Usage-Based Dynamics in Second Language Development 9781788925259

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Usage-Based Dynamics in Second Language Development

SECOND LANGUAGE ACQUISITION Series Editors: Professor David Singleton, University of Pannonia, Hungary and Fellow Emeritus, Trinity College, Dublin, Ireland and Associate Professor Simone E. Pfenninger, University of Salzburg, Austria This series brings together titles dealing with a variety of aspects of language acquisition and processing in situations where a language or languages other than the native language is involved. Second language is thus interpreted in its broadest possible sense. The volumes included in the series all offer in their different ways, on the one hand, exposition and discussion of empirical findings and, on the other, some degree of theoretical reflection. In this latter connection, no particular theoretical stance is privileged in the series; nor is any relevant perspective – sociolinguistic, psycholinguistic, neurolinguistic, etc. – deemed out of place. The intended readership of the series includes final-year undergraduates working on second language acquisition projects, postgraduate students involved in second language acquisition research, and researchers, teachers and policymakers in general whose interests include a second language acquisition component. All books in this series are externally peer-reviewed. Full details of all the books in this series and of all our other publications can be found on http://www.multilingual-matters.com, or by writing to Multilingual Matters, St Nicholas House, 31-34 High Street, Bristol BS1 2AW, UK.

SECOND LANGUAGE ACQUISITION: 141

Usage-Based Dynamics in Second Language Development In Celebration of Marjolijn Verspoor

Edited by

Wander Lowie, Marije Michel, Audrey Rousse-Malpat, Merel Keijzer and Rasmus Steinkrauss

MULTILINGUAL MATTERS Bristol • Blue Ridge Summit

DOI https://doi.org/10.21832/LOWIE5242 Library of Congress Cataloging in Publication Data A catalog record for this book is available from the Library of Congress. Names: Lowie, Wander - editor. | Michel, Marije - editor. | Rousse-Malpat, Audrey - editor. | Keijzer, Merel - editor. | Steinkrauss, Rasmus - editor. | Verspoor, Marjolyn, honoree. Title: Usage-Based Dynamics in Second Language Development/Edited by Wander Lowie, Marije Michel, Audrey Rousse-Malpat, Merel Keijzer, Rasmus Steinkrauss. Description: Blue Ridge Summit: Multilingual Matters, 2020. | Series: Second Language Acquisition: 141 | “In Celebration of Marjolijn Verspoor” | Includes bibliographical references and index. | Summary: “This book honours the contribution of Marjolijn Verspoor to the development and implementation of dynamic usage-based approaches in second language research and pedagogy. With chapters written by renowned experts in the field, the book addresses the dynamics of language, language learning and language teaching from a usage-based perspective”— Provided by publisher. Identifiers: LCCN 2020011243 (print) | LCCN 2020011244 (ebook) | ISBN 9781788925235 (paperback) | ISBN 9781788925242 (hardback) | ISBN 9781788925259 (pdf) | ISBN 9781788925266 (epub) | ISBN 9781788925273 (kindle edition) Subjects: LCSH: Second language acquisition—Study and teaching. | Language and languages—Study and teaching—Foreign speakers. | Speech acts (Linguistics)—Study and teaching. Classification: LCC P118.2 .U75 2020 (print) | LCC P118.2 (ebook) | DDC 418.0071—dc23 LC record available at https://lccn.loc.gov/2020011243 LC ebook record available at https://lccn.loc.gov/2020011244 British Library Cataloguing in Publication Data A catalogue entry for this book is available from the British Library. ISBN-13: 978-1-78892-524-2 (hbk) ISBN-13: 978-1-78892-523-5 (pbk) Multilingual Matters UK: St Nicholas House, 31-34 High Street, Bristol BS1 2AW, UK. USA: NBN, Blue Ridge Summit, PA, USA. Website: www.multilingual-matters.com Twitter: Multi_Ling_Mat Facebook: https​://ww​w.fac​ebook​.com/​multi​lingu​almat​ters Blog: www.c​hanne​lview​publi​catio​ns.wo​rdpre​ss.co​m Copyright © 2020 Wander Lowie, Marije Michel, Audrey Rousse-Malpat, Merel Keijzer, Rasmus Steinkrauss and the authors of individual chapters. All rights reserved. No part of this work may be reproduced in any form or by any means without permission in writing from the publisher. The policy of Multilingual Matters/Channel View Publications is to use papers that are natural, renewable and recyclable products, made from wood grown in sustainable forests. In the manufacturing process of our books, and to further support our policy, preference is given to printers that have FSC and PEFC Chain of Custody certification. The FSC and/or PEFC logos will appear on those books where full certification has been granted to the printer concerned. Typeset by Deanta Global Publishing Services, Chennai, India.

