facets, cognitive and socioaffective, is a rich research field for the understanding of developmental transformations including the interplay of factors promoting or hindering cognitive processes. The ageing writer reflects a cognitive intricacy of diametric threads, where advanced age meets practice, biological constraints meet wisdom, and decline meets expertise.
Acknowledgment Funded by the Portuguese Foundation for Science and Technology through grant UIDB/00050/2020 awarded to the Center for Psychology at University of Porto.
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References Abrams, L., & Farrell, M.T. (2010). Language processing in normal aging. In J. Guendouzi, F. Loncke, & M.J. Williams (Eds.). The Handbook of Psycholinguistic and Cognitive Processes: Perspectives in Communication Disorders (pp. 49–73). Abingdon, UK: Routledge. Adams, C. (1991). Qualitative age differences in memory for text: a life-span developmental perspective. Psychology and Aging, 6(3), 323–36. Adams, C., Smith, M.C., Nyquist, L., & Perlmutter, M. (1997). Adult age-group differences in recall for the literal and interpretive meanings of narrative text. Journal of Gerontology: Psychological Sciences, 52B(4), 187–95. Afonso, O., Álvarez, C.J., Martínez, C., & Cuetos, F. (2017). Writing difficulties in Alzheimer’s disease and mild cognitive impairment. Reading and Writing, 1, 217–33. Aichele, S., Rabbitt, P., & Ghisletta, P. (2016). Think Fast, Feel Fine, Live Long: a 29-year study of cognition, health, and survival in middle-aged and older adults. Psychological Science, 27(4), 518–29. Aldwin, C.M., Spiro, A., & Park, C.L. (2006). Health, behavior, and optimal aging: a life span developmental perspective. In J.E. Birren & KW. Schaie (Eds.). Handbook of the Psychology of Aging (pp. 85–104). Amsterdam, Netherlands: Elsevier. Baddeley, A.D., & Hitch, G.J. (1974). Working memory. In G.A. Bower (Ed.). The Psychology of Learning and Motivation (pp. 47–89). Cambridge, USA: Academic Press. Baddeley, A. (2000). The episodic buffer: a new component of working memory? Review article. Trends in Cognitive Sciences, 4(11), 417–23. Baxter, S. (2004). Perceptions of handwriting deterioration in older adults. PSIGE Newsletter, 87, 28–34. Blake, V., Hearn, J., Barber, R., Jackson, D., Johnson, R, & Luczynski, Z. (2016). Doing memory work with older men: the practicalities, the process, the potential. Working with Older People, 20(4), 209–13. Bohlmeijer, E., Smit, F., & Cuijpers, P. (2003). Effects of reminiscence and life review on late-life depression: a meta-analysis. International Journal of Geriatric Psychiatry, 18(12), 1088–94. Brady, E.M., & Sky, H.Z. (2003). Journal writing among older learners. Educational Gerontology, 29, 151–63. Branco, L.D., Cotrena, C., Pereira, N., Kochhann, R., & Fonseca, R.P. (2014). Verbal and visuospatial executive functions in healthy elderly: the impact of education and frequency of reading and writing. Dementia & Neuropsychologia, 8(2), 155–61. Braver, T.S., & Barch, D.M. (2002). A theory of cognitive control, aging cognition, and neuromodulation. Neuroscience and Biobehavioral Reviews, 26, 809–17. Bromley, D.B. (1991). Aspects of written language production over adult life. Psychology and Aging, 6(2), 296–308. Burke, D.M., MacKay, D.G., & James, L.E. (2000). Theoretical approaches to language and aging. In T. Perfect & E. Maylor (Eds.). Models of Cognitive Aging (pp. 204–37). Oxford, UK: Oxford University Press. Byrd, M. (1985). Age differences in the ability to recall and summarize textual information. Experimental Aging Research, 11, 87–91. Byrd, M. (1993). Adult age differences in the ability to write prose passages. Educational Gerontology, 19(5), 375–96. Caligiuri, M.P., Kim, C., & Landy, K.M. (2014). Kinematics of signature writing in healthy aging. Journal of Forensic Sciences, 59(4), 1020–4. Cardoso, S., Silva, D., Maroco, J., de Mendonça, A., & Guerreiro, M. (2014). Non-literal language deficits in mild cognitive impairment. Psychogeriatrics, 14, 222–8.
References 249 Carthery, M.T., de Matos Pimenta Parente, M.A., Nitrini, R., Bahia, V.S., & Caramelli, P. (2005). Spelling tasks and Alzheimer’s disease staging. European Journal of Neurology, 12, 907–11. Chan, S.C.C., Chan, C.C.H., Derbie, A.Y., Hui, I., Tan, D.G.H., Pang, M.Y.C., . . . & Fong, K.N.K. (2017). Chinese calligraphy writing for augmenting attentional control and working memory of older adults at risk of mild cognitive impairment: a randomized controlled trial. Journal of Alzheimer’s Disease, 58, 735–46. Chippendale, T. (2011). Life review through writing workshops: lessons learned from successful implementation in a senior residence setting. Physical & Occupational Therapy in Geriatrics, 29(4), 311–19. Chippendale, T., & Bear-Lehman, J. (2012). Effect of life review writing on depressive symptoms in older adults: a randomized controlled trial. American Journal of Occupational Therapy, 66, 438–46. Colcombe, S.J., Kramer, A.F., Erickson, K.I., & Scalf, P. (2005). The implications of cortical recruitment and brain morphology for individual differences in cognitive performance in aging humans. Psychology and Aging, 20(3), 363–75. Croisile, B., Ska, B., Brabant, M.-J., Duchene, A., Lepage, Y., Aimard, G., & Trillet, M. (1996). Comparative study of oral and written picture description in patients with Alzheimer’s disease. Brain and Language, 53, 1–19. Croisile, B. (1999). Agraphia in Alzheimer’s disease. Dementia and Geriatric Cognitive Disorders, 10, 226–30. Dettrick-Janes, M., McCluskey, A., Lannin, N.A., & Scanlan, J.N. (2015). Handwriting legibility in healthy older adults. Physical & Occupational Therapy in Geriatrics, 33(3), 189–203. Devereux, P.G., Heffner, K.L., Doane, M.J., Gosser, B., & Nolan, M. (2016). Identifying attentional deployment tactics in older adults’ written narratives about emotionally upsetting events. Journal of Health Psychology, 21(10), 2247–58. Dixon, R.A., Kurzman, D., & Friesen, I.C. (1993). Handwriting performance in younger and older adults: age, familiarity, and practice effects. Psychology and Aging, 8(3), 360–70. Elford, H., Wilson, F., McKee, K.J., Chung, M.C., Bolton, G., & Goudie, F. (2005). Psychosocial benefits of solitary reminiscence writing: an exploratory study. Aging & Mental Health, 9(4), 305–14. Engel-Yeger, B., Hus, S., & Rosenblum, S. (2012). Age effects on sensory-processing abilities and their impact on handwriting. Canadian Journal of Occupational Therapy, 79(5), 264–74. Forbes, K.E., Shanks, M.F., & Venneri, A. (2004). The evolution of dysgraphia in Alzheimer’s disease. Brain Research Bulletin, 63, 19–24. Freitag, S., & Schmidt, S. (2016). Prevention of frailty through narrative intervention. Social Science & Medicine, 160, 120–7. Ganz, A.B., Beker, N., Hulsman, M., Sikkes, S., Netherlands Brain Bank, Scheltens, P., . . . & Holstege, H. (2018). Neuropathology and cognitive performance in self-reported cognitively healthy centenarians. Acta Neuropathologica Communications, 6(1), 64. Garrard, P., Maloney, L.M., Hodges, J.R., & Patterson, K. (2005). The effects of very early Alzheimer’s disease on the characteristics of writing by a renowned author. Brain, 128, 250–60. Graham, S., Harris, K.R., & Olinghouse, N. (2007). Addressing executive function problems in writing: an example from the self-regulated strategy development model. In L. Meltzer (Ed.). Executive Function in Education: From Theory to Practice (pp. 216–36). New York, USA: Guilford Press. Graham, S. (2018). A writer(s)-within-community model of writing. In C. Bazerman, A. N. Applebee, V.W. Berninger, D. Brandt, S. Graham, J.V. Jeffrey, . . . & Wilcox, K.C. (Eds.). The Lifespan Development of Writing (pp. 272–325). Urbana, USA: National Council of Teachers of English.
250 10. The Ageing Writer Greenwood, P.M. (2007). Functional plasticity in cognitive aging: review and hypothesis. Neuropsychology, 21(6), 657–73. Gutchess, A. (2014). Plasticity of the aging brain: new directions in cognitive neuroscience. Science, 346(6209), 579–82. Hasher, L., Lustig, C., & Zacks, R. (2007). Inhibitory mechanisms and the control of attention. In A.R.A. Conway, C. Jarrold, M.J. Kane, A. Miyake, & J.N. Towse (Eds.). Variation in Working Memory (pp. 227–49). New York, USA: Oxford University Press. Hofer, S.M., & Sliwinski, M.J. (2006). Design and analysis of longitudinal studies on aging. In J.E. Birren & K.W. Schaie (Eds.). Handbook of the Psychology of Aging (pp. 15–37). Amsterdam, Netherlands: Elsevier. Hoskyn, M., & Swanson, H.L. (2003). The relationship between working memory and writing in younger and older adults. Reading and Writing, 16, 759–84. Hughes, J.C., Graham, N., Patterson, K., & Hodges, J.R. (1997). Dysgraphia in mild dementia of Alzheimer’s type. Neuropsychologia, 35(4), 533–45. Iizuka, A., Suzuki, H., Ogawa, S., Kobayashi-Cuya, K.E., Kobayashi, M., Takebayashi, T., & Fujiwara, Y. (2019). Can cognitive leisure activity prevent cognitive decline in older adults? A systematic review of intervention studies. Geriatrics & Gerontology International, 19(6), 469–82. Jackson, J.D., & Kemper, S. (1993). Age differences in summarizing descriptive and procedural texts. Experimental Aging Research, 19(1), 39–51. Kalman, Y., Kavé, G., & Umanski, D. (2015). Writing in a digital world: self-correction while typing in younger and older adults. International Journal of Environmental Research and Public Health, 12(10), 12723–34. Kellogg, R.T. (2008). Training writing skills: a cognitive developmental perspective. Journal of Writing Research, 1(1), 1–26. Kemper, S. (1987). Life- span changes in syntactic complexity. Journal of Gerontology, 42(3), 323–8. Kemper, S. (1990). Adults’ diaries: changes made to written narratives across the life span. Discourse Processes, 13(2), 207–23. Kemper, S., Greiner, L.H., Marquis, J.G., Prenovost, K., & Mitzner, T.L. (2001a). Language decline across the life span: findings from the Nun Study. Psychology and Aging, 16(2), 227–39. Kemper, S., LaBrage, E., Ferraro, F.R., Cheung, H., Cheung, H., & Storandt, M. (1993). On the preservation of syntax in Alzheimer’s disease: evidence from written sentences. Archives of Neurology, 50, 81–6. Kemper, S., Thompson, M., & Marquis, J. (2001b). Longitudinal change in language production: effects of aging and dementia on grammatical complexity and propositional content. Psychology and Aging, 16(4), 600–14. Kramer, A.F., Fabiani, M., & Colcombe, S.J. (2006). Contributions of cognitive neuroscience to the understanding of behavior and aging. In J.E. Birren & K.W. Schaie (Eds.). Handbook of the Psychology of Aging (pp. 57–83). Amsterdam, Netherlands: Elsevier. Krampe, R.T. (2002). Aging, expertise and fine motor movement. Neuroscience and Biobehavioral Reviews, 26, 769–76. Kurita, S., Doi, T., Tsutsumimoto, K., Hotta, R., Nakakubo, S., Kim, M., & Shimada, H. (2019). Cognitive activity in a sitting position is protectively associated with cognitive impairment among older adults. Geriatrics & Gerontology International, 19(2), 98–102. Kynette, D., & Kemper, S. (1986). Aging and the loss of grammatical forms: a cross-sectional study of language performance. Language and Communication, 6, 65–72. LaBarge, E., Smith, D.S., Dick, L., & Storandt, M. (1992). Agraphia in dementia of the Alzheimer type. Archives of Neurology, 49, 1151–6.
References 251 Le, X., Lancashire, I., Hirst, G., & Jokel, R. (2011). Longitudinal detection of dementia through lexical and syntactic changes in writing: a case study of three British novelists. Literary and Linguistic Computing, 26(4), 435–61. Luzzatti, C., Laiacona, M., & Agazzi, D. (2003). Multiple patterns of writing disorders in dementia of the Alzheimer type and their evolution. Neuropsychologia, 4, 759–72. MacKay, D.G., & Abrams, L. (1998). Age-linked declines in retrieving orthographic knowledge: empirical, practical, and theoretical implications. Psychology and Aging, 13(4), 647–62. MacKay, D.G., Abrams, L., & Pedroza, M.J. (1999). Aging on the input versus output side: theoretical implications of age-linked asymmetries between detecting versus retrieving orthographic information. Psychology and Aging, 14(1), 3–17. Margolin, S.J., & Abrams, L. (2007). Individual differences in young and older adults spelling: do good spellers age better than poor spellers? Aging, Neuropsychology, and Cognition, 14, 529–44. McDonough, I.M., Haber, S., Bischof, G.N., & Park, D.C. (2015). The Synapse Project: engagement in mentally challenging activities enhances neural efficiency. Restorative Neurology and Neuroscience, 33(6), 865–82. McDowd, J.M. (1997). Inhibition in attention and aging. Journals of Gerontology Series B: Psychological Science and Social Science, 52, 265–73. Medeiros, K., Mosby, A., Hanley, K.B., Pedraza, M.S., & Brandt, J. (2011). A randomized clinical trial of a writing workshop intervention to improve autobiographical memory and well- being in older adults. International Journal of Geriatric Psychiatry, 26, 803–11. Miyake, A., Friedman, N.P., Emerson, M.J., Witzki, A.H., Howerter, A., & Wager, T.D. (2000). The unity and diversity of executive functions and their contributions to complex ‘frontal lobe’ tasks: a latent variable analysis. Cognitive Psychology, 41, 49–100. Morgan, L.A., & Kunkel, S.R. (2007). Aging, Society, and the Life Course (3rd ed.). New York, NY: Springer Publishing Company. Neils, J., Boller, F., Gerdeman, B., & Cole, M. (1989). Descriptive writing abilities in Alzheimer’s disease. Journal of Clinical and Experimental Neuropsychology, 11(5), 692–8. Neils, J., Roeltgen, D.P., & Constantinidou, F. (1995). Decline in homophone spelling associated with loss of semantic influence on spelling in Alzheimer’s disease. Brain and Language, 49, 27–49. Pennebaker, J.W., & Stone, L.D. (2003). Words of wisdom: language use over the life span. Journal of Personality and Social Psychology, 85(2), 291–301. Press, Y., Velikiy, N., Berzak, A., Tandeter, H., Peleg, R., Freud, T., . . . & Dwolatzky, T. (2012). A retrospective analysis of the sentence writing component of the Mini Mental State Examination: cognitive and affective aspects. Dementia and Geriatric Cognitive Disorders, 33, 125–31. Rapcsak, S., Arthur, S.A., Bliklen, D.A., & Rubens, A.B. (1989). Lexical agraphia in Alzheimer’s disease. Archives of Neurology, 46, 65–8. Reuter-Lorenz, P.A., & Mikels, J.A. (2005). The aging mind and brain: implications of enduring plasticity for behavioral and cultural change. In P. Baltes, P.A. Reuter-Lorenz, & F. Roesler (Eds.). Lifespan Development and the Brain: The Perspective of Biocultural Co-Constructivism. London, UK: Cambridge University Press. Rosenblum, S., & Werner, P. (2006). Assessing the handwriting process in healthy elderly persons using a computerized system. Aging Clinical and Experimental Research, 18(5), 433–9. Rosenblum, S., Engel-Yeger, B., & Fogel, Y. (2013). Age-related changes in executive control and their relationships with activity performance in handwriting. Human Movement Science, 32(2), 363–76. Rowe, J.W., & Kahn, R.L. (1997). Successful aging. The Gerontologist, 37(4), 433–40.
252 10. The Ageing Writer Salthouse, T.A. (1984). Effects of age and skill in typing. Journal of Experimental Psychology: General, 113(3), 345–71. Salthouse, T.A. (1996). The processing-speed theory of adult age differences in cognition. Psychological Review, 103, 403–28. Salthouse, T.A. (2010). Major Issues in Cognitive Aging. New York, NY: Oxford University Press. Salthouse, T. (2012). Consequences of age- related cognitive declines. Annual Review of Psychology, 63(1), 201–6. Schuster, E. (1998). A community bound by words: reflections on a nursing home writing group. Journal of Aging Studies, 12(2), 137–47. Shafto, M.A., & Tyler, L.K. (2014). Language in the aging brain: the network dynamics of cognitive decline and preservation. Science, 346(6209), 583–7. Shepherd, C.E., & Aagard, S. (2011). Journal writing with Web 2.0 tools: a vision for older adults. Educational Gerontology, 37, 606–20. Sierpina, M. (2002). Share your Life Story Workshops. Galveston: University of Texas Medical Branch. Slavin, M.J., Philips, J.G., & Bradshaw, J.L. (1996). Visual cues and the handwriting of older adults: a kinematic analysis. Psychology and Aging, 11(3), 521–6. Sliwinski, M.J., Hofer, S.M., & Hall, C. (2003). Correlated and coupled cognitive change in older adults with and without clinical dementia. Psychology and Aging, 18, 672–83. Smith, M.E. (1957). The application of some measures of language behavior and tension to the letters written by a woman at each decade of her life from 49 to 89 years of age. The Journal of General Psychology, 57(2), 289–95. Snowdon, D.A., Kemper, S.J., Mortimer, J.A., Greiner, L.H., Wekstein, D.R., & Markesbery, W.R. (1996). Linguistic ability in early life and cognitive function and Alzheimer’s disease in late life: findings from the Nun Study. Journal of the American Medical Association, 275(7), 528–32. Spencer, E., Craig, H., Ferguson, A., & Colyvas, K. (2012). Language and ageing –exploring propositional density in written language— stability over time. Clinical Linguistics & Phonetics, 26(9), 743–54. Stern, Y. (2013). Cognitive reserve: implications for assessment and intervention. Folia Phoniatrica et Logopaedica, 65, 49–54. Supiano, K.P., Ozminkowski, R.J., Campbell, R., & Lapidos, C. (1989). Effectiveness of writing groups in nursing homes. The Journal of Applied Gerontology, 8(3), 382–400. Taler, V., & Phillips, N.A. (2008). Language performance in Alzheimer’s disease and mild cognitive impairment: a comparative review. Journal of Clinical and Experimental Neuropsychologicy, 30(5), 501–56. Thornton, R., & Light, L.L. (2006). Language comprehension and production in normal aging. In J.E. Birren & K.W. Schaie (Eds.). Handbook of the Psychology of Aging (pp. 262–87). Amsterdam, Netherlands: Elsevier. Treitz, F.H., Heyder, K., & Daum, I. (2007). Differential course of executive control changes during normal aging. Aging, Neuropsychology, and Cognition, 14, 370–93. Van Drempt, N., McCluskey, A., & Lannin, N.A. (2011a). Handwriting in healthy people aged 65 years and over. Australian Occupational Therapy Journal, 58, 276–286. Van Drempt, N., McCluskey, A., & Lannin, N.A. (2011b). A review of factors that influence adult handwriting performance. Australian Occupational Therapy Journal, 58, 321–8. Van Velzen, M., & Garrard, P. (2008). From hindsight to insight –retrospective analysis of language written by a renowned Alzheimer’s patient. Interdisciplinary Science Reviews, 33(4), 278–86. Walton, J. (1997). Handwriting changes due to aging and Parkinson’s syndrome. Forensic Science International, 88, 197–214.
References 253 Werner, P., Rosenblum, S., Bar-On, G., Heinik, J., & Korczyn, A. (2006). Handwriting process variables discriminating mild Alzheimer’s disease and mild cognitive impairment. Journal of Gerontology: Psychological Sciences, 61B(4), 228–36. West, R.L. (1996). An application of prefrontal cortex function theory to cognitive aging. Psychological Bulletin, 120, 272–92. Williams, L.M., Brown, K.J., Palmer, D., Liddell, B.J., Kemp, A.H., Olivieri, G., Peduto, A., & Gordon, E. (2006). The mellow years?: Neural basis of improving emotional stability over age. Journal of Neuroscience, 26(24), 6422–30. Wilson, R.S., Boyle, P.A., Yu, L., Barnes, L.L., Schneider, J.A., & Bennett, D.A. (2013). Life-span cognitive activity, neuropathologic burden, and cognitive aging. Neurology, 81(4), 314–21. Yoon, J.H., Kim, H., Kim, J., Park, E., & Kim, S.R. (2013). Size variability of handwriting in healthy Korean older adults. Geriatrics & Gerontology International, 14(2), 458–63.
V
CONCLUSIONS AND FUTURE DIRECTIONS
11 Broader Approaches to Defining, Assessing, and Strengthening Executive Control in Writing George McCloskey
Defining Executive Functions As pointed out by Willoughby and Hudson in Chapter 2 of this book and others (Hughes 2011; Jurado & Rosselli, 2007), there is no single, widely accepted definition of executive function (EF), and a review of the literature will yield dozens of different definitions of this multifaceted construct (McCloskey & Perkins, 2013). Many of these define EFs as a collection of cognitive processes that enable conscious direction of feelings, thoughts, and behaviours to achieve intentional goals (Lezak et al., 2004; Welsh & Pennington, 1988). Other models emphasize a hierarchical, supervisory system involving a broad collection of neural mechanisms housed within the prefrontal cortex that can be used to cue, direct, and coordinate perceptions, feelings, thoughts, and actions through the activation of various neural networks extending throughout the brain (McCloskey, Perkins, & Van Diviner, 2009; Stuss & Alexander, 2000; Stuss & Knight, 2012). Beyond these overarching general definitions however, views on the nature and number of EFs and their specific operations are highly diverse. Also noted by Willoughby and Hudson (Chapter 2), many researchers in the fields of cognitive psychology and education are beginning to converge on a definition of EF that includes three core components—inhibition, working memory, and cognitive flexibility (Miyake et al., 2000; Miyake & Friedman, 2012), which are used to guide the discussions of many chapters in this volume. The overarching intention of emphasizing the tripartite model of EFs is to provide a clear conceptual basis for defining and understanding the construct of EF so that research can progress in a more systematic manner. However, as Willoughby and Hudson (Chapter 2) and St. Clair-Thompson and Wen (Chapter 4) illustrate, the narrower tripartite view of EFs often raises as many conceptual and methodological questions as it does answers. Willoughby and Hudson also note that the parsimony of the tripartite configuration has narrowed the scope of cognitive functions that are considered as executive in nature and complicated efforts to clarify how EFs are related to other conceptually similar constructs such as metacognition. George McCloskey, Broader Approaches to Defining, Assessing, and Strengthening Executive Control in Writing In: Executive Functions and Writing. Edited by: Teresa Limpo and Thierry Olive, Oxford University Press. © Oxford University Press 2021. DOI: 10.1093/oso/9780198863564.003.0011
258 11. Broader Approaches In closer alignment with the broader definitions of EFs, Olive (Chapter 9) and Graham (Chapter 3) discuss a large and much more diverse set of executive mental processes that are used to cue, direct, and coordinate the writing process. In Chapter 9, Olive provides a set of well-reasoned inferences drawn from related empirical findings, theoretical perspectives, and astute descriptive analyses of the writing process that detail how EFs are likely to be involved in cueing, directing, and coordinating efficient and effective writing. It should be noted that Olive’s approach to describing EFs and skilled writing also can be applied to identify and describe how EF deficits may lead to inefficient and ineffective writing. In Chapter 3, Graham employs the term executive control (EC) to open the discussion to a much broader set of executive capacities including those that represent self-regulation. Graham offers his views on EC of the writing process within the context of the Writing in the context of Writing within Communities (WWC) model (Graham, 2018), addressing both inter-and intraindividual factors that influence the act of written communication. Graham uses the methods described by Olive to embed within his discussion of the WWC model, a very broad, overarching view of EC and its role in all aspects of the WWC model. When considered collectively, Graham’s descriptions of EC reflect a multidimensional perspective on EFs that is highly consistent with the elements of the Holarchical Model of Executive Functions proposed by McCloskey (HMEF, McCloskey, Perkins, & Van Diviner, 2009; McCloskey & Perkins, 2013; McCloskey, Gilmartin, & Stanco, 2014). Similar to Graham’s shift to the construct of EC, the HMEF has been referred to in recent years as the Holarchical Model of Executive Capacities and the Holarchical Model of Executive Control (HMEC) to account for the model’s emphasis on multiple tiers of EC and the need to distinguish between the awareness of knowing when to cue (EFs) and the awareness of knowing how to direct (executive skills) the use of other mental resources (McCloskey, 2021). When considered in tandem and operating at multiple levels, EFs and executive skills collectively are referred to as executive capacities that are engaged in EC. Within the HMEC, awareness of knowing when to cue and how to direct mental processing is exercised from increasingly broader perspectives of control by successively fewer executive capacities, similar to the organization of the management structure of a corporation. Expanding on this metaphor, EC represents the operations of the brain’s supervisory system. Within the HMEC, first tier executive capacities are involved in cueing, directing, and coordinating the mental resources necessary to engage in self- regulation throughout the day. The HMEC stipulates that EC can be exerted over all domains of function—perceptions, feelings, thoughts, and actions. In the context of the writing process, effective functioning at the self-regulation level of the HMEC requires awareness of when to cue, and how to direct and coordinate, the use of mental resources to engage the writing process. The HMEC specifies 33 mental resources—organized within 7 clusters—that are cued, directed, and coordinated through EC to achieve self-regulation (see Box 11.1 for descriptions of the mental resources that can be executively controlled and their functions during the writing process.)
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Box 11.1 First tier EF self-regulation of the mental resources involved in the writing process Attention cluster Perceive/Aware—cueing and directing awareness of the need to engage the writing process. Focus—cueing and directing attention to the specific details of the writing process. Sustain—cueing and directing sustained engagement of attention to writing processes as long as necessary (or as long as possible before a rest break is necessary).
Engagement cluster Initiate—cueing and directing initiation of the steps in the writing process Energize—cueing and directing the application of adequate energy and effort while engaged in the writing process. Inhibit—cueing and directing the inhibition of impulses or urges that are counterproductive to the writing process; resistance to sudden urges to disengage with the writing process and cueing the avoidance of, or ignoring of, distracting stimuli. Stop—cueing and directing the cessation of thoughts, feelings, or actions that may be interfering with the writing process. Interrupt—cueing and directing the interruption of, and return to, the writing process when a pause is required. Flexible—cueing and directing the realization of the need to consider alternative possibilities when engaged in one or more steps of the writing process. Shift—cueing and directing the shift from one set of perceptions or thoughts about the writing process to another or from one emotional state or one action, to another during the writing process.
Optimization cluster Modulate—cueing and directing the adjustment of the intensity of perceptions, feelings, thoughts, and actions while engaged in the writing process. Monitor—cueing and directing the monitoring of written production to ensure alignment with goals and intentions; cueing and directing the checking of written material for accuracy of grammar, word use, and meaning. Correct—cueing and directing the correction of errors in written production based on feedback from internal or external monitoring sources. Balance—cueing and directing the balancing of elements of the writing product (e.g. giving equal weight to multiple perspectives when appropriate) or the writing process (e.g. ensuring that adequate time, energy, and effort are applied to each step in the writing process).
260 11. Broader Approaches
Efficiency cluster Sense Time—cueing and directing a sense of the passage of time while engaged in the writing process. Pace—cueing and directing regulation of the rate at which perceptions, thoughts, or actions are performed during the writing process. Using routines—cueing and directing the activation of well-known series of perceptions, feelings, thoughts, and/or actions when engaged in the writing process, especially in cases where automated routines have been practised and used frequently. Sequence—cueing and directing the ordering of a series of perceptions, feelings, thoughts, and/or actions while writing, especially in cases where automated routines are being accessed or are initially being developed.
Memory cluster Hold—cueing and directing the holding of specific perceptions, feelings, thoughts, and actions for a brief period of time when engaged in the writing process. Manipulate— cueing and directing the manipulation of perceptions, feelings, thoughts, or actions as they are being held in mind when engaged in the writing process. Store—cueing and directing the storing of specific perceptions, feelings, thoughts, and actions so that they can be retrieved as needed at a later time during the writing process. Retrieve—cueing and directing the retrieval of previously stored information about perceptions, feelings, thoughts, and actions when engaged in the writing process.
Inquiry cluster Gauge—cueing and directing the ‘sizing up’ of the demands of a task in order to know the perceptions, emotions, thoughts, or actions needed to effectively engage with the writing process. Anticipate/Foresee—cueing and directing the ability to project into the future to envision writing goals and anticipate audience reactions to what is written. Estimate Time—cueing and directing the process of estimating how long it will take to complete one or more steps of the writing process or estimating how much time is left in a specific period of time that was allotted for the writing process. Analyse—cueing and directing the close examination of perceptions, feelings, thoughts, or actions to obtain a greater understanding of a problem or situation when engaged in the writing process. Evaluate/ Compare— cueing and directing the making of comparisons or the judging of the adequacy of writing production.
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Solution cluster Associate—cueing and directing the identification of connections between ideas and strategies that have been used in the past with situations being encountered during the current writing process. Generate—cueing and directing the resources needed to carry out novel problem- solving routines. Organize—cueing and directing the meaningful arrangement of ideas and text during the writing process. Plan (short-term)—cueing and directing the specification of a series of actions that, if carried out, would be likely to produce a desired outcome in the very near future (within minutes to within several hours). Prioritize—cueing and directing the ordering of thoughts, and/or actions according to their relevance or importance to the writing process or the final written product. Choose/Decide—cue and directing the use of choice or decision-making processes during the writing process.
Within the HMEC, the operations of the second, third, and fourth tiers address many aspects of EC of the writing process within the context of the writing community as described by Graham. Second tier EC within the HMEC involves awareness of when and how to activate self-determination, which involves goal setting and long-term planning to achieve goals. Additionally, this tier consciously activates self- realization which involves awareness of self, awareness of self in relation to others, and the capacity for self-evaluation and self-reflection as well as evaluation of and reflection on the self in relation to others. To fully grasp the nature of the writing community, the relationship of personal goals and the writing community’s goals and needs and the needs and characteristics of the audience that the writing product is intended to reach, the writer needs to be exerting EC to know when and how to effectively activate self-determination and self-realization. The third tier of EC within the HMEC involves an awareness of when and how to activate self-generation, which involves an awareness of the need to establish, evaluate, and modify a moral and ethical stance that can be used to guide self-determination and self-realization. It is not enough to have goals for writing that are established through a self-realized appraisal of the needs of the self, the community, and the self within the community. These goals and needs must be subjected to careful scrutiny to ensure that the writing product will reflect a moral and ethical stance based on good intentions, discernment of the difference between right and wrong and good and bad, and compassionate treatment of self and others. Graham discusses at length the influence of the writing community on the writer, as well as the writer’s influence
262 11. Broader Approaches on the writing community. Although a writer and a written product may be in alignment with the characteristics of the community, it must be acknowledged that not all writing communities have good intentions and not all writing products will have a positive effect on audiences. Writers must be aware of the need to engage EC at this level to ensure that their involvement with the writing community is based on good intentions, that the writing product will have positive effects on the audience, and that the activities of the community and the writer reflect a compassionate treatment of self and others. The fourth and final tier of the HMEC, referred to as trans-self-integration, addresses awareness of a greater sense of connection that extends beyond self and the writing community and includes all communities, all of humanity, and all of existence. Using the metaphor of the corporate management structure, this tier addresses the issue of the CEO. This tier involves an awareness of the need to state, and seek an answer to, a fundamental question: is there a singular, highest level of EC that directs the moral and ethical resources of the self-generation tier? If such a control process exists, where does it reside? Do you believe that you answer to a higher power? Do you believe that the CEO resides strictly within the neural mechanisms of your brain? Or do you believe that there is no CEO? Although some may find this level to be the stuff of pure metaphysical speculation, an objective line of scientific research has focused on this level (Lama & Ekman, 2008; Newberg, 2010). Taken together, the HMEC offers a comprehensive view of EC that is akin to a spectrum of consciousness. Adopting a broad multidimensional model of EC enables researchers, educators, and clinicians to acknowledge the interrelationship of various forms of EC and their simultaneous activation when children, adolescents, and adults are engaged in the writing process. A multidimensional model of EC also provides the framework needed to address all aspects of EC involvement in the writing process as elaborated in the WWC model.