Contents

Contributors vii Prologue xiii Kees de Bot Introduction 1 1 Thinking for Speaking in an L2: From Research Findings to Pedagogical Implications Teresa Cadierno

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2 On the Sample Size Required to Identify the Longitudinal L2 Development of Complexity and Accuracy Indices Akira Murakami

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3 A DUB-Inspired Case Study of Multidimensional L2 Complexity Development: Competing or Connecting Growers? 50 Bram Bulté and Alex Housen 4 A Holistic Person-Centred Approach to Mobile-Assisted Language Learning Hongying Peng, Sake Jager, Steven L. Thorne and Wander Lowie 5 Creativity and Routinisation in L2 English: Two Usage-Based Case Studies Søren W. Eskildsen 6 Attractor States in the Development of Linguistic Complexity in Second Language Writing and the Role of Self-Regulation: A Longitudinal Case Study Attila M. Wind and Luke Harding

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7 Competence Appraisals: Dynamic Judgements of Communication Competence in Real Time Peter D. MacIntyre and Samantha Ayers-Glassey 8 Dynamic Changes in Motivation and Willingness to Communicate in the Second Language Classroom: A Multiple Case Study Giulia Sulis, Joanna Davidson and Marije Michel 9 Nested Locatives: Conceptual Basis and Theoretical Import Ronald W. Langacker

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10 Getting Out the Word on Phrasal Verbs: It Turns Out Phrasal Verb Construction Meanings are Systematic and Teachable Andrea Tyler, Hana Jan, Nargas Mahpeykar and Brandon Tullock

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11 The Icing On the Cake? Effects of Explicit Form-Focused Instruction after Two Years of Implicit EFL Learning Leslie Piggott, Elena Tribushinina and Rick de Graaff

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12 Film Language Integrated Learning: A Usage-Inspired L2 Teaching Approach Tim Kassenberg, Fabio Galati, Diana de Vries-Zhuravleva and Iryna Menke-Bazhutkina

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Epilogue 295 Diane Larsen-Freeman Index 301

Contributors

Samantha Ayers-Glassey is a fourth-year psychology student at Cape Breton University completing her undergraduate honour’s bachelor of sciences degree. She is currently employed as a research assistant for Dr Peter MacIntyre, working on second language communication competence and non-verbal-behaviour strategies. Her general research interests include cognitive neuroscience, attention and emotion regulation, topics which she hopes to pursue further at the graduate level. Kees de Bot received his PhD from the University of Nijmegen. He was chair of applied linguistics and is now an emeritus professor of the University of Groningen and full professor of applied linguistics at the University of Pannonia in Vészprem in Hungary. His research interests include the application of Complex Dynamic Systems Theory in second language development and multilingualism, multilingual processing, language attrition and the history of applied linguistics. More recently, he has become interested in ethical issues and truth in science. He is one of the organisers of the 2020 (now 2021) World Congress of the International Association of Applied Linguistics in Groningen. Bram Bulté has been a guest professor and post-doctoral researcher in linguistics at the universities of Brussels, Leuven and Ghent. He specialises in second language acquisition, statistics, computational linguistics and natural language processing. Teresa Cadierno is full professor at the Department of Language and Communication at the University of Southern Denmark. Her research interests include instructed second language acquisition, with a special focus on the acquisition of grammar by L2 learners; L2 input processing and the role of formal instruction in L2 acquisition; and applied cognitive linguistics, especially the acquisition of L2 constructions for the expression of motion events and the investigation of re-thinking for speaking processes in a foreign language.

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Joanna Davidson is an English language teacher at the University of Toulouse, France. She graduated from the University of Lancaster with an MA in applied linguistics and TESOL, where her research interests included Willingness to Communicate (WTC) in the L2 classroom and Complex Dynamic Systems Theory (CDST). Søren W. Eskildsen is an associate professor in second language (L2) learning at the University of Southern Denmark in Sønderborg. His primary research interest concerns usage-based processes and practices in second language learning over time as seen through the lens of usagebased models of language and conversation analysis. Other interests include the role of gestures in L2 learning. He works with both in- and out-of-class L2 data. Fabio Galati is a lecturer of Italian proficiency and linguistics at the Department of European Languages and Cultures of the University of Groningen. In the field of linguistics, his interests concern the history of the Italian language, specifically in relation to Italian identity and language standardisation. Rick de Graaff is professor in foreign language pedagogy at Utrecht University and the University of Applied Sciences Utrecht. His research focuses on effective teaching interventions in foreign language education. Luke Harding is a senior lecturer in the Department of Linguistics and English Language at Lancaster University (UK). His research interests are in language assessment and applied linguistics more broadly. His work has been published in international journals such as Applied Linguistics, Language Testing and Assessing Writing. He is currently co-editor of the journal Language Testing. Alex Housen is professor of English linguistics and applied linguistics in the Department of Linguistics and Literary Studies at the Vrije Universiteit Brussel. His research focuses on linguistic, cognitive and social factors in second language acquisition, bilingualism, and bilingual and language education. His recent publications (in Studies in Second Language Acquisition, The Modern Language Journal and Second Language Research) deal with second language complexity and cognitive mechanisms in second language acquisition. Sake Jager holds a PhD in applied linguistics from the University of Groningen. He is assistant professor in applied linguistics and is head of the department of ICT in Education (University of Groningen). He specialises in computer-assisted language learning (CALL) with a research focus on the integration of CALL in institutional environments.

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Hana Jan is an assistant professor of applied linguistics at the English Language Institute in King Abdulaziz University, Saudi Arabia. Her research interests include crosslinguistic influence in bilingualism and applied cognitive linguistics. Her work focuses on employing cognitive linguistic theories to teach English as a second/foreign language and to explain similarities and differences in conceptualisation between Arabic and English especially in describing spatial scenes. Tim Kassenberg is a lecturer of English for academic purposes, English linguistics and applied linguistics at the University of Groningen. His teaching and research interests lie in usage-inspired teaching methods and computer-assisted language learning (CALL). In particular, he is interested in finding ways to combine findings from these areas to create principled and evidence-based teaching materials for second and foreign language teaching. Merel Keijzer (PhD in linguistics, VU University, Amsterdam, 2007) is professor of English linguistics and English as a second language at the University of Groningen, where she also chairs the Bilingualism and Aging Lab (BALAB). Her research interests are bilingual language use and development, with a special interest in the linguistic, social and cognitive consequences of third-age language learning. Ronald Langacker was professor of linguistics at the University of California, San Diego from 1966 until his retirement in 2003. He has published extensively in Cognitive Linguistics, and since 1976 has been developing the theoretical framework of cognitive grammar. Diane Larsen-Freeman is professor emerita of education and linguistics, research scientist emerita and former director of the English Language Institute at the University of Michigan. She is also professor emerita at the SIT Graduate Institute in Brattleboro, Vermont and a visiting faculty member at the University of Pennsylvania. Her recent books are Complex Systems and Applied Linguistics (2008, with L. Cameron), winner of the MLA’s Kenneth Mildenberger Book Prize, the third edition of Techniques and Principles (2011, with M. Anderson), the third edition of The Grammar Book, Form, Meaning, and Use for English Language Teachers (2015, with M. Celce-Murcia), and Second Language Development: Ever Expanding (2018). Wander Lowie holds a PhD in linguistics from the University of Groningen and is chair of applied linguistics at this university. He is a research associate of the University of the Free State in South Africa and is associate editor of The Modern Language Journal. His main research interest lies in the application of Dynamic Systems Theory to second language

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development (learning and teaching). He has published more than 50 articles and book chapters and (co-)authored five books in the field of applied linguistics. Peter D. MacIntyre received his PhD in psychology from the University of Western Ontario (now Western University) in 1992 with R.C. Gardner and is currently a professor of psychology at Cape Breton University. The majority of Peter’s research examines the psychology of communication, including motivation, anxiety and willingness to communicate, with a particular emphasis on second language contexts. His books (coauthored or co-edited) include Capitalizing on Language Learners’ Individuality (2014), Motivational Dynamics in Language Learning (2015), Positive Psychology in SLA (2016), Innovative Practices in Language Teacher Education (2017), and Optimizing Language Learners’ Nonverbal Behavior: From Tenet to Technique (2017). Narges Mahpeykar is a researcher at Apollo Strategic Communications, London, UK. Narges received her PhD in linguistics from Georgetown University. Her dissertation is entitled ‘A Principled Cognitive Account of English Phrasal Verbs’. Her primary interest is in cognitive linguistic approaches to language and language learning. Iryna Menke-Bazhutkina is a lecturer of German at the Department of European Languages and Cultures at the University of Groningen. In her teaching and research, she is especially interested in the effect of different teaching methods on second language acquisition, the development of objective assessment criteria based on empirical research and the design of content and language integrated learning materials. Marije Michel (PhD applied linguistics from the University of Amsterdam) is chair of language learning at the University of Groningen in the Netherlands. Her teaching and research focus is on socio-cognitive aspects of second language acquisition and task-based language pedagogy. In her recent work, she has used eye-tracking and key-stroke logging to investigate second language writing processes and alignment in digitally mediated communication. Marije Michel is treasurer of the executive committee of the European Second Language Association (EuroSLA). Akira Murakami is a Birmingham fellow at the University of Birmingham. His main research interests are in second language acquisition, corpus linguistics and quantitative data analysis. Prior to joining Birmingham, he worked as a post-doctoral researcher at the Universities of Birmingham, Cambridge and Tübingen. Hongying Peng is a PhD student in applied linguistics at the University of Groningen. Her current research interests include the use of mobile