Assessment of Executive Functions in the Context of Writing Processes In Chapter 4, St. Claire-Thompson and Wen describe measures of EF designed to assess inhibition, working memory and cognitive flexibility but do not discuss how performance on these domain-general EF measures are associated with assessment of the writing process or completion of a writing product. Willoughby and Hudson (Chapter 2) and Hooper, et. al (Chapter 6) also offer discussions of EF assessment in the context of the tripartite EF model (with planning added in the Hooper et al. chapter). In Chapter 5, Dockrell and Connelly discuss the topic of assessing writing, with brief mention of the relationship between working memory and writing, but without reference to specific measures of working memory. It is important to note that none of these chapters describes methods for the assessment of EFs as they are being used to cue, direct, and coordinate the writing process. This fact highlights a
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significant blind spot for research that is focused on understanding how EFs are involved in the writing process. Issues related to the assessment of EFs. As noted in Chapters 2, 4, and 6, the two primary forms of EF assessment currently used are individually-administered, norm-referenced tests that assess inhibition, working memory and cognitive flexibility and norm-referenced behaviour rating scales that assess rater perceptions of the adequacy of performance of a wide range of behaviours thought to be associated with the use or disuse of EFs. The shortcomings of both types of EF measures were discussed in these chapters, and included the lack of consistency of results in test-retest conditions and with different measures designed to assess the same EF as well as between individually-administered measures of EF and behaviour rating scales. From the perspective of the HMEC, there are additional shortcomings of currently used EF measures that reduce their validity, some of which may help to explain the lack of consistency between the results of individually-administered tests and behaviour rating scales. Two basic tenets of the HMEC are that EC varies based on the domains of functioning (perception, emotion, cognition, and action) and Arenas of Involvement (management of self, self in relation to others, self in relation to the environment, and self in relation to the use of symbol systems for processing information). The HMEC proposes that EC can be used to cue and direct the use of mental resources when a person is engaged in perceiving, feeling, thinking, or acting and that EC across these domains of functioning is dissociable (e.g. a person can be good at cueing and directing thinking, but poor at cueing and directing emotion and vice versa). Likewise, EC can be used to cue and direct the use of mental resources based on the arena that provides the context for their perceptions, feelings, thoughts and actions, and EC across these contexts is dissociable (e.g. a person can be good at cueing and directing self-management when alone, but poor at cueing and directing of self when involved with others). From the perspective of the HMEC, individually- administered standardized tests of EF only assess the use of EFs to direct mental resources involving perceiving, thinking, and acting and only in the context of tasks assessing symbol system information processing. These measures do not address EF direction of emotions when performing specific symbol system tasks, and they do not assess EF in the contexts of self-management, management of self in relation to others, or management of self in relation to the environment. Although rating scales have the potential to assess the use of EF across all four domains of functioning within all four contexts, none of the behaviour rating scales currently available were designed to provide such a systematic coverage. The result is an amalgam of items describing behaviours that inconsistently address EC of perception, emotion, cognition, and action and inconsistently make reference to one or more of the four contexts within which EC can be exerted. The most recently developed of these rating scales however—the McCloskey Executive Functions Scales (McCloskey, 2016, 2021)—is based on the HMEC, but considerations related to test length necessitated the reconfiguration of the four Arenas of
264 11. Broader Approaches Involvement into two—an Academic Arena (focusing on managing self during the use of symbol system information processing and some aspects of managing self in relation to the environment) and a Self/Social Arena (focusing on self-management and management of self in relation to others). Issues related to the assessment of EFs and writing. It is important to recognize that EFs cannot be assessed ‘in a vacuum’ (McCloskey, Perkins, & Van Diviner, 2009; McCloskey & Perkins, 2013; Stuss & Levine, 2002), that is, EFs cannot be meaningfully assessed without consideration of the mental resources that they are directing and the specifics of the task. It is important to avoid overgeneralization of results obtained with measures thought to be domain-general measures of EFs, as research and clinical practice have documented that EF use can vary greatly depending on the tasks being used in assessment. The most effective forms of assessment of EC of the writing process therefore would involve tasks that require the use of EFs while performing a writing task or a writing-related task, but such tasks have yet to be developed and standardized for use in clinical practice. In fact, the difficulties with assessing EC of the writing process are compounded by the limited availability of reliable and valid tasks that assess the writing process even without consideration of the assessment of EC. In their chapter, Dockrell and Connelly note that the field lacks consensus about what constitutes proficiency at various points in the development of writing skills and of specific methods used to assess writing proficiency. Dockrell and Connelly reference a standardized group test used in the UK as an example of the deficiencies of current methods used to assess writing skills. Methods for assessing EF involvement in the writing process. Considering the current state of writing assessment in the United States, McCloskey and Perkins (2013) describe a cascading production analysis (CPA) methodology that can be used to structure the assessment of EFs involvement in various tasks. The CPA methodology is used to identify cascading production decrements. Cascading production decrements are most likely to occur when alterations of task demands involve an increase in the need for engagement of one or more EFs to cue and direct mental resources to successfully perform a task. The steps in CPA involve: (1) administration of a task that does not require much cueing and directing for completion, referred to as an EF-minimized task. EF-minimized tasks are usually subtests from standardized batteries that provide very explicit directions, telling the examinee what to do and when to do it, and demonstrating at length how to do it using sample item explanations and teaching items, as well as tasks that, when mastered, can be performed with automaticity (e.g. rapid naming of letters and words, rapid naming of numbers, alphabet writing, judging whether the visual images of words match or do not match). (2) Administer a variant of the baseline task that additionally requires the use EFs for successful performance (e.g. requiring the frequent shifting between rapid naming of words and rapid naming of numbers). These tests are referred to as EF-saturated or EF+ tasks. (3) Compare the norm-referenced scores obtained on the EF-minimized baseline task with the norm-referenced score on the EF-saturated task. When the EF-minimized score is in the average range or better (GTE 25th percentile) and the
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EF-saturated task score is significantly lower than the EF-minimized task, it can be hypothesized that the decrement in performance is due to the increased EF demands of the EF+ task. As a case in point, the CPA methodology can be employed with one of the tasks described by St. Clair-Thompson and Wen in Chapter 4—the Stroop Test in the form of the Delis-Kaplan Executive Function System Color-Word Interference Subtest (D-KEFS; Delis, Kaplan, & Kramer, 2001), which involves activation of neural networks involved in the processing of orthography. As a writing-related task, this test has the potential to provide meaningful results for assessing some aspects of EC that may be needed to successfully complete writing tasks. The Color-Word Interference Subtest first requires examinees to perform a rapid naming task that minimizes EF involvement—reading rows of randomly ordered colour name words (red, blue, green) as quickly as possible. This task establishes a baseline as rapid sight word reading is typically automated by proficient readers (and writers) and likely to require minimal involvement of EFs for effective performance. The baseline task is followed with the administration of the Inhibition task, a variant of the baseline task in which the examinee is presented with rows of colour name words printed in different coloured ink (e.g. the word red printed in blue ink) and instructed to say the colour of the ink in which each word is printed (e.g. saying blue when viewing the word red printed in blue ink) as quickly as possible instead of reading the words. The ink-colour naming condition typically requires the use of EF to cue and direct the inhibition of the natural urge to read the wordsinstead of stating the ink colour of each word. A cascading production decrement is observed when the norm-referenced score obtained with the ink colour naming Inhibition task is significantly lower than the norm-referenced score obtained with the Word Reading baseline task. This pattern of test results offers support for the hypothesis that the reduced ink colour naming score reflects a difficulty in the use of EF to cue and direct the inhibition of the subordinate automated cognitive process of rapid word naming while managing the rapid performance of the non-automated ink colour naming task. The comparison of the EF+ condition with the baseline EF-minimized condition is critical to support of the hypothesis that the low Stroop-effect Inhibition score is due to the addition of the EF demands rather than a deficit in the subordinate automated rapid naming process. Although Stroop-like tasks involve rapid word naming and the inhibition of word reading, studies have established the relationship between results of the Stroop test and some measures of writing proficiency (Peverly & Sumowski, 2012). The D-KEFS adds a third condition to their Stroop-like task that extends the potential for the CPA to yield an additional decrement in performance due to difficulties with cueing, directing, and coordinating a greater number of EFs (an gEF++ condition). In the EF++ condition, the examinee views a page with colour name words printed in different ink colours with the occasional addition of a rectangular shape enclosing a word. The examinee is instructed to say the colour of the ink in which the word is printed unless there is a ‘box’ around the word, in which case, the examinee is to say the word instead of name the colour of the ink. In this condition, inhibition of
266 11. Broader Approaches rapid automatic naming and management of the non-automated ink colour naming task are joined by the need to shift from ink colour naming back to rapid word reading when encountering a rectangular shape enclosing a word. This format allows for the possible occurrence of an additional cascading production decrement when the norm-referenced score for the combined inhibition-switching task is significantly lower than the norm-referenced score obtained with the ink colour naming (inhibition) task. The additional decrement lends support to the hypothesis that increasing demands for EFs for a task involving the processing of orthography further reduces the examinees ability to perform effectively. Ideally however, CPA methodology should be applied to tasks that assess writing. To date, however, no specific writing tasks have been developed and standardized using the CPA methodology. In the absence of tasks specifically designed to assess EF involvement in the writing process, McCloskey and Perkins (2013) offered guidelines for a cross-battery approach that could be used to assemble the tasks needed to conduct a CPA to assess the effects of increased demand for EF involvement for task performance. A major limitation to applying the guidelines, as noted earlier, is the fact that the tasks currently available to assess writing do not conform to a consensus model of how to assess the development of writing skills. Two examples are provided here to illustrate how CPA can be applied to test hypotheses related to the effects of EF demands on task performance. The first example applies CPA to text transcription skill assessments using the Process Assessment of the Learner-Second Edition (PAL-II; Berninger, 2007) Alphabet Writing task for the baseline and the Copying A and Copying B tasks as EF+ and EF++ tasks. The PAL-II Copying A and Copying B tasks are likely to involve EFs to sustain the writing process for prolonged periods of time. A cascading production decrement is observed when the norm-referenced scores obtained with the Copying A and Copying B task are significantly lower than the norm-referenced scores obtained with the Alphabet Writing baseline task. This pattern of test results offers support for the hypothesis that the reduced sentence copying scores reflect a difficulty in the use of EFs to cue and direct sustained attention and effort and the inhibition of distracting stimuli while performing a task involving automated letter writing. The comparison of the EF+ sentence copying conditions with the EF-minimized baseline alphabet writing condition is critical to support of the hypothesis that the low sentence copying scores are due to the addition of the EF demands of the task rather than a deficit in the automaticity of alphabet writing. The inclusion of the Copying B task allows for the possible occurrence of an additional cascading production decrement (EF++) when the norm-referenced scores for the paragraph Copying B task are significantly lower than the norm-referenced scores obtained with the sentence Copying A task. The additional decrement lends support to the hypothesis that increasing the length of time required for the application of EFs of a task involving the automated task of letter writing further reduces the examinees ability to perform effectively.
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The second example applies CPA to text generation (translation) skill fluency. Because of the multiple abilities, processes, skills, and knowledge bases that contribute to the translation of thoughts about language into text that represents that language, multiple EF-minimized baseline tasks are used to establish the adequacy of these cognitive components when task scores are in the average or above range. In this example, The PAL-II Alphabet Writing and Copying tasks are administered to estimate the automaticity of text transcription (handwriting fluency) skills; the Kaufman Test of Educational Achievement—Third Edition (KTEA-3; Kaufman, 2014) Spelling Subtest is administered to estimate of the adequacy of word spelling skills; the KTEA- 3 Oral Expression Subtest is administered to estimate the adequacy of expressive language abilities; the WJ-IV Tests of Oral Language (WJ-IV; Schrank, Mather & McGrew, 2014a) Story Recall Subtest is administered to estimate the adequacy of expressive language skills and working memory capacity; the Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V; Wechsler 2014) Vocabulary Subtest is administered to estimate the adequacy of word knowledge, retrieval from long-term storage capability, and expressive language abilities; and the NEPSY-II (Korkman, Kirk, & Kemp, 2007) Word Generation Semantic and Initial Letter tasks are administered to estimate the adequacy of word storage and word retrieval fluency. All of these tasks collectively serve as the EF-minimized baseline when the obtained scores are in the average range or above. Administration of the baseline tasks is followed by administration of the KTEA- 3 Sentence Writing Fluency Subtest (SWF) and the WJ-IV Tests of Achievement (Schrank, Mather, & McGrew, 2014b) Writing Fluency Subtest (WF;). These tasks are likely to involve EC to sustain the translation process for several minutes. Each item of the KTEA-3 SWF requires the child to look at a picture and write a brief sentence about the picture. The child is instructed to write as many sentences as possible in a period of three minutes. The task score is the number of words written in the 3-minute time period. Each item of the WJ-IV WF requires the child to view three words and a picture and write a sentence that describes the picture that includes the three words in the same grammatical form (for example the word book cannot be changed to books; the word helped cannot be changed to help or is helping). The child is instructed to write as many sentences as possible in a period of five minutes. It is hypothesized that performance of the KTEA-3 SWF will require greater involvement of EFs to sustain effort and attention and inhibit response to distractions until completion of the task than any of the baseline tasks. Likewise, it is hypothesized that the WJ-IV WF’s use of constraints on the writing task (using the three words provided in their current grammatical form) will further increase the need for EC and/or may overtax the child’s ability to maintain EC. The scoring methods applied to these two tasks also strengthen the hypotheses related to EC. The KTEA-3 SWF sums the number of words written for every sentence to obtain the subtest score, ensuring that no penalty is incurred for writing longer sentences. In contrast, the WJ-IV WF only assigns a score of 1 to each sentence that uses the three words correctly in a grammatically correct sentence. In
268 11. Broader Approaches the case of the WJ-IV, a child is penalized by loss of time if they write longer sentences because each sentence can only earn 1 point, regardless of its length. A cascading production decrement is observed when the norm-referenced scores obtained with the KTEA-3 SWF and the WJ-IV WF are significantly lower than the norm-referenced scores obtained with the baseline tasks. This pattern of test results offers support for the hypothesis that the text translation tasks reflect a difficulty in the use of EC to cue and direct sustained attention and effort and the inhibition of responding to distracting stimuli while performing a task that requires additional EC to coordinate the simultaneous use of language abilities, handwriting fluency, spelling skills, word knowledge, and word retrieval fluency. The comparison of the sentence writing fluency tasks with the EF-minimized baseline tasks is critical to support the hypothesis that the lower sentence writing fluency scores are due to the addition of the EF demands of the task rather than deficits in baseline abilities, skills, processes, or knowledge bases. The inclusion of the WJ-IV WF allows for the possible occurrence of an additional cascading production decrement when the norm-referenced score obtained with the WJ-IV WF EF++ task is significantly lower than the norm- referenced score obtained with the KTEA-3 SWF EF+ task. The additional decrement lends support to the hypothesis that placing constraints on the writing task, scoring individual sentences rather than number of words written, and requiring sustained effort for a longer period of time further reduces the examinees ability to use EFs to perform effectively. Additionally, if the score obtained with the NEPSY-II Semantic Word Generation EF-minimized task is in the average or above range and the score obtained with the NEPSY-II Initial Letter Generation EF+ task is significantly lower than the Semantic Word Generation score, the Initial Letter Word Generation task score also is considered to reflect a cascading production decrement reflective of difficulties with executive direction of the retrieval of words from long-term storage due to the addition of the constraint on retrieval that requires retrieving and saying only words that begin with a specific letter. In such cases, it can be hypothesized that the lower initial letter word retrieval performance may be contributing to the relatively poor performance of the sentence writing fluency tasks. The use of the CPA methods discussed here have been applied in clinical settings with individual cases and are based on hypotheses supported by the findings of research studies investigating the relationships among the various tasks used in the analyses and the methods used to construct various measures thought to assess EFs. I have used these techniques for several decades to help teachers, educational administrators, parents, and children themselves to understand that the writing difficulties these children are experiencing are not a matter of indifference, apathy, lack of motivation, oppositional defiance, or character flaws, but rather the result of difficulties with the use of EC processes. Additionally, these techniques have helped to identify interventions such as those discussed in the chapter by Mason and Brady that could be implemented to assist children struggling with EC difficulties. It is important to note that these CPA methods have not been rigorously examined in
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controlled research studies. It is hoped that the discussion of the CPA methods provided here and described in more detail elsewhere (McCloskey, Perkins, & Van Diviner, 2009; McCloskey & Perkins, 2013) will spur interest in performing such research studies. In the interim, clinicians are encouraged to adopt a pragmatic approach by trying, objectively documenting, critically evaluating, and sharing the results of their applications of the CPA approach to the assessment of EF involvement in writing tasks.
Instruction and Intervention for Improving Writing Skills When EF Difficulties Are Suspected In Chapter 8, Mason and Brady put forth the premise that skilled writers use EFs in a conscious, purposeful, and thoughtful manner to cue, direct, and coordinate the mental resources needed to guide the writing process and craft written products that communicate effectively to intended audiences within the context of the writing community. Conversely, they propose that poor writers are less likely to know what they should be doing to cue and guide the writing process, and are less aware of when and how to exert control while engaged with a writing task. Instruction and intervention efforts targeted at improving writing skills therefore should increase writers’ awareness of the need to engage EFs to drive the writing process and teach techniques intended improve their ability to do so. Much of the literature establishing the effectiveness of integrating instruction on the strengthening of EFs with instruction on strategies for completing writing tasks involves the self-regulated strategy development (SRSD) approach (originally referred to as self-instructional strategy training) pioneered by Graham and Harris in the 1980s. Mason and Brady’s review makes clear the fact that the most successful interventions apply multiple techniques to ensure that students develop an awareness of what EFs are needed to achieve writing goals, when these EFs need to be applied during the writing process, and how these EFs can be activated and applied during the writing process. Successful interventions teach writers strategies that can be used to complete a writing task. These strategies teach students when and how to analyse a writing task, make decisions about what to write to meet the demands of the writing task, plan what to write, focus, and sustain attention throughout the writing task, identify the resources needed to initiate and complete the writing task, and how to apply all of these in a flexible, recursive manner. These techniques strengthen writers’ awareness of, and capacity for engaging in, self-regulation to self-manage the writing process by specifically teaching how to employ multiple aspects of self- regulation, including goal setting and understanding of expectations, self-monitoring the writing process and writing progress, guiding the writing process through the use of self-reflection and self-talk, and self-administered reinforcement to sustain motivation and effort. Also, they are intended to increase writers’ self-efficacy related to the writing process, which has the added benefit of increasing writers’ motivation to
270 11. Broader Approaches engage in the writing process, and in turn the likelihood that writers will employ the strategies to sustain and improve their effective writing skills. In Chapter 3, Graham utilizes a broader perspective when providing recommendations for strengthening writers’ EC of the writing process. These include: (1) provide a clear context for the writing process by specifying goals and expectations and teach strategies that can be used to meet these goals and expectations; (2) fully engage students in the writing process through personal goal setting, purpose clarification, and modifications to strategies for writing; (3) use social modelling by talking writers through the steps while modelling the self-talk that could be used to self-regulate the writing process; (4) teach specific self-regulation strategies (self-monitoring, self- talk, self-reinforcement) or strategies that teach the what, when and how needed to exert EC over mental resources; (5) promote flexible and inventive uses of all elements taught as well as those generated by students and guide writers through exercises the encourage them to think about how to adapt techniques to different situations or settings; (6) employ methods likely to maximize student motivation and engagement in the writing process (e.g. self-selection of topics, communication to authentic audiences); (7) provide writing environments (physical and psychological) that reduce the impact of factors that can lead to EC difficulties (e.g. providing quiet places, creating timelines, nurturing positive beliefs); (8) reduce the variability within and across environments that can interfere with writers’ abilities to use EC by monitoring teaching practices within the writing environment and discussing their use across environments and different writers.
A Generalized Model for Strengthening the Use of EFs in Varying Contexts The research findings reviewed by Mason and Brady and the recommendations provided by Graham specify the methods that can be used effectively to strengthen writers’ use of EFs to improve their ability to self-regulate the writing process, communicate effectively to audiences, and function within the context of the writing community. It should come as no surprise that the techniques employed in SRSD instruction are consistent with effective, evidence-based practices used in many different settings and contexts to help individuals improve their use of EFs. A general framework for these practices is describe by McCloskey, Gilmartin, and Stanco (2014) in relation to instructing students with learning disabilities. Table 11.1 shows a side-by-side comparison of the steps in SRSD instruction described by Mason and Brady in Chapter 8, the general recommendations for enhancing developing writers’ EC provided by Graham in Chapter 3, and the EC intervention continuum described by McCloskey (McCloskey et al., 2014; McCloskey 2020). The EC intervention continuum was developed based on extensive literature reviews conducted in the preparation of one book (McCloskey, Perkins, & Van Diviner, 2009) and several book chapters (McCloskey, Allen, & Harne, 2017; McCloskey, Gilmartin, & Stanco, 2014;
Table 11.1 Comparison of SRSD, executive control enhancement recommendations, and the executive control intervention continuum Steps in SRSD Instruction (Graham & Harris as described by Mason and Brady)
Graham’s Recommendations For Enhancing Writers’ Executive Control
The Executive Control Intervention Continuum (McCloskey, et al. 2014)
1. Develop background
2. Ensure that writers understand the context and expectations and ways to accomplish tasks
1. Orienting phase Self-realization: Understanding the context Identification of the problem and recognition of the need to address the problem
2. Discuss goals and strategies
2. Increase writers’ motivation and engagement through involvement in goal setting and strategy development 6. Increase motivation with real life tasks and authentic audiences and collaboration with other writers
1. Orienting phase Self-Determination: Motivational interviewing and setting goals and identifying strategies to address the problem with help of the individual
3. Model writing and EF strategies; scaffold as needed to get steps right
3. Social modelling of the use 2. External control phase of EFs in the context of the Teach and model task writing task performance and strategies 4. Teach strategies for use of EF Scaffold as needed to fine-tune in context of writing strategy 7. Reduce negative impact of Prompt for use factors likely to reduce EF use Structure environment and time 1. Clarify expectations and to increase likelihood of success teach skills
4. Memorize steps in the strategy to ensure internalization
2. Increase writers’ motivation and engagement through involvement in goal setting and strategy development
5. Support writers’ use of strategies; provide feedback and gradually fade support
5. Promote flexible, inventive uses of strategies
6. Opportunities for independent performance
4. Promote flexible, inventive 4. Internal self-regulation uses of strategies and Independent, self-regulated adaptations of strategies to performance new situations with reflection – Use of self-talk for internal on outcome feedback and reflection – Self-monitoring 8. Recognize variability in – Self-reinforcement different settings
6. Increase motivation with real life tasks and authentic audiences and collaboration with other writers
3. Bridging phase – Enhance strategy use through reflective questioning – Practice of learned strategies with feedback about the use of strategies – Model use of strategies for refinement – Teach additional routines that support strategy use – Increase use of internalized control strategies (self- monitoring, self-talk, and self- reflection, self-reinforcement) – Align external demands with internal desires
272 11. Broader Approaches McCloskey, Hewitt, Henzel, & Eusebio, 2008). These reviews examined published studies investigating the effectiveness of interventions that have been used to increase self-regulation of behaviour, cognition, and emotion and improve either EFs, self- monitoring, metacognitive processes, self-control, or adaptive functioning. As illustrated in Table 11.1, there is universal overlap and consistency among the steps of SRSD, the broader set of recommendations offered by Graham, and the phases of the EC intervention continuum. This comparison lends credence to the proposition that the SRSD method could be adapted and used to structure interventions for strengthening EFs while improving other academic skill sets (SRSD for reading and SRSD for math) and these could be combined to provide interventions for various content areas (combined reading and writing SRSD approaches for the study of history, or biology; combined reading, writing, and math SRSD approaches for Chemistry or Physics). These combined SRSD methods could be rigorously tested using research designs similar to those applied in the investigation of SRSD instruction in the area of writing. I believe that these approaches are not only feasible but practical, as I have applied an informal version of such a combined reading and writing SRSD approach in the field of school psychology when working with graduate students who were struggling greatly with the completion of their doctoral dissertations. Beyond the extension of the SRSD approach to other basic skill areas and academic content areas, it seems plausible to posit, as Graham did for the case for writing, the need for the development of broader models that embed instruction for the improvement of EC in the broader context of communities (i.e. a Reader within the context of the Reading Community model or a Mathematician in the context of the Mathematics Community model).
Conclusions In hindsight, it is apparent that Steve Graham and Karen Harris were ahead of their time in the mid-1980s in their thoughts about how to improve student’s writing skills when they chose the psychological construct of self-regulation as inspiration for devising teaching methods in which students used self-directed prompts to cue the use of strategies that they learned in order to accomplish writing tasks. At a time when behaviourists were strongly asserting that human thought is a form of mentalism that is extraneous to learning and behaviour (Skinner, 1984) and many neuropsychologists could not even conceive of the idea that children were capable of independently activating frontal lobe functions (Golden, 1981), Graham and Harris were busy teaching children how to activate those frontal lobe functions to cue and direct the use of mental resources to improve what is arguably one of the most complex of human behaviours—the act of writing (Graham & Harris, 1987, 1989; Harris & Graham, 1985). Thirty-five years later, the publication of this book confirms the fact that the fields of psychology and education have started to catch up with Graham and Harris regarding
Conclusions 273
the significance of mental mechanisms that can be used to set goals, consciously control cognition and emotion, and coordinate the wide array of mental resources needed to successfully execute complex behaviours. As noted by Willoughby and Hudson (Chapter 2) and others (Hughes, 2011; McCloskey & Perkins, 2013), interest in the frontal lobes and the development of associated EFs has grown exponentially over the last 20 years. With this interest has come a plethora of theories and opinions and many scholarly debates about the nature of EFs. It is not surprising that many researchers seek to establish some bounds on definition and operation so that investigations can proceed in a more systematic, orderly manner. Many professionals in various disciplines see the professional literature as converging on a tripartite model of EFs. As Willoughby and Hudson point out however, such convergence is likely to have negative as well as positive consequences. I am of the opinion that the debates about EFs will never be settled to the satisfaction of any of the participants no matter how much effort is invested in rigorous scientific inquiry. The reason isn’t so much the deeply ingrained beliefs we all hold no matter what research findings may indicate, but more so because EFs and all the terms that seem related to this construct such as self-regulation, self-control, self-determination, self-awareness, self-realization, mindfulness, metacognition, intelligence, personality, adaptive functioning, and many more, are fuzzy concepts (Graff, 2000). As such, they will forever elude the boundaries that some researchers attempt to erect around them in hopes of changing them into strictly defined classical concepts. This is not as big a problem as it may seem. From a broader perspective, what matters most is that we identify effective methods that can be used to help children learn to master skills that will serve them well throughout their lives, and realize that such methods can be subjected to rigorous study regardless of the conceptual underpinnings that may have inspired the development of these methods. It is also important to realize that well- reasoned, coherent theories about EFs, whether ultimately correct, partially correct, or completely incorrect, can serve as the source of inspiration for the development of what may prove to be an effective instruction or intervention method just as much as the results of rigorous studies that attempt to validate the nature of psychological constructs. Although members of the various disciplines may never agree on what EFs are and how to measure their involvement in writing, clinicians will continue to find ways to take the constructs at the centre of academic debates and apply them to develop and test instructional methods that show the greatest promise. Over the course of 35 years, Steve Graham and his colleagues have shown us that getting the picture right on definition is secondary to gathering evidence that tests the effectiveness of instruction and intervention methods. Through their efforts to test the viability of the SRSD approach, Graham and colleagues have accumulated the evidence necessary to verify that this method is one of the most effective techniques that can be used to teach writing. These findings do not depend on whether you do, or do not, believe that EFs and self-regulation are completely different constructs. Their research efforts also have taught us that the most successful interventions consider the contexts within which learners function, the specific tasks that must be mastered, the
274 11. Broader Approaches problems that must be solved, and the strategies that can be applied so that learners can achieve the goals they set for themselves. Just as importantly, instruction and intervention do not rely on a single, narrow method repeatedly applied in the same manner in all situations, but rather incorporate multiple methods that tap multiple constructs and that are applied flexibly in various combinations depending on the goal to be achieved, the individual characteristics of the writer, and the contexts of the writer’s community. Future research efforts can build on the very solid foundation that Graham and colleagues have built, expanding on the SRSD techniques to enhance their effectiveness and to explore related avenues of research that can be drawn from Graham’s WWC. Even without a consensus definition of EFs and a host of methodological issues related to attempts to assess them, research using various definitions and various instruments currently available can contribute data than can lead to the development of hypotheses about learner characteristics that can be tested by examining the effectiveness of clinical applications based on these hypotheses. Given the success realized by the use of SRSD methods to teach writing, it is hoped that these methods will be adopted to address other areas of instruction that have proven to be most challenging for teachers and learners alike, including reading comprehension and reasoning with language, and math problem solving and reasoning with quantities.
References Berninger, V.W. (2007). PAL-II: Process Assessment of the Learner: Diagnostic Assessment for Reading and Writing. Administration and Scoring Manual for Reading and Writing. London, UK: Pearson. Delis, D.C., Kaplan, E., & Kramer, J.H. (2001). Delis-Kaplan Executive Function System. London, UK: Pearson. Golden, C.J. (1981). The Luria-Nebraska children’s battery: theory and formulation. In G. Hynd & J. Obrzut (Eds.). Neuropsychological Assessment and the School-Aged Child (pp. 277–302). New York, NY: Grune & Stratton. Graff, D. (2000). Shifting sands: an interest-relative theory of vagueness. Philosophical Topics, 28(1), 45–81. Graham, S. (2018). A revised writer (s)-within-community model of writing. Educational Psychologist, 53(4), 258–79. Graham, S., & Harris, K.R. (1987). Improving composition skills of inefficient learners with self-instructional strategy training. Topics in Language Disorders, 7(4), 66–77. Graham, S., & Harris, K.R. (1989). Improving learning disabled students’ skills at composing essays: self-instructional strategy training. Exceptional Children, 56(3), 201–14. Harris, K.R., & Graham, S. (1985). Improving learning disabled students’ composition skills: self-control strategy training. Learning Disability Quarterly, 8(1), 27–36. Hughes, C. (2011). Changes and challenges in 20 years of research into the development of executive functions. Infant and Child Development, 20(3), 251–71. Jurado, M.B., & Rosselli, M. (2007). The elusive nature of executive functions: a review of our current understanding. Neuropsychology Review, 17(3), 213–33.
References 275 Kaufman, A.S. (2014). Kaufman Test of Educational Achievement (KTEA-3). Bloomington, MN: NCS Pearson. Korkman, M., Kirk, U., & Kemp, S. (2007). NEPSY-II. Bloomington, MN: NCS Pearson. Lama, D., & Ekman, P. (2008). Emotional Awareness: Overcoming the Obstacles to Psychological Balance and Compassion. New York, NY: Macmillan. Lezak, M.D., Howieson, D.B., Loring, D.W., & Fischer, J.S. (2004). Neuropsychological Assessment. Oxford, UK: Oxford University Press. McCloskey, G. (2016). McCloskey Executive Functions Scale (MEFS). Sparta, WI: Schoolhouse Educational Services. McCloskey, G. (2021). McCloskey Executive Functions Scale (MEFS): Parent Form Technical Supplement. Sparta, WI: Schoolhouse Educational Services. McCloskey, G., Allen, S., & Harne, A. (2017). Applying an executive function framework in educational therapy. In M. Ficksman & J.U. Adelizzi (Eds.). The Clinical Practice of Educational Therapy: A Teaching Model (Chapter 9). Abingdon, UK: Routledge Press. McCloskey, G., Gilmartin, C., & Stanco, B. (2014). Interventions for students with executive skills and executive functions difficulties. In J.T. Mascolo, D.P. Flanagan, & V.C. Alfonso (Eds.) Essentials of Planning, Selecting, and Tailoring Interventions for Unique Learners (pp. 314–56). McCloskey, G, Hewitt, J., Henzel, J.N., & Eusebio, E.C. (2008). Executive functions and emotional disturbance. In S.G. Feifer & G. Rattan (Eds.). The Neuropsychology of Emotional Disorders (pp. 65–105). Middletown, MD: The School Neuropsych Press. McCloskey, G., & Perkins, L.A. (2013). Essentials of Executive Functions Assessment (Vol. 68). Hoboken, NJ: John Wiley & Sons. McCloskey, G., Perkins, L.A., & Van Diviner, B. (2009). Assessment and Intervention for Executive Function Difficulties. New York, NY: Taylor & Francis. Miyake, A., & Friedman, N.P. (2012). The nature and organization of individual differences in executive functions: four general conclusions. Current Directions in Psychological Science, 21(1), 8–14. Miyake, A., Friedman, N.P., Emerson, M.J., Witzki, A.H., Howerter, A., & Wager, T.D. (2000). The unity and diversity of executive functions and their contributions to complex ‘frontal lobe’ tasks: a latent variable analysis. Cognitive Psychology, 41(1), 49–100. Newberg, A.B. (2010). Principles of Neurotheology. Farnham, UK: Ashgate Publishing, Peverly, S.T., & Sumowski, J.F. (2012). What variables predict quality of text notes and are text notes related to performance on different types of tests? Applied Cognitive Psychology, 26(1), 104–117. Schrank, F.A., Mather, N., & McGrew, K.S. (2014a). Woodcock-Johnson IV Tests of Oral Language. Rolling Meadows, IL: Riverside. Schrank, F.A., Mather, N., & McGrew, K.S. (2014b). Woodcock-Johnson IV Tests of Achievement. Rolling Meadows, IL: Riverside. Skinner, B.F. (1984). Methods and theories in the experimental analysis of behavior. Behavioral and Brain Sciences, 7(4), 511–23. Stuss, D.T., & Alexander, M.P. (2000). Executive functions and the frontal lobes: a conceptual view. Psychological Research, 63(3–4), 289–298. Stuss, D.T., & Knight, R.T. (2012). Introduction: past and future. In D.T. Stuss & R.T. Knight (Eds.). Principles of Frontal Lobe Function (pp. 1–11). Oxford, UK: Oxford University Press. Stuss, D.T., & Levine, B. (2002). Adult clinical neuropsychology: lessons from studies of the frontal lobes. Annual Review of Psychology, 53(1), 401–33. Wechsler, D. (2014). Wechsler Intelligence Scale for Children (5th Ed.). Bloomington, MN: NCS Pearson. Welsh, M.C., & Pennington, B.F. (1988). Assessing frontal lobe functioning in children: views from developmental psychology. Developmental Neuropsychology, 4, 199–230.