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technologies in language learning and methodological issues relating to Complex Dynamic Systems Theory (CDST). Leslie Piggott is an EFL teacher in secondary education and has recently completed her PhD research project on the effects of implicit formfocused instruction on foreign language acquisition in classroom settings at Utrecht University. Audrey Rousse-Malpat received her PhD in applied linguistics in 2019 at the University of Groningen. Her main research interests are the effectiveness of language teaching methods, innovations in language curricula and dynamic usage-based inspired pedagogy. She is currently an assistant professor of language learning at the University of Groningen where she teaches French linguistics and French proficiency. Rasmus Steinkrauss is an assistant professor of applied linguistics at the University of Groningen where he teaches courses on first and second language development and research methods. His research interests are L1 and L2 development from a usage-based construction grammar perspective, the role of variability in language development and the interaction between language development and working memory. Giulia Sulis is currently a post-doctoral fellow at the University of Graz. She graduated from the University of Groningen with a Master’s in Applied Linguistics and pursued her PhD in Linguistics and English Language at Lancaster University. Alongside her PhD, she worked as Associate Lecturer in Literacy and Education and as a tutor of English for Academic Purposes (EAP) at Lancaster University. Her research interests lie in the psychology of language learning and teaching; in particular, she is currently researching motivation, engagement, Willingness to Communicate (WTC), and teacher wellbeing. Steven L. Thorne is professor of second language acquisition in the Department of World Languages and Literatures at Portland State University (USA), with a secondary appointment in the Department of Applied Linguistics at the University of Groningen (the Netherlands). His interests include formative interventions in world languages education and research that draws on contextual traditions of language analysis and usage-based and distributed approaches to language development. Elena Tribushinina is an assistant professor in the acquisition of English as a first and a second language at Utrecht University. Her research focuses on child bilingualism and developmental language disorders. Brandon Tullock is an assistant professor in the Department of World Languages, University of South Florida. He received his PhD in linguistics

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from Georgetown University in 2019. His dissertation is entitled ‘Identity and Transnationalism in Study Abroad: Multilingual Sojourners in Barcelona’. His primary foci of research include second language acquisition, multilingualism and study-abroad programmes. Andrea Tyler is professor emerita in the Department of Linguistics, Georgetown University. She has published extensively on usage-based theories of language, including cognitive linguistics and discourse analysis, and the application of these theories to second language learning. Her book, Cognitive Linguistics and Second Language Learning: Theoretical Basics and Experimental Evidence, won the 2013 BAAL Book Award. Diana de Vries-Zhuravleva is a lecturer of Russian language proficiency at the University of Groningen. Her research and teaching interests are predominantly based in the area of second language development within a usage-based perspective and content and language integrated learning (CLIL). She is particularly interested in creating materials and tasks which integrate movies in language learning. Attila M. Wind completed his PhD in the Department of Linguistics and English Language at Lancaster University (UK). His research interests are in the area of second language development more broadly, with a special focus on second language writing development from a Complex Dynamic Systems Theory perspective.

Prologue CDST: Everything Dynamic Goes? Kees de Bot

As in all research areas, theories in applied linguistics (AL) have their own life cycle. Ever since Kuhn’s (1962) groundbreaking The Structure of Scientific Revolutions, we know that theory development in science is not a gradual or linear process. According to Kuhn, science develops in three distinct stages. The start is ‘prescience’ in which there is no central paradigm, but rather a wild and incoherent set of ideas brought together. This is followed by ‘normal science’, when scientists attempt to enlarge the central paradigm by ‘puzzle-solving’. The third stage is ‘revolutionary science’ in which a new paradigm emerges that can deal with both old data that didn’t fit with the existing paradigm and with new data that can only be explained within the new paradigm. New theories have to prove their worth. Journals, editors and reviewers will be critically evaluating the publications based on a new framework, and while getting publications into leading journals continues to be problematic, gradually more and more leaders in the field are starting to endorse the new paradigm. At this point, a theory may reach a critical state where it may either show a breakthrough or start a gradual demise because in the end the theory did not meet the expectations, or the resistance is too strong. Does this also apply to Complex Dynamic Systems Theory (CDST)? With respect to the impact of CDST in developmental psychology. Van Geert (2011) sketches three scenarios: • The pessimistic stance is that such a paradigm shift [to CDST thinking] will not occur, primarily because the forces that act against paradigm shifts in developmental psychology – if not in all scientific disciplines – are now too strong to allow for paradigm shifts. • The less pessimistic prediction is that DST will not diffuse into developmental psychology as a whole as I would hope, but will survive as yet another subdivision in developmental psychology. • The optimistic prediction is that in line with DST itself, the growing number of currently rather isolated islands of DST applications in