12 Executive Functions Rediscovering Their Roots with the Help of Writing George Georgiou
Introduction Admittedly, the number of studies examining executive functions (EF) has exploded over the last decade. EF is broadly defined as a set of skills that an individual uses for the purpose of achieving a goal (Chan, Shum, Toulopoulou, & Chen, 2008; see also Willoughby & Hudson, in this book, for a presentation of the different definitions of EF). In older children (Lee, Bull, & Ho, 2013) and young adults (Miyake et al., 2000),1 EF has been described as a multicomponent construct comprising of (a) inhibition, the ability to deliberately suppress dominant, automatic or prepotent responses when necessary; (b) shifting of attention (sometimes referred to as cognitive flexibility), the ability to switch attention between tasks, strategies, or mental sets; and (c) updating, the ability to revise and monitor representations in working memory. Despite the acknowledged importance of these three EF components in writing, they have unwillingly overshadowed other components of EF, particularly cognitive planning, which is considered to be the pinnacle of EF (Best, Miller, & Jones, 2009). Thus, in this chapter, I will attempt to bring us back to the origins of EF (the function of the frontal lobes) and describe how cognitive planning can fit into the existing models of writing (perhaps even better than the three popular EF components). Finally, I will describe a writing task that can be used as a measure of cognitive planning.
EF and Academic Achievement Several studies have shown that the three popular EF components (inhibition, shifting, and updating) are related to academic achievement in general (see e.g. Cantin et al., 2016; Lan et al., 2011; Monette, Bigras, & Guay, 2011; Nayfeld, Fuccillo, & Greenfield, 2013; St Clair-Thompson & Gathercole, 2006) and writing in particular (see Altemeier, Abbott, & Berninger, 2008; Balioussis, Johnson, & Pascual-Leone,
1
In young children, EF tasks tend to load on one factor (see Wiebe, Espy, & Charak, 2008).
George Georgiou, Executive Functions In: Executive Functions and Writing. Edited by: Teresa Limpo and Thierry Olive, Oxford University Press. © Oxford University Press 2021. DOI: 10.1093/oso/9780198863564.003.0012
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2012; Hooper et al., in this book). Meta-analytic studies have also reported significant correlations between EF components and academic achievement, albeit relatively modest (e.g. Allan et al., 2014; Follmer, 2018; Ober, Brooks, Homer, & Rindskopf, 2020; Pascual, Muñoz, & Robres, 2019; Yeniad et al., 2013). For example, Ober et al. (2020) recently found that the correlations between the EF components and decoding ranged from 0.28 to 0.34. Follmer (2018) also reported an average correlation of 0.36 between EF and reading comprehension.2 Studies have further shown that deficits in EF may have detrimental effects on individuals’ academic performance (e.g. Lonergan et al., 2019; see also Filipe, in this book) and daily life activities such as the ability to work and attend school, or develop and maintain appropriate social relationships (e.g. Fogel et al., 2020; Grafman et al., 1996; Green, 1996; Vaughan & Giovanello, 2010). However, research on EF presented in this book as well as in recent special issues in refereed journals (see Cirino & Willcutt, 2017; Filipe, Castro, & Limpo, 2020; Mulder & Cragg, 2014) has reminded us of a number of issues associated with EF. First, how EF is defined can sometimes be too broad or too narrow. This is important because depending on the definition adopted, different researchers have used different EF tasks, resulting in different patterns of relations with academic achievement. Second, the dimensionality of EF widely varies. Is it one factor, two factors, or more? If at different ages we have different factors, we cannot describe in detail how each EF component is supposed to affect performance. Third, the operationalization of the EF components also varies considerably (see Chan et al., 2008, for a list of measures to assess EF). Although it is commendable to develop measures of EF, this plethora of measures used to operationalize EF might be partly responsible for the mixed results reported in the literature. It would not be an exaggeration to say that for every significant effect of EF reported in the literature, one can also find a study reporting non- significant effects (even for children of the same nationality, age, and socioeconomic background). Relatedly, in view of the multicomponential nature of EF, it is problematic when researchers use a single measure to operationalize EF (see e.g. Liu et al., 2018) simply because no measure is able to adequately assess all aspects of EF. Fourth, many studies have failed to report the reliability of the EF tasks and those who did have generally reported low reliabilities (particularly test-retest reliability). Finally, the tasks used to assess EF are characterized by task impurity (i.e. there is no ‘pure’ measure that taps executive functions exclusively; see Miyake, Emerson, & Friedman, 2000). This may explain why some researchers have controlled for the effects of other processing skills (e.g. speed of processing, vocabulary, visual skills) before examining the role of EF components in academic performance (e.g. Altani, Protopapas, & Georgiou, 2017; Georgiou & Das, 2018). However, this is not always done and, as a result, we do not know whether it is the ‘executive’ or the ‘non-executive’ demands of the EF tasks that drive the relations with academic performance.
2 I mention the size of these correlations with reading because of the close connection between reading and writing. To my knowledge, no meta-analyses have explored the relation between EF components and writing.
278 12. Rediscovering the Roots of EFs What conclusion can we then draw from an ever-increasing literature on EF that suffers from so many critical issues? What have we really gained by creating a construct ‘for all purposes’ (similar in many ways to that of general intelligence), that is often construed by the results of factor analysis rather than being derived from theory? In what follows, I revisit the origins of EF, specifically cognitive planning, as a means of solving some of the aforementioned issues (however, see also Alvarez & Emory, 2006, for evidence against a one-to-one relationship between EF and frontal lobe activity).
Back to Its Origin: EF as a Function of the Frontal Lobes The origin of the concept to EF is usually attributed to the model of working memory advanced by Baddeley and colleagues (see Baddeley, 1986, 2012; Baddeley & Hitch, 1974). According to Baddeley (1986), EF refers to ‘central executive’ functions that are responsible for the control and regulation of a number of cognitive processes. Some of the functions of central executive include shifting, selective attention, and inhibition. However, researchers following Baddeley regarded EF as a much broader concept that includes the abilities of goal formation, planning, carrying out of goal- directed plans, and effective performance (see e.g. Lezak, 2004; Robbins, 1996; Zelazo, Carter, Reznick, & Frye, 1997). This conceptualization of EF connects it to its second source of origin, namely planning. Planning is defined as ‘any hierarchical process in the organism that can control the order in which a sequence of operations is to be performed’ (Miller, Galanter, & Pribram, 1960, p. 16) and is viewed as an essential component of goal-directed activity that involves the ability to ‘formulate actions in advance and to approach a task in an organized, strategic, and efficient manner’ (Best et al., 2009, p. 188). Initially, Luria (1966) identified planning as one of the three functional units in the brain associated with the functioning of the frontal lobes, especially of the prefrontal cortex. More specifically, Luria (1966, 1973) proposed that the human brain comprises three separate but interrelated brain systems (referred to as functional units). The first unit, Attention-Arousal, is located mainly in the brain stem and is responsible for maintaining general alertness or orientation to the task and for controlling attention. The second unit is responsible for encoding, processing, and storage of information and encompasses the temporal, parietal, and occipital lobes. The third functional unit, Planning, is located in the anterior region of the brain (i.e. the frontal lobes) and is involved in decision making, evaluation, programming, and regulation of present and future behaviour. Damage to the frontal lobes, and in particular the prefrontal cortex, is expected to disrupt complex behavioural programming and a person’s ability to verify or regulate behavioural outcomes. To assess the functioning of the frontal lobes, Luria (1973) developed the Reciprocal Motor Programme test and the Fist-Edge-Palm test. In the Reciprocal
Back to Its Origin: EF as a Function of the Frontal Lobes 279
Motor Programme test, individuals are asked to tap their hands once when they hear a two tapping sound and to tap their hands twice when they hear a one tapping sound. In doing so, they are required to disinhibit their motor action and to react in the opposite way. In the Fist-Edge-Palm test, individuals are asked to place their hands in each of the postures, that is, fist, edge, and palm, in an alternate and success way as quickly as possible. Following Luria, Das and colleagues (e.g. Das, 1980; Das, Kar, & Parrila, 1996; Das, Naglieri, & Kirby, 1994; Naglieri & Das, 1987) conceptualized planning as one of the major cognitive processes in PASS (Planning, Attention, Simultaneous and Successive processing) theory of intelligence and operationalized it in the Cognitive Assessment System (CAS; Naglieri & Das, 1997; see also Naglieri, Das, & Goldstein, 2014, for the second edition of CAS) with three measures (Matching Numbers, Planned Codes, and Planned Connections).3 In Matching Numbers, individuals are presented with four pages comprised of eight rows of numbers that increase in length. For each row, individuals are instructed to underline the two numbers that look alike, as quickly as possible. In Planned Codes, individuals are asked to fill in as quickly as possible, and by using any strategy of choice (e.g. left to right, top to bottom, randomly), empty boxes with a combination of O’s and X’s printed on top of an empty box that each corresponded to a letter (e.g. A = XO, B = XX, C = OX, D = OO). The task contains two pages, each with a distinct set of codes arranged in seven rows and eight columns. A legend located at the top of each page indicates the combination of O’s and X’s that corresponds to each letter. Individuals are given 60 seconds to fill in as many empty boxes as possible. Finally, in Planned Connections (a transparent adaptation of Trail Making), individuals are asked to connect sequential stimuli. In Items 1 and 2, individuals are asked to connect numbers (1 to 25) that are semi-randomly arranged on a page. In Item 3, individuals are asked to connect 25 numbers (1–25) and 25 letters (A–Z) in successive order (1, A, 2, B, 3, C). The subtest score is the total time to complete all three items. Naglieri et al. (2014) have reported high reliability coefficients for each of the planning tasks (0.82 for Matching Numbers, 0.88 for Planned Codes, and 0.80 for Planned Connections) as well as for the planning subscale (0.92). Interestingly, previous studies that used all three measures of Planning in CAS to predict academic achievement (e.g. Best, Miller, & Naglieri, 2011; Naglieri & Rojahn, 2004; see also Georgiou et al., 2020, for evidence from a recent meta-analysis) have reported correlations that are substantially higher than the average correlations found between the popular EF
3 Prior to publishing CAS, Das and colleagues also included Planned Search in the battery of planning tasks (e.g. Das et al., 1994; Leong, Cheng, & Das, 1985; Parrila, Das, & Dash, 1996). Planned Search requires individuals to first identify a target figure (picture, number, or letter) situated inside a box in the middle of a search field, and then find an instance of the target figure in a search field that includes distractor items belonging to the same category as the target (e.g. picture among pictures). To complete the task effectively, an individual needs to keep the target figure in active short-term memory for comparisons, develop an efficient way of scanning each field for the target figure, and control for impulsivity in order to avoid choosing wrong answers.
280 12. Rediscovering the Roots of EFs components and academic achievement in previous meta-analyses (e.g. Follmer, 2018; Ober et al., 2020; Pascual et al., 2019).
The Three Levels of Planning Naturally, one would wonder how the three measures of planning in CAS relate to other known measures of cognitive planning such as the Tower of London (Shallice, 1982), the Wisconsin Card Sorting Test (Heaton et al., 1993), or Crack the Code (Das et al., 1996). Do all these measures assess the same underlying concept? To answer this question, it is important to first review the levels of planning that conceptually divide the tests that have been used to assess planning. According to the Activity Theory (Leontjev, 1978), planning has three levels: activity, action, and operations. At the level of activity, planning can be conceptualized as a method of realizing or aiming towards one’s general life goals and motives such as self-improvement, career development, or planning for a retired life. As an activity, planning is a molar unit of analysis that can be used to explain an individual’s behaviour in general. For example, plans for a life after retirement will provide a framework within which a person’s behaviour can be understood. The function of activity planning is to mediate between a person’s life goals and the external world. To achieve this, activity planning entails components that are not necessarily present in other forms of planning. The components unique to activity planning include selection and shaping of one’s environments so that they support the fulfilment of one’s life goals. Obviously, measuring activity planning is difficult as it often takes a long time to develop life goals. At the level of action, planning is equivalent to problem solving and aims at achieving a particular goal or solving a particular problem. It involves forming a mental representation of the problem, the constraints on planning, and the course of action. Action planning is especially important in tasks where finding the solution requires integration of multiple steps into a coherent process and in tasks that allow more than one way to find the answer. The Tower of London task fits nicely with this description as an individual must convert an initial configuration of balls into a goal configuration by moving the balls among three pegs according to a set of rules (e.g. you can only move one ball at a time). To achieve the goal in the minimum number of moves, an individual must develop a plan which involves generating a sequence of moves, monitoring the effectiveness of this sequence, and revising the sequence as needed. Finally, at the level of operation, planning is equivalent to strategies and tactics, and consists of working towards the solution of a problem in accordance with task- imposed constraints (i.e. meeting environmental conditions). Because the goal or end result is often known, operations planning involves forming a representation of the task and conditions, choosing the possible operations to be applied, and then
Planning and Writing 281
executing these steps. The planning tasks of the CAS fit nicely with this description. For example, in Planned Codes, individuals know that the end goal is to fill in as many empty boxes as possible with a combination of O’s and X’s that corresponds to a given letter. Once they create a representation of the problem, they choose the strategy that will help them achieve their goal and follow the same strategy until they complete the task. Evidence from two recent studies supports the aforementioned classification of planning tasks. More specifically, Das and Georgiou (2016) showed first that the three planning measures in CAS were loading on one factor (representing operations planning) and Crack the Code (CTC)4 on a second factor (representing action planning). Georgiou, Li, and Das (2017) replicated the two-factor structure using Tower of London as a measure of action planning along with CTC. Obviously, classifying the planning tasks according to the aforementioned levels is important and can explain why previous studies have not always reported strong correlations between different planning tasks. If these tasks represent different levels of planning, they should not necessarily correlate strongly with each other (that is the reason they load on different factors in the first place).
Planning and Writing Planning is necessary for good compositions (see Dockrell & Connelly, in this book). In some of his classic studies, Luria used poor composition as an index of deficits in frontal lobe functions. Composing an essay or a narrative requires all the major executive processes (Das, 1980; Das et al., 1996). In fact, evaluation of written compositions after viewing a picture in terms of originality and individuality of the written composition was used as one of the first measures of Planning (Das, 1980). Ashman and Das (1980) also showed that lack of planning in written compositions was related to deficiencies in simple operation planning tasks involving visual search. In what follows, I discuss the role of the three levels of planning (activity, action, and operations) in writing using Biggs’ (1988) model of essay writing as a point of reference.5 Biggs (1988) proposed three stages of writing: intentional, parawriting, and actual writing. The intentional stage includes affective and aspirational aspects that are present prior to writing. After interviewing university students regarding their feelings about an essay assignment, Biggs found two general approaches to essay writing: a deep 4 In CTC (see Das & Misra, 2015, for the items; see also Das & Georgiou, 2016; Papadopoulos, Panayiotou, Spanoudis, & Natsopoulos, 2005; Parrila et al., 1996, for previous research with CTC), individuals are shown two to five lines of information that contain three to five coloured chips that are placed in a particular order. They are also shown a label indicating how many of the coloured chips are in their correct place in each line. An individual’s task is to integrate information from all of the information lines and place their set of coloured chips on the answer line in such an order that all the information lines are true. Individuals are given 3 minutes to finish each item and a discontinuation rule of two consecutive errors is applied. 5 See Graham (in this book) and Kim and Park (2019) for other models of writing.
282 12. Rediscovering the Roots of EFs approach and a surface approach. The deep approach was characterized by a high degree of personal involvement, enjoyment, anticipation of a rich personally rewarding experience, and, frequently, expectation of a high grade. In turn, the surface approach was characterized by apprehension, little personal involvement, and generally, a low expectation about the outcome. Biggs’ (1988) intentional stage of writing nicely captures some of the functions of activity planning. A deep approach to writing, for example, could be seen as stemming from a person’s life goals (e.g. self-improvement). How these life goals are translated into the actual writing task involves activity planning. An example of action planning in writing is solving the particular problems in writing an article, an essay, and so forth; this is roughly equivalent to what Biggs (1988) referred to as parawriting activities. The main objective of this level is to determine the specific goal of the writing task in hand, often in relation to external task demands. Interpreting the question, choosing the audience and style, generating and organizing the content, and setting specific goals and criteria for different parts of the written work are all action planning questions. While action planning is logically different from text generation, it does not take place exclusively prior to text generation. Plans and goals often evolve during writing, as was acknowledged by Biggs. Sometimes we can begin to write out an activity plan with a very sketchy action plan that subsequently becomes more elaborate and inclusive as we proceed, or maybe a new plan emerges that requires a reorganization of both the already produced content as well as our specific goals for the writing. Thus, action planning is a process that continues until the written product is finished and satisfies the writer’s activity planning goals and the specific goals for the current writing task, which by then may be considerably different from the goals that the writer had prior to beginning the task. For Biggs (1988), the actual writing begins with a transcription of focal intention into written form (a feature of operations planning), followed by a review of the writing that is based on the monitoring criteria decided upon during parawriting. If revisions are needed, they can either address any of the parawriting activities or concentrate on the text written so far. According to Biggs, intentions and effects of writing can determine the type of review and revisions in which the writer will engage: students with a deep approach to essay writing tend to review less often and review larger entities, whereas students with a surface approach are more concerned with reviewing individual words and sentences (similar to younger students; see McCutchen, 1995). Revision itself is not a separate process from writing but rather takes the writer back to planning, forming new intentions, monitoring, and so forth (again, features of operations planning).