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the world will finally form a critical mass, leading to a tipping point phenomenon... Or a velvet evolution. (Van Geert, 2011: 277) More or less the same holds for CDST and AL, and it is not clear what direction CDST will take. When CDST was introduced to AL by LarsenFreeman in 1997, her article on this topic did not catch on immediately; it took the field almost a decade to see the potential of her contribution as several other research groups around the world joined in in what has been called ‘the dynamic turn’ (de Bot, 2015). While there is a substantial core group of researchers working on CDST at this point, only time will tell whether the seeds that were planted by the older generation will bear fruit in the years to come. Theories go through different stages and cycles. They do not emerge out of the blue, but result from earlier thinking and empirical work. There is always a current paradigm, even if that paradigm is not systematically defined. Paradigm shifts follow from dissatisfaction with current and old paradigms. There may be new data, or new types of data (such as neuroimaging techniques in cognitive science) that are incompatible with the existing paradigm. There may also be conflicts at the personal level leading to groups splitting off (and becoming the fiercest opponents of the ‘old’ paradigm). To what extent and how quickly new theories are accepted by a given research community depend on the state of the field and the forces that hinder or support it. ‘Research data only really become information when they attract advocates for the messages they contain. Thus endorsement of data as “evidence” reflects judgments that are socially and politically situated’ (Nutley et  al., 2013: 24). So, the next phase of the cycle is the spreading of the word through publications and presentations at conferences, books and special issues of journals, and training a younger generation in the new framework. Researchers working within the new paradigm will try to convince others to consider the new theory as an alternative. Resistance or acceptance will differ between those who belong to the orthodox followers of the old paradigm and those who are eclectic in their use of theories. New theories may be seen as a threat by researchers working exclusively in an existing theoretical framework. They may have built their career on that framework and are known for it, get invited as plenary speakers, acquire subsidies and are promoted to full professor. A new theory always calls for substantial investment and openness to something new and may put all of that in peril. For example, the resistance against a CDST approach was clearly voiced by Kevin Gregg in his 2010 review of Larsen-Freeman and Cameron’s (2008) book on CDST. Gregg is not known for the subtlety of his evaluation of anything outside strict universal grammar (UG) thinking. His main point is that language is not a dynamic system:

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If we take ‘language’ in a narrower sense to refer to the linguistic competence(s) of an individual – the standard view in theoretical ­linguistics – all normal humans reach a steady state fairly early in life, which is to say that language in this sense is not dynamical, hence by definition not a complex system. When I say steady state, I mean steady: I have been using English for more years than I am going to let on, and since puberty at least, pretty much nothing has happened to my phonological, semantic, or syntactic knowledge. (Gregg, 2010: 553)

Apart from the fact that there is substantial evidence for language attrition through non-use and crosslinguistic influence (Schmid, 2011), it is hardly conceivable that Gregg’s language system was completely unaffected by his move to a Japanese university. Also, it is questionable if the linguistic ‘competence’ of an idealised individual is currently the standard definition of ‘language’ in linguistics. In the past decades, the impact of UG-based approaches to second language development (SLD) has clearly declined (Hulstijn, 2019). After having seen golden years in which UG seemed the only acceptable theory of language, with a massive presence at conferences and easy access to leading international journals and subsidies for researchers working within UG, in recent years the role of UG as the leading paradigm is beginning to be taken over by Usage-Based approaches which are compatible with CDST thinking. Another typical phenomenon in theory building is that early adopters become defenders of the original version of the new paradigm which they tend to see as the ‘true’ theory. However, if a new theory catches on, its reach will automatically broaden. The zealots will resist any adaptation and aim at defining the essential characteristics as much and as narrowly as possible. If a theory causes a breakthrough, more and more researchers will pick it up and either adapt their work to make it fit with the new kid in town, or they try to stretch the theory to make their research fall under the new paradigm and belong to the work by the frontrunners to which they aspire. With growing popularity, the more technical/mathematical parts and labels of the theory become mainstream, and with that these labels lose their specific meaning. A good example in the present context is the term ‘dynamic’. While in CDST this refers to the changing interaction of variables over time, in the mainstream this specific meaning gets lost. Now, numerous articles mention the term ‘dynamic’ even though a CDST interpretation is not intended. So what is required for research to be labelled ‘dynamic’ in a CDST sense? According to most researchers in CDST, the essence of CDST is the dynamic interaction of variables, so an interaction that changes over time. This means that there should always be something that changes. Measuring language development over time requires data on different time scales, and thus dense longitudinal studies are needed. This brings