The Predicament Test All the measures of planning described earlier can be classified as measures of ‘cold’ EF (Grafman & Litvan, 1999) because they do not involve much emotional arousal.6
6
This also applies to all the measures of inhibition, shifting, and updating.
The Predicament Test 283
A natural follow-up question would then be whether there are any measures of planning that contain an affective component and could be used to operationalize ‘hot’ EF. As Das and Misra (2015) concede, had we excluded problems laced with affect, action planning would be missing an important part of reality—moods, emotions, and preconditioned traits (e.g. temperament). To bridge the ‘cold’ and ‘hot’ aspects of EF, Channon (2004) developed the Predicament Test; a simple operationalization of a ‘wholesome’ action planning. In the Predicament Test, participants are first asked to read a short episode and then generate as many solutions as possible to the presented problem. The episode reads like that: ‘You have an apartment; a family that rents the apartment above yours has a dog. The dog is housed in their kitchen at night. Their kitchen is above your bedroom. The dog barks at night. You can’t have a good night’s rest. You complain to the renter. He says that’s the only place they have for the dog as they live in a one-bedroom apartment. What can you do?’ Participants are asked to write as many solutions to the problem as they can within a 2-minute time limit. Next, they are asked to choose one of the solutions that they can justify best and give the reasons for justifying it. Their answer is then given to three judges who rate how appropriate is the solution. The Predicament Test can give us two scores: a fluency score (number of solutions generated) and a socially appropriate judgement score (as rated by the three independent raters). In rating a participant’s answer, judges consider if: (a) all the pertinent facts have been taken into account, (b) the solution is socially appropriate, and (c) the solution is effective from a practical viewpoint. More recently, Das and Misra (2015) provided new scenarios and a twist to each problem by asking participants to consider also the other character’s position. Think of the following scenario: ‘Twenty cadets are placed in a training ship with an officer and his young wife, who is the only woman on the ship. The officer’s quarters are directly above the cadets’ dormitory. Naturally, at night the officer and his wife play music and break into a dance or two, the sound of which can easily be heard in the cadets’ dormitory since there is no soundproofing in the floor. The cadets can’t sleep at night and are usually tired in the morning, especially on the nights when the dance and music go past midnight, which happens quite frequently. What can the cadets do?’ Initially, participants are asked to produce as many solutions as possible to the problem, then choose the best one, and give some reasons for choosing it. Independent raters then judge the solutions first on the criterion of fluency (i.e. how many solutions were generated by the participant that took into account all the important aspects of the problem) and then on the criterion of social appropriateness and practical effectiveness. However, in contrast to Channon (2004), Das and Misra (2015) also asked participants how they would solve the problem if they were the officer with a young spouse. Thus, in the same problem-solving situation participants get to assume the role of both the cadet and the officer. Unfortunately, to my knowledge, no studies have been conducted using Das and Misra’s (2015) scenarios; a very intriguing field of future research.
284 12. Rediscovering the Roots of EFs St Clair-Thompson and Wen (in this book) indicated that neuropsychological measures of EF (as in CAS) do not correlate well with rating scales of EF (e.g. Behavioral Rating Inventory of Executive Function; Gioia, Isquith, Guy, & Kenworthy, 2000) that have been developed to assess an individual’s behaviour in day to day environments (thus also capturing emotions). The Predicament Test may provide a solution combining both ‘hot’ and ‘cold’ aspects of EF.
Conclusion The collection of articles in this book has elucidated different aspects of EF and writing, and reminded us that neither construct is simple. However, the two constructs have a common denominator, namely planning. It is fascinating that a writing task (see Predicament Test) can be used to operationalize planning and represent both ‘cold’ and ‘hot’ EF. In view of arguments that the nature of EF is ‘elusive’ (Jurado & Rosselli, 2007), returning to the origins of EF may offer us both theoretical and practical advantages. From a theoretical point of view, planning is associated with a theory of how the brain works (Luria, 1966) that speaks about specific functions in the brain and how they may relate to dysexecutive syndrome. From a practical point of view, it gives direction to instruction. A few planning intervention studies have already produced positive outcomes (e.g. Iseman & Naglieri, 2011; Mahapatra, Das, Stack-Cutler, & Parrila, 2010). Taken together, this evidence suggests that it may be time to rediscover EF and put theory before factor analysis.
References Allan, N.P., Hume, L.E., Allan, D.M., Farrington, A.L., & Lonigan, C.J. (2014). Relations between inhibitory control and the development of academic skills in preschool and kindergarten: a meta-analysis. Developmental Psychology, 50, 2368–79. Altani, A., Protopapas, A., & Georgiou, G. (2017). The contribution of executive functions in naming words, digits, and objects. Reading and Writing: An Interdisciplinary Journal, 30, 121–41. Altemeier, L.E., Abbott, R.D., & Berninger, V.W. (2008). Executive functions for reading and writing in typical literacy development and dyslexia. Journal of Clinical and Experimental Neuropsychology, 30, 588–606. Alvarez, J., & Emory, E. (2006). Executive function and the frontal lobes: a meta-analytic review. Neuropsychology Review, 16, 17–42. Ashman, A.F., & Das, J.P. (1980). Relation between planning and simultaneous-successive processing. Perceptual and Motor Skills, 51, 371–82. Baddeley, A.D. (1986). Working Memory. New York, NY: Oxford University Press.
References 285 Baddeley, A.D. (2012). Working memory: theories, models, and controversies. Annual Review of Psychology, 63, 1–29. Baddeley, A.D., & Hitch, G. (1974). Working memory. In G.H. Bower (Ed.). The Psychology of Learning and Motivation: Advances in Research and Theory (pp. 47–89). New York, NY: Academic Press. Balioussis, C., Johnson, J., & Pascual-Leone, J. (2012). Fluency and complexity in children’s writing: the role of mental attention and executive function. Rivista di Psicolinguistica Applicata/Journal of Applied Psycholinguistics: Special Issue, XII, 3, 33–45. Best, J.R., Miller, P.H., & Jones, L.L. (2009). Executive functions after age 5: changes and correlates. Developmental Review, 29, 180–200. Best, J.R., Miller, P.H., & Naglieri, J.A. (2011). Relations between executive function and academic achievement from ages 5 to 17 in a large, representative national sample. Learning and Individual Differences, 21, 327–36. Biggs, J. (1988). Approaches to learning ant to essay writing. In R. Schmeck (Ed.). Learning Strategies and Learning Styles (pp. 185–228). New York, NY: Plenum Press. Cantin, R.H., Gnaedinger, E.K., Gallaway, K.C., Hesson-McInnis, M.S., & Hund, A.M. (2016). Executive functioning predicts reading, mathematics, and theory of mind during the elementary years. Journal of Experimental Child Psychology, 146, 66–78. Chan, R.C.-K., Shum, D., Toulopoulou, T., & Chen, E.Y.-H. (2008). Assessment of executive functions: review of instruments and identification of critical issues. Archives of Clinical Neuropsychology, 23, 201–16. Channon, S. (2004). Frontal lobe dysfunction and everyday problem-solving: social and non- social contributions. Acta Psychologica, 115, 235–54. Cirino, P.T., & Willcutt, E.G. (2017). An introduction to the special issue: contributions of executive function to academic skills. Journal of Learning Disabilities, 50, 355–8. Das, J.P. (1980). Planning: theoretical considerations and empirical evidence. Psychological Research (W. Germany), 41, 141–51. Das, J.P., & Georgiou, G. (2016). Levels of planning predict different reading comprehension outcomes. Learning and Individual Differences, 48, 24–8. Das, J.P., Kar, B.C., & Parrila, R.K. (1996). Cognitive Planning: The Psychological Basis of Intelligent Behavior. New Delhi, India: Sage. Das, J.P., Naglieri, J.A., & Kirby, J.R. (1994). The PASS Theory of Intelligence. Boston, MA: Allyn & Bacon. Das, J.P., & Misra, S.B. (2015). Cognitive Planning and Executive Functions: Applications for Education and Management. New Delhi, India: SAGE. Filipe, M., Castro, S.L., & Limpo, T. (2020). The link between executive functions and literacy: introduction. Reading and Writing: An Interdisciplinary Journal, 33, 807–12. Fogel, Y., Rosenblum, S., Hirsh, R., Chevignard, M., & Josman, N. (2020). Daily performance of adolescents with executive function deficits: an empirical study using a complex-cooking task. Occupational Therapy International. Available at: https://doi.org/10.1155/2020/ 3051809 Follmer, D.J. (2018). Executive function and reading comprehension: a meta-analytic review. Educational Psychologist, 53, 42–60. Georgiou, G., & Das, J.P. (2016). What component of executive functions contributes to normal and impaired reading comprehension in young adults? Research in Developmental Disabilities, 49–50, 118–28. Georgiou, G., & Das, J.P. (2018). Direct and indirect effects of executive function on reading comprehension in young adults. Journal of Research in Reading, 41, 243–58. Georgiou, G., Guo, K., Naveenkumar, N., Vieira, A.P.A., & Das, J.P. (2020). PASS theory of intelligence and academic achievement: a meta-analytic review. Intelligence, 79, 101431.
286 12. Rediscovering the Roots of EFs Georgiou, G., Li, J., & Das, J.P. (2017). Tower of London: what level of planning does it measure? Psychological Studies, 62, 261–7. Gioia, G.A., Isquith, P.K., Guy, S.C., & Kenworthy, L. (2000). Behavior rating inventory of executive function. Child Neuropsychology, 6, 235–8. Grafman, J., & Litvan, I. (1999). Importance of deficits in executive functions. The Lancet, 354, 1921–23. Grafman, J., Schwab, K., Warden, D., Pridgen, A., Grown, H.R., & Salazar, A.M. (1996). Frontal lobe injuries, violence, and aggression: a report of the Vietnam Head Injury Study. Neurology, 46, 1231–8. Green, M.F. (1996). What are the functional consequences of neurocognitive deficits in schizophrenia? American Journal of Psychiatry, 153, 321–30. Heaton, R.K., Chelune, G.J., Talley, J.L., Kay, G.C., & Curtiss, G. (1993). Wisconsin Card Sorting Test Manual Revised and Expanded. Odessa, FL: Psychological Assessment Resources. Iseman, J., & Naglieri, J.A. (2011). A cognitive strategy instruction to improve math calculation for children with ADHD: a randomized controlled study. Journal of Learning Disabilities, 44, 184–95. Jurado, M.B., & Rosselli, M. (2007). The elusive nature of executive functions: a review of our current understanding. Neuropsychological Review, 17, 213–33. Kim, Y.-S.G., & Park, S. (2019). Unpacking pathways using the Direct and Indirect Effects Model of Writing (DIEW) and the contributions of higher order cognitive skills to writing. Reading and Writing: An Interdisciplinary Journal, 32, 1319–43. Lan, X., Legare, C.H., Ponitz, C.C., Li, S., & Morrison, F.J. (2011). Investigating the links between the subcomponents of executive function and academic achievement: a cross-cultural analysis of Chinese and American preschoolers. Journal of Experimental Child Psychology, 108, 677–92. Lee, K., Bull, R., & Ho, R.M.H. (2013). Developmental changes in executive functioning. Child Development, 84, 1933–53. Leong, C.K., Cheng, S.C., & Das, J.P. (1985). Simultaneous-successive synthesis and planning in Chinese readers. International Journal of Psychology, 20, 19–31. Leontjev, A.N. (1978). Activity, Consciousness, and Personality. Englewood Cliff, NJ: Prentice-Hall. Lezak, M.D. (2004). Neuropsychological Assessment. New York, NY: Oxford University Press. Liu, Y., Sun, H., Lin, D., Li, H., Yeung, S.S.S., & Wong, T.T.Y. (2018). The unique role of executive function skills in predicting Hong Kong kindergarteners’ reading comprehension. British Journal of Educational Psychology, 88(4), 628–44. Lonergan, A., Doyle, C., Cassidy, C., Mahon, S.M., Roche, R.A.P., Boran, L., & Bramham, J. (2019). A meta-analysis of executive functioning in dyslexia with consideration of the impact of comorbid ADHD. Journal of Cognitive Psychology, 31, 725–49. Luria, A.R. (1966). Human Brain and Psychological Processes. New York, NY: Harper and Row. Luria, A.R. (1973). The Working Brain. New York, NY: Basic Books. Mahapatra, S., Das, J.P., Stack-Cutler, H., & Parrila, R. (2010). Remediating reading comprehension difficulties: a cognitive processing approach. Reading Psychology, 31, 428–53. McCutchen, D. (1995). Cognitive processes in children’s writing: developmental and individual differences. Issues in Education, 1, 123–60. Miller, G.A., Galanter, E., & Pribram, K.H. (1960). Plans and the Structure of Behavior. New York, NY: Holt, Rinehart & Winston. Miyake, A., Emerson, M.J., & Friedman, N.P. (2000). Assessment of executive functions in clinical settings: problems and recommendations. Seminars in Speech and Language, 21, 169–83.
References 287 Miyake, A., Friedman, N.P., Emerson, M.J., Witzki, A.H., Howerter, A., & Wager, T.D. (2000). The unity and diversity of executive functions and their contributions to complex ‘frontal lobe’ tasks: a latent variable analysis. Cognitive Psychology, 41, 49–100. Monette, S., Bigras, M., & Guay, M.C. (2011). The role of the executive functions in school achievement at the end of grade 1. Journal of Experimental Child Psychology, 109, 158–73. Mulder, H., & Cragg, L. (2014). Executive functions and academic achievement: current research and future directions. Infant and Child Development, 23, 1–3. Naglieri, J.A., & Das, J.P. (1987). Construct and criterion-related validity of planning, simultaneous, and successive cognitive processing tasks. Journal of Psychoeducational Assessment, 4, 353–63. Naglieri, J.A., & Das, J.P. (1997). Das-Naglieri Cognitive Assessment System. Itasca, IL: Riverside Publishing. Naglieri, J.A., Das, J.P., & Goldstein, S. (2014). Cognitive Assessment System (2nd Ed.). Austin, TX: Pro-Ed. Naglieri, J.A., & Rojahn, J. (2004). Construct validity of the PASS theory and CAS: correlations with achievement. Journal of Educational Psychology, 96, 174–81. Nayfeld, I., Fuccillo, J., & Greenfield, D.B. (2013). Executive functions in early learning: extending the relationship between executive functions and school readiness to science. Learning and Individual Differences, 26, 81–8. Ober, T.M., Brooks, P.J., Homer, B.D., & Rindskopf, D. (2020). Executive functions and decoding in children and adolescents: a meta-analytic investigation. Educational Psychology Review, 32(3), 735–63. Papadopoulos, T.C., Panayiotou, G., Spanoudis, G., & Natsopoulos, D. (2005). Evidence of poor planning in children with attention deficits. Journal of Abnormal Child Psychology, 33, 611–23. Parrila, R., Das, J.P., & Dash, U.N. (1996). Development of planning and its relation to other cognitive processes. Journal of Applied Developmental Psychology, 17, 597–624. Pascual, A.C., Muñoz, N.M., & Robres, A.Q. (2019). The relationship between executive functions and academic performance in primary education: review and meta-Analysis. Frontiers in Psychology, 10, 1582. Robbins, T.W. (1996). Dissociating executive functions of the prefrontal cortex. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 351, 1463–70. Shallice, T. (1982). Specific impairments of planning. Philosophical Transactions of the Royal Society of London, B, 298, 199–209. St Clair-Thompson, H.L., & Gathercole, S.E. (2006). Executive functions and achievements in school: shifting, updating, inhibition, and working memory. The Quarterly Journal of Experimental Psychology, 59, 745–59. Vaughan, L., & Giovanello, K. (2010). Executive function in daily life: age-related influences of executive processes on instrumental activities of daily living. Psychology and Aging, 25, 343–55. Wiebe, S.A., Espy, K.A., & Charak, D. (2008). Using confirmatory factor analysis to understand executive control in preschool children: a latent structure. Developmental Psychology, 44, 575–87. Yeniad, N., Malda, M., Mesman, J., van IJzendoorn, M.H., & Pieper, S. (2013). Shifting ability predicts math and reading performance in children: a metanalytical study. Learning and Individual Differences, 23, 1–9. Zelazo, P.D., Carter, A., Reznick, J.S., & Frye, D. (1997). Early development of executive function: a problem-solving framework. Review of General Psychology, 1, 198–226.
13 The Future Role of Executive Functions in Education From Acquisition to Knowledge and Effective Application Sam Goldstein and Keith D. McGoldrick
Introduction What will schools throughout the world be like 30 years from now? What knowledge, skills, attitudes, values, and behaviours will future students need to master in order to thrive in diverse educational environments and transition successfully into adult life and vocation? Even more importantly, how will we get from today to tomorrow? How will instructional systems develop the means of teaching students and challenging their abilities? How will educational institutions be organized in primary, secondary, college, and graduate schools? As a worldwide collection of societies and cultures, we face unprecedented social, economic, and environmental challenges. This myriad of challenges are driven by accelerating globalization, and a near light-speed rate of technological development. While these phenomena provide the opportunity to build a strong foundation to guide our journey into the future, the future remains uncertain. Our educational system will need to prepare students for vocations that have yet to be created, science that has yet to be discovered, and technology that has yet to be invented. It has been the case over the past 200 years that the responsibility for this important preparation has fallen increasingly upon our educational systems. This is a trend that will continue. Further we believe schools and educational systems over the coming thirty years will be turned inside out. Teachers will shift from fonts of knowledge transforming into instructional and motivational coaches creating environments in which students develop ability and acquire knowledge through a variety of hands on and interactive activities. This book is about the application of executive function (EF) to writing. This volume demonstrates the rapid growth of our understanding and appreciation of the role behaviours related to EF serve in helping students succeed in their acquisition and effective application of knowledge. As a topic grows, so too does interest increase the number of guides, volumes, and research science about it. Topics such as executive Sam Goldstein and Keith D. McGoldrick, The Future Role of Executive Functions in Education In: Executive Functions and Writing. Edited by: Teresa Limpo and Thierry Olive, Oxford University Press. © Oxford University Press 2021. DOI: 10.1093/oso/9780198863564.003.0013
Introduction 289
functioning typically begin with a broad textbook such as the one the first author co- authored (Naglieri & Goldstein, 2013). As a topic expands, texts and research dealing with specific aspects such as writing, reading, and mathematics align the interest of scientists and educators. Our research and that of others has very clearly demonstrated that EF or the strategies used for effective learning and performance comprise up to 25% of the variance in successful outcomes. It is with good reason that educators have an increased appreciation that students need not just to acquire knowledge but to acquire an understanding and appreciation of how to efficiently and effectively apply their knowledge to solve problems. To navigate successfully in future educational settings, students will need to develop efficient EF. They will need to master self-regulation, initiation, planning, organization, emotional regulation, and resilience or the ability to function adequately even in the face of adversity. Students of the future will need to respect and appreciate the ideas, perspectives, and the values of others. They will need to work cooperatively and learn to effectively share their knowledge and ideas. Even more important, students will need to become increasingly responsible for their education. The term sometimes used to refer to this process is agency (Shogren, Wehmeyer, & Palmer, 2017). Agency requires the ability to frame a guiding purpose and identify actions to achieve a goal. Future students will need to apply their knowledge in unknown and evolving circumstances. They need not just to think well but to think about their thinking (metacognition) and acquire the capacity for critical thinking, creativity, learning how to learn, and regulate behaviour. They will need to be competent in applying empathy, self-efficacy, and the ability to collaborate with others. More important, they will need to be able to use this knowledge and their abilities to create a safe, secure, and better world. Executive functioning includes a group of cognitive processes, such as planning, working memory, attention, inhibition, self-monitoring, self-regulation, and initiation carried out by pre-frontal areas of the frontal lobes. Recent functional neuroimaging studies have supported the theory of the pre-frontal cortex as responsible for EF, demonstrating that two parts of the pre-frontal cortex, the ACC, and DLPFC appear to be particularly important for completing tasks thought to be sensitive to EF. In the 1950s, psychologists and neuroscientists became interested in understanding the role of the pre-frontal cortex in guiding intelligent behaviour. British psychologist Donald Broadbent (1958) described differences between automatic and controlled processes. In 1975, psychologist Michael Posner coined the term ‘cognitive control’ in a book chapter titled ‘Attention and Cognitive Control’ (Posner & Snyder, 1975). Posner proposed that there is a separate executive branch of the attentional system responsible for focusing attention on selected aspects of the environment. Alan Baddeley proposed a similar system as part of his model of working memory, arguing there must be a component which he referred to as the ‘central executive’ allowing information to be manipulated in short term memory. Shallice (1988) also suggested that attention is regulated by a ‘supervisory system which can over-ride automatic responses in
290 13. Future Role of EFs in Education favour of scheduling behaviour on the basis of plans or intentions’. Consensus slowly emerged that this control system is housed in the most anterior portion of the brain, the prefrontal cortex. Pribram (1973) was one of the first to use the term ‘executive’ when discussing matters of pre-frontal cortex functioning. Since then at least 30 or more constructs have been included under the umbrella term, EF, making the concept hard to operationally define. Many authors have made attempts to define the concept of EF using models that range from one to multiple components. Lezak (1995) suggested that EFs consisted of components related to volition, planning, purposeful action, and effective performance. It has been hypothesized that each component involves a distinct set of related behaviours. Reynolds and Horton (2006) suggested that EFs are distinct from general knowledge. They suggest that EFs represent the capacity to plan, to do things, and perform adaptive actions, while general knowledge related to the retention of an organized set of objective facts. They further hypothesized that EF involves decision- making, planning actions, and generating novel motor outputs adapted to external demands rather than the passive retention of information. Goldstein and Naglieri (2013) based their view of the behavioural aspects of EF on a large national study of children. They suggested that EF is best represented as a single phenomenon, conceptualized as the efficiency with which individuals go about acquiring knowledge as well as how well problems can be solved across nine behaviours (attention, emotion regulation, flexibility, inhibitory control, initiation, organization, planning, self- monitoring, and working memory). An important foundation for understanding the development of EF can be found in the works of A.R. Luria (1963, 1966, 1993). Luria’s neurodevelopmental model postulated specific developmental stages related to stages of higher cortical maturation. Luria suggested that the various stages of mental development encountered as children mature provide a unique opportunity to study how EFs develop. Luria (1966) postulated a number of stages by which neuropsychological functions critical for intelligence and EF are developed. These stages were thought to interact with environmental stimuli based on Vygotsky’s cultural and historical theory (Van der Veer & Valsiner, 1994). Vygotsky developed a complex theory related to language and thought processes. He postulated that environmental and/or cultural influences were important in understanding the development of neurological structures responsible for higher level mental abilities, such as abstraction, memory, and attention. Luria expanded Vygotsky’s original theories (Vygotsky, 1997a, 1997b, 1997c, 1997d). In 1966, Luria postulated that higher cortical functions involving EF required interaction of normal neurological development and specific environmental stimuli of a cultural, historical, and social nature of develop. In this way, Luria’s thoughts are very consistent with current theory suggesting that particular phenotypes are shaped by environmental experience, leading to multifinality or multiple endophenotypes. Thus, the result of the optimal interaction of neurological development and environmental stimuli would result in more efficient cortical functioning related to abilities such as language, attention, memory, intelligence, and EF.
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In school, students are being required at younger ages to plan and complete long- term projects, develop and write lengthy writing assignments, and quickly and efficiently use advanced technology. EF is a critical tool in being able to plan, organize, and self-correct as well as synthesize a vast array of information on such projects. Unfortunately, although students are required to complete such tasks, they are not always provided the EF strategies and tools needed to do so. As such it is important for educators and parents to provide students such strategies to help them develop EF behaviours which then propels them to greater success from elementary school through college and into their working career. In elementary school, basic EF assists in maintaining attention to learn material as well as hold this information within one’s mind, and subsequently place it in long- term memory. Fuhs et al. (2014) found that growth in EF and general academic skills were interrelated in pre-kindergarten. In addition, EF in prekindergarten gains were also a predicter of further academic gains in kindergarten which was consistent with Stipek, Newton, and Chudgar (2010). Furthermore, Fuhs et al. (2014) found that EF behaviours enable children to adapt to classroom demands and learn new task demands. This is important as students are then required to synthesize new information with what they have already learned to complete increasingly more complex tasks. Development of EF strategies at a young age coupled with the regular addition of new and more advanced strategies can assist students to learn and remember more efficiently from a young age. In addition, learning executive functioning strategies will assist students in developing the needed skill sets to take complicated projects and break them down into smaller steps, and then develop a planning strategy as well as self-correct as needed. Executive functioning also plays an important role in the transition from elementary to middle school. The entry to middle school places new challenges and demands on students with increased workload, managing multiple classes, and changes in peer interactions, all which placed greater demands on executive functioning. Students are also required to efficiently problem solve as well as demonstrate increased self- control within the classroom and with peers. Higher levels of EF have been associated with greater academic competence and outcomes as well as better behavioural functioning within a classroom environment (Jacobson, Williford, & Pianta, 2011). Students entering high school require similar EF levels, but to a higher degree due to the increasing demands, such as increased workload, managing multiple classes, and assignments, as well as managing the emotional and social demands that occur within school and outside of school. Those who have difficulty writing are typically at a disadvantage in school, and later in their working career, as writing is used share knowledge and convey ideas. Importantly, writing is the means for students to express and demonstrate their knowledge. As they enter college and the workforce, writing is required to effectively communicate one’s thoughts and requests of others. This is increasingly important as more work is being conducted via computer/email. Previously one often spoke via telephone or in person, which helped ensure their requests were understood, such as
292 13. Future Role of EFs in Education through facial expressions and clarification questions. However, the increasing reliance on written communication requires one to be more concise and exact in their statements and requests. As such, there is increasing demand to ensure that students are learning how to effectively communicate via written language. Prior to writing a student is required to learn the basics of reading, which in addition to language, requires multiple facets of executive functioning. Reading comprehension requires a significant amount of sustained attention, particularly when content is difficult. Cirino et al. (2018) also found behavioural and cognitive control affects early reading development as well as reading improvement over time. This relates to Connor’s et al. (2016) finding that reading comprehension additionally requires self-regulatory skills. Furthermore, word decoding, vocabulary, and comprehension were found to have moderate relations with working memory (Peng et al., 2018). Once the basics of reading are mastered, a student can begin on the journey of becoming proficient writers. There are also several EF components utilized within writing. In the manual/ physical process of writing alone, a student is required to have motor planning, orthographic, and orthographic-motor integration which are processed via the orthographic loop of working memory and processing speed (Berninger et al., 2008). Deficits in the basic physical writing process can affect higher order writing. For example, when additional attention is required to focus on writing neatly and spelling correctly, additional cognitive load is placed on a student at the expense of other EFs. Skilled writing requires strategies for planning, drafting, and revising text. This is reliant on analysis of information, decision-making, planning, execution, and integration of information as well as attention to detail for revision. A basic tenant of this is having a mental representation of the assignment or understanding what is being asked. Next a student needs to decide on and develop an approach in order to plan what they are going to write. The student then needs to have attentional control and strong working memory in order to focus and execute tasks developed within the planning stage and simultaneously integrate information within their writing. Following this the student must revise their work and self-correct as needed, which requires attention to detail and cognitive flexibility. As there has been more research and understanding the importance of EF in learning, there has subsequently been increasingly number of strategies to assist with development of EF for students. A review of these specific techniques is beyond the scope of this chapter. Through the continual process of employing these strategies and helping children learn to attend to information, develop problem-solving, critically evaluate, and integrate information, and express themselves students become better learners. Learning how to learn is critical, especially as a student progresses to higher grades are, they required to use executive functioning to develop plans on how to research, synthesize, and demonstrate their work. Once they have learned how to learn, students can then demonstrate their knowledge through oral and written communication. Additionally, children who were able to learn academic content quickly are more likely to participate and develop higher executive functioning
References 293
skills. Through assisting students early on to developing these abilities and then to help them continuingly enhance and further develop these abilities as they progress through school, students are then better set up for greater success throughout the rest of their life. Three decades of US student achievement in reading and writing has studied 3.9 million students through the National Assessment of Education Progress Program (Reilly, Neumann, & Andrews, 2019). These authors examined a number of phenomena, including gender differences. Differences found for reading were small to medium (d = – 0.32 by grade 12), but they were medium-sized for writing (d = –0.55 by grade 12). These were stable historically over time. They were pronounced in balances in gender ratios at the lower left and upper right tails of the ability spectrum. Although some have argued that most psychological gender differences are only small to trivial in size (Hyde, 2005), it appears that language and verbal abilities represent one exception to the general rule of gender similarities. Girls outperform boys in mean reading and written achievement. Further, these gender differences do not appear to be declining over time.
Conclusion Over the past 200 years, significant and critical advancements have been made in our understanding of the manner in which the brain regulates, manages, organizes, and helps organisms interface with their environment; particularly to acquire and manage knowledge as well as problem solve effectively. It is well-documented that to function effectively, the brain requires an executive system. We are increasingly aware of the influence of this system and its importance as the knowledge of the world is literally at our fingertips. This EF system is needed to control and manage our abilities, knowledge, and capacity to problem solve. We now know the pre-frontal areas of the frontal lobes primarily carry out these operations. These parts of the brain are recently evolved. It is not surprising that human beings possess a complex EF system. Educational institutions of the future will increasingly focus upon the development of EF in educating and guiding students. The next thirty years will be an exciting time in science and education, as what we learn through organized research finds its way efficiently and quickly into applied educational practice. Today’s children entering school in 2020 will be young adults by 2050. Building a foundation to develop an effective, future educational system is our responsibility today. It is a responsibility that we as scientist practitioners relish and are excited to be part of.
References Berninger, V.W., Nielsen, K.H., Abbott, R.D., Wijsman, E., & Raskind, W. (2008). Writing problems in developmental dyslexia: under-recognized and under-treated. Journal of School Psychology, 46(1), 1–21.
294 13. Future Role of EFs in Education Broadbent, D.E. (1958). Perception and Communication. London: Pergamon. Cirino, P.T., Miciak, J., Ahmed, Y., Barnes, M.A., Taylor, W.P., & Gerst, E.H. (2018). Executive function: association with multiple reading skills. Reading and Writing, 32(7), 1819–46. Connor, C.M., Day, S.L., Phillips, B., Sparapani, N., Ingebrand, S.W., McLean, L., . . . & Kaschak, M.P. (2016). Reciprocal effects of self-regulation, semantic knowledge, and reading comprehension in early elementary school. Child Development, 87(6), 1813–24. Fuhs, M.W., Nesbitt, K.T., Farran, D.C., & Dong, N. (2014). Longitudinal associations between executive functioning and academic skills across content areas. Developmental Psychology, 50(6), 1698–709. Goldstein, S., & Naglieri, J.A. (2013). Handbook of Executive Functioning. New York, NY: Springer. Hyde, J.S. (2005). The gender similarities hypothesis. American Psychologist, 60, 581–92. Jacobson, L.A., Williford, A.P., & Pianta, R.C. (2011). The role of executive function in children’s competent adjustment to middle school. Child Neuropsychology, 17(3), 255–80. Lezak, M.D. (1995). Neuropsychological Assessment (3rd ed.). Oxford, UK: Oxford University Press. Luria, A.R. (1963). Restoration of Function after Brain Injury. New York, NY: Pergamon Press. Luria, A.R. (1966). Higher Cortical Functions in Man. New York, NY: Basic. Luria, A.R. (1993). The Working Brain. New York, NY: Basic. Naglieri, J.A., & Goldstein, S. (2013). Comprehensive Executive Functioning Index. Toronto, ON: Multi-Health Systems. Peng, P., Barnes, M., Wang, C., Wang, W., Li, S., Swanson, H.L., . . . & Tao, S. (2018). A meta- analysis on the relation between reading and working memory. Psychological Bulletin, 144(1), 48–76. Posner, M., & Snyder, C.R.R. (1975). Attention and cognitive control. In R.L. Solso (Ed.). Information Processing and Cognition (pp. 55–85). Hillsdale, NJ: Erlbaum. Pribram, K.H. (1973). The primate frontal cortex—executive of the brain. In K.H. Pribram & A.R. Luria (Eds.). Psychophysiology of the Frontal Lobes (pp. 293–314). New York, NY: Academic. Reilly, D., Neumann, D.L., & Andrews, G. (2019). Gender differences in reading and writing achievement: evidence from the National Assessment of Educational Progress (NAEP). American Psychologist, 74(4), 445–58. Reynolds, C.R., & Horton, A.M., Jr. (2006). Test of Verbal Conceptualization and Fluency: Examiner’s Manual. Austin, TX: PRO-ED. Shallice, T. (1988). From Neuropsychology to Mental Structure. Cambridge, UK: Cambridge University Press. Shogren, K.A., Wehmeyer, M.L., & Palmer, S.B. (2017). Casual agency theory. In M.L. Wehmeyer, K.A. Shogren, T.D. Little, & S.J. Lopez (Eds.). Handbook on the Development of Self-determination (pp. 55–70). New York, NY: Springer. Stipek, D., Newton, S., & Chudgar, A. (2010). Learning-related behaviors and literacy achievement in elementary school-aged children. Early Childhood Research Quarterly, 25(3), 385–95. Van der Veer, R., & Valsiner, J. (1994). The Vygotsky Reader. Cambridge, UK: Blackwell. Vygotsky, L.S. (1997a). Consciousness as a problem for the psychology of behavior. (Orig. 1925). In R.W. Rieber & J. Wollock (Eds.). The Collected Works of L.S. Vygotsky, Volume 3: Problems of the Theory and History of Psychology (pp. 63–79). New York, NY: Plenum Press. Vygotsky, L.S. (1997b). The historical meaning of the crisis in psychology: a methodological investigation (orig. 1927). In R.W. Rieber & J. Wollock (Eds.). The Collected Works of L.S. Vygotsky, Volume 3: Problems of the Theory and History of Psychology (pp. 233–343). New York, NY: Plenum Press.