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about a practical problem when conducting research in a CDST framework: Since longitudinal research implies repeated data collection over a longer period of time, finding funding is a major challenge and once secured, for PhD students a problem might be that longitudinal studies hardly fit in the typical three to four-year PhD contracts. But as several of the papers in this volume show, it can be done. In his influential book Against the Current. Essays in the History of Ideas, Isaia Berling (1979) discusses the development of ideas with an emphasis on almost forgotten thinkers whose work was not appreciated or valued in their own lifetime, only to re-emerge much later. As is evident from his discussion of theories in different fields, not all ideas come to fruition and most theories are short-lived. In his highly interesting A Directory of Discarded Ideas, Grant (1981) discusses a large number of ideas that were ultimately untenable, but that created the foundation for more durable ideas. While we can ridicule these discarded ideas on the basis of current knowledge, a proper analysis shows that much of the knowledge at any point comes from research at earlier moments in time, and our current ideas may be ridiculed when their time comes. So if old theories are superseded by newer theories, how exactly is it that theories fail? There may be various reasons, some of them scientific, others more sociological. It may be that there is no empirical support for the theory or that, over time, the scientific landscape changes in such a way that the original empirical foundation no longer meets contemporary standards. Another reason is the so-called ‘decline effect’. In 2010, Lehrer wrote an article for the New Yorker on this effect which may occur when scientific claims receive decreasing support over time. Lehrer discusses a number of examples, mainly from medicine, and concludes that decline may be caused by the need to have a new niche, by a publication bias, but also by satiation. Other factors are the retirement/death of the main figures who were instrumental in the development of the theory, and the theory being overtaken by a new theory. In her discussion of CDST, Larsen-Freeman (p.c. 5/6/2017) raised the issue of what constitutes a theory. Do CDST, or UG, or Usage Based (UB) actually qualify as ‘theories’? What exactly is a theory is a matter of debate. An influential definition is the one by the American Academy of Science: In science, the term ‘theory’ refers to a well-substantiated explanation of some aspect of the natural world, based on a body of facts that have been repeatedly confirmed through observation and experiment. (National Academy of Sciences, 1999: 2)

What ‘some aspect of the natural world’ is for AL depends on one’s definition of AL. De Bot (2015) asked some 100 researchers in the field of AL how they would define the field. Roughly speaking, there were three perspectives:

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• Everything linguistic apart from theoretical/descriptive linguistics. • The application of linguistic knowledge and tools to solve real-world problems, and more specifically language learning and teaching. • The study of SLD. In our discussion of the life cycle of theories, we will limit our scope to the last perspective; thus, theories on SLD as ‘some aspect of the natural world’. These theories range from UG and sociocultural theory to usagebased approaches and CDST. It is not always clear what these theories are actually theories of. No theory can claim to cover the complete process of language in use, and there is no single overarching theory for all aspects of SLD. Most theories focus on linguistic or grammatical aspects (Processability Theory/UB/Input Processing), others take language functions as a starting point (Systemics, Sociocultural Theory [SCT]). Some are general theories of development and change (SCT/Connectionism, CDST) that may or may not have specific subtheories dealing with SLD. Since the various theories deal with different dimensions on SLD, their development may vary in direction and pace. The issue focused on here is whether they go or have gone through similar stages over time. Theories are typically dynamic and changing due to new findings, changes in Zeitgeist or the emergence of competing theories. It is proposed here that theories go through two types of cycles. The first cycle is one in which a theory emerges and becomes established, the second is one in which satiation takes place and new theories challenge the current one. These cycles are similar to Kuhn’s normal and revolutionary science. The adherents to a specific theory are not necessarily in the same stage of adoption. Some of the forerunners may no longer experience the novelty of the theory, while for others it is the new thing for which they have been looking. This holds for CDST too. In addition, while many researchers have taken it on as a useful mid-level theory and use its metaphorical means to get a better insight into the processes of development, others point to the weaknesses or the overlying mathematical nature of the theory. As mentioned earlier, theory choice by an individual researcher is often assumed to be a completely rational process, but this is probably not true. Larsen-Freeman and Cameron argue: The theory that we choose to work with, explicitly as researchers and perhaps implicitly as teachers, will dictate how we describe and investigate the world. It controls how we select, out of all that is possible, what to investigate or explain, what types of questions we ask, how data are collected, and what kinds of explanations of the data are considered valid. (Larsen-Freeman & Cameron, 2008: 160)

All of the above is relevant when we talk about Marjolijn Verspoor. With her colleagues, she importantly contributed to turning CDST and