References 295 Vygotsky, L.S. (1997c). The history of the development of higher mental functions (M.J. Hall, trans) (orig. 1931). In R.W. Rieber & J. Wollock (Eds.). The Collected Works of L.S. Vygotsky, Volume 4: The History of the Development of Higher Mental Functions (pp. 1–251). New York, NY: Plenum Press. Vygotsky, L.S. (1997d). The instrumental method in psychology (R. Van der Veer, trans.) (orig. 1930). In R.W. Rieber & J. Wollock (Eds.). The Collected Works of L.S. Vygotsky, Volume 3: Problems of the Theory and History of Psychology (pp. 85–90). New York, NY: Plenum Press.
Index For the benefit of digital users, indexed terms that span two pages (e.g., 52–53) may, on occasion, appear on only one of those pages. Tables and boxes are indicated by t and b following the page number Abbott, R.D. 144–45, 146–47 academic achievement 276–78, 279–80 Activity Theory 280 ageing writers 227–53 cognitive changes 229–35 dementia 240–47 discourse level characteristics 233–34 executive functions 236–43 explanatory models 239–43 general slowing model 236–37 handwriting 234–35, 236–37 inhibition 238–39 interventions for healthy ageing 244–47 language changes 230 lexical level 231–32 mild cognitive impairment 240, 241, 242 spelling 231–32, 236–37 syntactic complexity 232–33 typing 236 working memory 237–38 writer(s)-within-community model 239–40 agency 39–40, 50, 52–54, 58, 60–61, 289 AIMS strategy 196 Altemeier, L.E. 144–45, 146–47 Alves, R.A. 113, 148–49, 192–93 Alzheimer’s disease 240, 241, 242 Anderson, P. 23 Arnsten, A. 29 Asaro-Saddler, K. 197 attention 23, 27–28, 29, 53, 56, 142–43, 212, 289–90 attention deficit/hyperactivity disorder (ADHD) 85–86, 144–45, 161–62, 165–71 autism spectrum disorder 85–86, 161–63, 170 autobiographical writing 245–46 automated writing assessment 118–19 automatization of writing 208, 211–12, 219–20 backward digit span task 83–84, 86–89, 87t Balioussis, C. 146–47 Barkley, R.A. 23–24 Barkley Deficits in Executive Function Scale (BDEFS) 93–94 Children and Adolescents (BDEFS-CA) 93–94
Behavior Rating Inventory of Executive Function (BRIEF) 20, 91–92, 93, 94, 95–96 Berninger, V.W. 143, 144–45, 146–47 bifactor models 24–25 Biggs, J. 281–82 Biname, F. 148 Blair, C. 29 Block recall task 83–84 Bouck, E.C. 197 Burgess, P.W. 21–22 Byrd, M. 233 calligraphy training 246 Campbell, R. 245–46 cascading production analysis (CPA) 264–69 central executive 22, 210, 237, 278 central tendency bias 93 Chan, S.C.C. 247 Channon, S. 282–83 Chevalier, N. 27 Childhood Executive Functioning Inventory (CHEXI) 20, 91–92 Christie, Agatha 243–44 Cognitive Assessment System (CAS) 279–80, 281 Cognitive Complexity and Control (CCC) theory 141 cognitive effort 208, 213–19 cognitive flexibility 25–26, 145–47, 161, 222 ADHD 165 autism spectrum disorder 163 deficit-linked writing problems 164t dyslexia 167–68 cognitive interventions, healthy ageing 245 collective history 46 communication 115 complex span task 83–84, 86–89 Comprehensive Executive Function Inventory (CEFI) 91–92 computer-based graphic organizers 198 concept mapping programs 197 conceptualization 50 context executive control 39–41, 66–67 writing community 46
298 Index COPS strategy 190 Corsi Blocks task 83–84 Costa, L.-J.C. 152–53 critical reading 216–18 curriculum-based measures of writing 116–18 DARE strategy 194–96 Das, J.P. 279, 283 Datchuk, S.M. 184–85 day–night task 82, 86–89, 87t Decker, S.L. 147 Delis-Kaplan Executive Function System Color-Word Interference Subtest (D-KEFS) 264–66 Delis Rating of Executive Function (D-REF) 91–92 dementia, writing markers 240–47 development associations and dissociations between executive functions and writing 151–53 executive functions 24, 26–28, 142–43, 152–53 reading 292 writing communities 60, 64–65 diary writing 233 digit span task 83–84 dimensional change card sort 83, 87t direct and indirect effects model of writing development (DIEW) 119–20 discourse level, age-related changes 233–34 Down’s syndrome 85–86 dyscalculia 166–67 dysgraphia 166–67, 168 dyslexia 85–86, 166–68 economic strain 18–19 editing 217–18, 236 educational settings 288–95 Elford, H. 245–46 emotions 29, 57, 141 environmental-based interventions 169 Eriksen flanker task 81, 86–89, 87t error detection 217 error monitoring 29–30 evaluation phase 55 Evmenova, A.S. 198 Executive Control Intervention Continuum 270– 72, 271t executive functions 3, 4–5, 210–11 academic achievement 276–78, 279–80 ADHD 161–62, 165–71 age-related changes in writing 236–43 assessment measures 19–22, 79–102, 262–69 associations and dissociations with writing 149–53 autism spectrum disorder 161–63 cognition 4, 17–18, 38–39
cognitive (performance-based) measures 19– 21, 80–91, 94–95 conceptual issues 28–31 context 39–41, 66–67 definition 17–18, 141, 257–62, 290 development 24, 26–28, 142–43, 152–53 developmentally appropriate tasks 85–86, 93–94 dimensions 24–26 dyslexia 167–68 educational setting 288–95 factor analytic methods 24–26, 79–80 frontal lobe 18, 278–80 functional assessment 21–22 hierarchical organization 28 Holarchical Model of Executive Capacities/ Control (HMEC) 258–62, 263–64 interventions 69–70, 269–70 minimizing when writing 39 models 139–42 neurobiology 18–19 overview of relationship with writing 144–49 problem-solving models 141 psychological models 140–41 questionnaire-based assessment 20–21 rating scales (self-reports) 91–95 selection of measures 95–96 sentence writing 184–86 skilled writers 213–19 specific learning disorders 161–62, 166–68 staged acquisition 27–28 standardized assessment tools 22 state–trait variations 28–29 theoretical models 22–24 tripartite model 25–26, 79–80, 161 working memory model 142 writer(s)-within-community model 42, 48–49, 52–56, 58–59, 60–62, 63–66, 67, 68b, 69–70 writing instruction 182–84 writing process 187–96, 219–21 written text production 121–22 expository writing 117 factor analytical techniques 24–26, 79–80 Fidalgo, R. 148–49 First Author® software 197 Fist-Edge-Palm test 278–79 Flick, A. 184–85 Flower, L. 3 FLYPenTM 197 free-writing 39 Friedman, N.P. 24–25 frontal lobe 18, 278–80 Frontal Systems Behavior Scale (FrSBe) 93–94
Index 299 Garon, N. 27–28 Garrard, P. 243 gender differences 235, 293 generalisability theory 116 goals 23, 26–27, 54, 183, 214, 278, 280, 282 go/no-go tasks 81, 87t Graham, A. 85 Graham, S. 182, 192 graphic errors, dementia 242 Greene, J.A. 152–53 Guignouard, C. 217 halo effect 93 handwriting ADHD 165–66 age-related changes 234–35, 236–37 autism spectrum disorder 162–63 automaticity 143 calligraphy training 247 cognitive effort 218 dysgraphia 168 dyslexia 167 executive demands 219–20 gender differences 235 working memory capacity 211–12 writer(s)-within-community model 67 writing bursts 113 written text production 119 Harris, K.R. 192 Hayes, J. 3–4 hierarchical models 24–25 Hodges, J.R. 243 Holarchical Model of Executive Capacities/Control (HMEC) 258–62, 263–64 Holarchical Model of Executive Functions (HMEF) 258 Hooper, S.R. 146, 152–53 Hughes, C. 85 ideation 50 inhibition 25–26, 79–80, 144–45, 161, 222 ADHD 144–45, 165, 166 age-related changes in writing 238–39 assessment 80–82, 87t autism spectrum disorder 163 deficit-linked writing problems 164t dyslexia 167–68 intentional stage of writing 281–82 intentions 54–55, 240 interventions executive function difficulties 69–70, 269–70 healthy ageing 244–47 writing in neurodevelopmental disorders 169–70 Intra-Extra Dimensional Set Shift (ID/ED) task 82–83, 87t
James, P.D. 243–44 jingle-jangle fallacy 30–31 Johnson, J. 146–47 Jones, J. 146–47 journaling 247 Kalman, Y. 236 Karr, J.E. 24 Kaufman Test of Educational Achievement –Third Edition (KTEA-3) 267–68 Kavé, G. 236 Kellogg, R.T. 210–11, 238, 239–40 Kemper, S. 233 Kim, Y.-S. 119–20, 147–48 knowledge telling 115 language age-related changes 230 oral language skills 120 Lapidos, C. 246–47 Larigauderie, P. 217 leniency bias 93 letter monitoring task 83, 87t, 90–91 Lezak, M. 22–23 Limpo, T. 114, 148–49, 192–93 listening recall 83–84, 87t long-term memory 51–52 Luria, A. 278–79, 290 Lyons, K.E. 29–30 McCloskey, G. 258, 264–65 McCloskey Executive Functions Scales 263–64 McCutchen, D. 211 Maloney, L.M. 243 Mason, L.H. 192, 193–94 Matching Numbers 279–80 memory span 83–84, 89–90 metacognition 29–30, 114 mild cognitive impairment 240, 241, 242 Misra, S.B. 283 Miyake, A. 24–25, 79–80 mnemonic keyword method 169 motivation 46, 141, 183 motor competence 18–19 Multiple Errands Tests 21–22 Munakata, Y. 26–27 Murdoch, Iris 243–44 narrative writing 117 N-back tasks 84, 86, 87t, 89–90 neurodevelopmental disorders 160–80 ADHD 85–86, 144–45, 161–62, 165–71 autism spectrum disorder 85–86, 161–63, 170 specific learning disorder 161–62, 166–68 writing interventions 169–70
300 Index NIH Examiner 22 NIH Toolbox 22 Not-So-Simple model 121, 143, 213–14, 217–18 novel writing 38, 243–44 Nyongesa, M. 80 older people see ageing writers Olive, T. 217, 219–20 online planning 111 oral language skills 120 Ozminkowski, R.J. 246–47 parawriting 282 Pascual-Leone, J. 146–47 pattern recall task 83–84 Patterson, K. 243 Pennington, B.F. 140–41 Pennington, R. 184–85 Perkins, L.A. 264–65 perseverative errors 163 personality 57 persuasive writing 194, 195t physiological states 57 Piolat, A. 216–17 Planned Codes 279–80 Planned Connections 279–80 planning 3–4, 54–55, 110, 148–49, 278–80, 281–82 action 280, 282 activity 280, 281–82 ADHD 165 cognitive effort 214–15 content 214–15 online 111 operations 280–81, 282 prewriting 111–12 process 214 Self-Regulated Strategy Development (SRSD) model 192–94 PLANS strategy 193–94 Poncelet, M. 148 poverty 18–19 POW strategy 190 predicament test 282–84 prefrontal cortex 18–20, 278, 289–90 prewriting planning 111–12 problem-solving 23, 141, 148 Process Assessment of Learner-Second Edition (PAL-II) 266–67 production bursts 112–13 production processes 50–51 quick-writes 40–41, 190–92
Raver, C.C. 29 reaction phase 55 reading comprehension 193–94 critical reading and cognitive effort 216–18 development 292 written text production and 120–21 Reciprocal Motor Programme test 278–79 reconceptualization 51 Regan, K. 198 Reve, Gerard 243 revision 3–4, 110, 113–14 bursts 112 cognitive effort 216–18 Roebers, C.M. 30 Roussey, J.-Y. 216–17 running span task 84, 87t, 89 scaffolding instruction 149, 194–96 Schacher, R. 144 Schatschneider, C. 147–48 self-instruction 183 Self-Regulated Strategy Development (SRSD) model 67, 149, 169–70, 187–96, 269–72 self-regulation 29–30, 183–84, 221, 258 technology with embedded self-regulation 197–201 sentence writing dementia 241 executive functions 184–86 shifting 24–25, 79–80, 82–83, 87t Simon task 81, 87t simple view of writing 213–14, 217–18 Smith-Wehr, K. 184–85 sociocultural approach 115, 182, 202 specific language impairment 85–86 specific learning disorder 161–62, 166–68 speech-to-text programs 197 spelling age-related changes 231–32, 236–37 cognitive effort 215 dementia 241 dyslexia 167 inhibition and 144–45 written text production 119, 120 Spelling, Punctuation and Grammar (SPAG) test 105–6 statue task 82, 87t stop-signal tasks 81, 86–89, 87t, 144–45 STOP strategy 194–96 Strategy Instruction Model (SIM) 185–86 Stroop task 80–81, 85, 86–89, 87t, 90, 238–39 subject-verb agreement 216
Index 301 summary writing 233–34 Supiano, K.P. 246–47 symmetry span 83–84, 87t syntax age-related changes 232–33 dementia 242 Systematic Analysis of Language Transcripts (SALT) 118 task impurity problem 90 teaching writing 67–70, 182–84 interventions in neurodevelopmental disorders 169–70 technology-based writing 197–201 thinking-then-writing 220–21 thinking-while-writing 220–21 TIDE strategy 191 top-down process 3–4, 17–18 Toplak, M.E. 20–21, 94–95 Tower of Hanoi (London) 81–82, 86, 87t, 90–91 trail making task 82, 87t, 89 transcription 50–51, 104–5, 110, 113, 119, 218–20 translation 3, 50, 110, 112–13, 146, 218–20 TREE strategy 191, 194 triple task technique 213–14 TWA strategy 193–94 type token ratios 108–9 typing skills 218 age-related changes 236 Umanski, D. 236 updating 25–26, 79–80, 83–84, 87t, 222 Wagner, R.K. 108 Wallace, I. 38 Wechsler Objective Language Dimensions (WOLD) 106–7 Welsh, M.C. 140–41 Williams syndrome 85–86 Winn, W.D. 143 Wisconsin card sorting test (WCST) 82, 86, 87t, 90–91 WJ-IV Tests of Oral Language 267–68 word fluency test 90–91 word span task 83–84 working memory 3–4, 147–48, 161, 209, 278 ADHD 165, 166 age-related changes in writing 237–38 autism spectrum disorder 163 capacity model 211–13 componential model 210–11
deficit-linked writing problems 164t dysgraphia 168 dyslexia 167–68 executive functions 142 revision process 113–14 specific learning disorder 168 updating 25–26, 79–80, 83–84, 87t, 222 written text production 121 writer(s)-within-community model 55–56 writer(s)-within-community (WWC) model 38– 76, 182, 187 agency 39–40, 50, 52–54, 58, 60–61, 289 age-related changes in writing 239–40 capacity of community 59, 62–63 development 60, 64–65 executive control 42, 48–49, 52–56, 58–59, 60– 62, 63–66, 67, 68b, 69–70 interactions 60–62, 63–64 teaching writing 67–70 variability of community 59–60 writers and their collaborators 49–59 writing community 42–49 writing automatization 208, 211–12, 219–20 Bigg’s three stage model 281–82 bursts 112–13 definition 104–5 five-factor model 108 low-level and high-level skills 148, 219 proximal and distal factors 119–22 writing assessment 103–35 analytic scoring 105, 107 automated scoring 118–19 curriculum-based measures 116–18 fine-grained analysis 105, 108–9 generalisability theory 116 holistic scoring 105, 106–7 lexical diversity 107–8 macrostructure and microstructure 107–8 orthographic transparency 124–25 productivity 107–8 quality 107–8 text genre 117–18 writing process 110–15 written product 106–10 writing groups 246–47 writing instruction 67–70, 182–84 interventions in neurodevelopmental disorders 169–70 Zelazo, P.D. 23, 29–30, 141