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its development into a prominent new perspective. But to get there, she had to follow a long and winding road. After attending a traditional, grammar-focused teacher trainer programme, she moved to the United States where she worked as a language teacher, including German, for which she was hardly trained. In those 20 years, she managed to write several handbooks, and worked with Winitz on autonomous language learning programmes. She completed her PhD in Leiden. It was around this time that she abandoned UG for various reasons. The main reason was that the educational effects of this linguistic theory were too limited and that alternative linguistic theories such as Cognitive Linguistics (CL) provided a much stronger starting point. Around that time, in the 1970s and 1980s, UG was by far the most dominant theory in most linguistic departments. So this was not an easy time for an aspiring researcher to find a research position that was not UG oriented. Despite that, she opted for Groningen where the UG researchers formed a strong and self-conscious group that was not particularly open to newcomers from another church. Marjolijn Verspoor realised that for her, becoming the umpteenth generative grammar linguist in such a competitive environment was not the most attractive option. This is not to say that the choice she made for Cognitive Grammar (CG) and its theories on development made her path unwinding and short. CG in those days was not taken seriously as she found out, and there was basically no room for more and deviant researchers, so she went on to take a job as an English language teacher, which has continued to be an important interest and source of inspiration, and data, in particular on L2 writing development. In 2007, the widely cited Bilingualism: Language and Cognition article on the relevance of DST for second language learning was published, which was inspired by earlier work from Diane Larsen-Freeman and Paul van Geert (de Bot et al., 2007). Marjolijn then developed a line of research with several PhDs on CDST and its application, the dynamicity of which was a regular point of discussion at staff research meetings. She heralded the implementation of a more lenient CDST school that liberally applied notions from CDST. As all CDST adepts, she, often with a colleague or PhD student, submitted various articles to leading AL journals with mixed success (though most of these early writings have been published in adapted form in the meantime). Coming back to the life cycle of theories, it is obvious that CDST is now in the second cycle. There is some satiation in the research groups working on CDST, but many researchers have met their limits in terms of statistical and mathematical knowledge. In the AL community, CDST has made its mark and many researchers have taken over relevant aspects for their own research, but the Gregg-adapts will beyond doubt attack this theory whenever they can. As mentioned, Paul van Geert’s scenarios for the impact of CDST in developmental psychology are equally

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relevant for AL. As a useful and easily understandable metaphor, CDST will hang on for quite some time, and there we need young and engaging researchers to carry this further. Over the years, Marjolijn Verspoor developed from a more or less traditional linguist, as evidenced by her early work on articles, to a cognitive linguist. Her work had not attracted much attention in a time when Chomsky and his followers dominated theoretical linguistics. In several of her publications, Marjolijn Verspoor has argued against the UG approach and in support of the UB one. She moved from a CL approach to an AL one. Her definition of CL and its scope are broad which makes CL suitable for many, if not all, aspects of language. The present volume brings it all together, from her link with CL through Ron Langacker’s contribution, to her dynamic usage-based approach through the contributions of her PhDs. Working with her colleagues in Groningen, she developed an interest in the development of second language writing which led to a substantial number of publications, mostly in cooperation with one of her PhDs. Her work has been well-received as evidenced by articles in the leading AL journals such as Applied Linguistics, Second Language Writing, Language Learning and The Modern Language Journal. Her interest in the application of CDST in education led to the development of the Dynamic Usage-Based approach (DUB) which is discussed in detail in several chapters in this volume. DUB made her what might be called a full applied linguist, someone who bridges the gap between research and application in education though it took some years for this approach to settle. This confirms that a late start may still lead to an admirable academic career. References Berling, I. (1979) Against the Current: Essays in the History of Science. Chicago, IL: Chicago University Press. De Bot, K. (2015) A History of Applied Linguistics 1980–2010. New York: Routledge. De Bot, K., Lowie, W.M. and Verspoor, M.H. (2007) A dynamic systems theory approach to second language acquisition. Bilingualism: Language and Cognition 10 (1), 7–21. Grant, J. (1981) A Directory of Discarded Ideas. London: Ashgrove Press. Gregg, K. (2010) Shallow draughts: Larsen-Freeman and Cameron on complexity. Second Language Research 26, 549–560. Hulstijn, J.H. (2019) An individual-differences framework for comparing nonnative with native speakers: Perspectives from BLC theory. Language Learning 69, 157–183. Kuhn, T. (1962) The Structure of Scientific Revolutions. Washington: American Association of Science. Larsen-Freeman, D. (1997) Chaos/complexity science and second language acquisition. Applied Linguistics 18 (2), 141–165. Larsen-Freeman, D. and Cameron, L. (2008) Research methodology on language development from a complex theory perspective. The Modern Language Journal 92 (4), 200–213.

xx Prologue

Lehrer, J. (2010) The truth wears off. The New Yorker 13.52, 229. National Academy of Sciences (1999) Science and Creationism: A View from the National Academy of Sciences (2nd edn). Washington, DC: The National Academies Press. Nutley, S.M., Powell, A.E. and Davies, H.T.O. (2013) What Counts as Good Evidence. London: Alliance for Useful Evidence. Schmid, M.S. (2011) Language Attrition. Cambridge: Cambridge University Press. van Geert, P. (2011) The contribution of complex dynamic systems to development. Child Development Perspectives 5 (4), 273–278.

Introduction

Usage-based accounts of (second) language development have gained ground ever since they were introduced to the scientific community of linguistics (cf. review Langacker, this volume). These accounts draw on concepts of Complex Dynamic Systems Theory (CDST; cf. LarsenFreeman, 1997, 2012, this volume) which strongly promotes a holistic approach to language development, in which any relevant component in the system is in constant interaction with the other components in the system (de Bot et al., 2007). Within complex systems, nonlinear relationships between components are constantly changing and self-organising, typically leading to alternated periods of fluctuation and stability (de Bot et al., 2007; Larsen-Freeman & Cameron, 2008). One particularly productive strand of research within CDST approaches, which lies at the heart of the current volume, adopts a dynamic perspective on second language (L2) development and L2 teaching, the so-called dynamic usage-based (DUB) account. The main tenet of this account is that language learning draws on statistical learning. In this perspective, repetitive exposure to meaningful input is a basic requirement for language development to happen (Langacker, 2000; Tomasello, 2003). Language acquisition, that is, making new form-meaning mappings, builds on associative learning established through language use. Given the emphasis on language use for learning, Verspoor (2017) proposed to expand the CDST term by adding ‘use’, that is, to conceptualise learning of constructions as building new form-use-meaning mappings (FUMMs). Language acquisition as making new FUMMs requires that constructions are ‘heard and used frequently’ which results in their entrenchment based on general principles of ‘habit formation, routinization or automatization’ (Verspoor & Schmitt, 2013: 354). Schmid (2020: 7) highlights that deeper entrenchment in turn generates more frequent use, because a form that is strongly entrenched is more likely to be activated and used with less effort than less entrenched forms. Consequently, in the context of language development, use and entrenchment are both cause and effect of each other.

1

2  Usage-Based Dynamics in Second Language Development

The notion of dynamicity within DUB approaches pertains to the realisation that language acquisition is a nonlinear process in which some subsystems are acquired before others (Langacker, 2000). In this perspective, intra- and interindividual variability in making FUMMS and variation in the use of (new) structures (including making errors), is a natural consequence of each person’s individual learning experiences. In other words, language learning trajectories are intrinsically characterised by a high degree of variability within and between learners (Verspoor, 2017). With her conceptual, empirical and pedagogical contributions, Marjolijn Verspoor has been a driving force in the investigation and implementation of DUB approaches in L2 research and pedagogy. Over the course of 15 years of research, she has published more than 30 works on the topic, of which the earliest emerged in 2004 (Verspoor et al., 2004) and many of which have become seminal contributions to the field (e.g. Verspoor et al., 2008; 2011). Building on the intellectual legacy of Marjolijn Verspoor, the aim of this edited volume is to bring together current work and thinking in the domain of DUB approaches to (second) language development. What is the field’s current state of the art and which empirical work has been and continues to be the basis for this? The volume thus presents theory and empirical work, where the empirical part clusters around three sub-themes: methodological innovation, empirical observation and pedagogical application. The chapters collectively present cutting-edge thinking in relation to both the scope of DUB theory and its applications. Reflecting the breadth of the field, the initial chapters provide a gallery of conceptual perspectives such as cognitive grammar and linguistics, thinking-for-speaking (TFS) and CDST approaches, united by their shared underpinnings of language as a dynamic system of conventionalised routines, and supported by rich empirical data. The second half of the volume showcases state-of-the-art methodologies to study dynamic trajectories of language learning, additional empirical investigations into the above-mentioned theoretical concepts and innovative classroom implementations of DUB language pedagogy. Outline of the Book

The volume opened with a prologue by Kees de Bot, a long-standing co-author of Verspoor. Focusing on the introduction of new frameworks such as CDST and DUB to long-standing theoretical and empirical traditions, he sets out how research(ers) can go about introducing a new theoretical approach and what factors play a role in deciding whether this approach survives or not. In Chapter 1, Cadierno links usage-based, cognitive-linguistic implications for language pedagogy to Dan Slobin’s idea of TFS and highlights the need to evaluate this concept for language teaching. Indeed, learning a second or foreign language (L2) entails learning alternative ways

Introduction 

3

of thinking for speaking. That is, it involves learning how a message is encoded in the lexico-grammatical resources of the L2. Cadierno uses the domain of motion to exemplify this process. The second part of Cadierno’s chapter discusses the pedagogical implications of the language theory that can clearly be characterised as a fruitful elaboration and application of the DUB framework. Murakami (Chapter  2) discusses the methodological considerations of the relatively new framework of CDST. Since CDST and DUB are essentially about change over time, process-based studies will usually take a longitudinal perspective. Murakami discusses crucial decisions at the basis of quantitative approaches that draw on corpus techniques to explore vast amounts of longitudinal L2 data. While sample size in cross-sectional group studies can be estimated with relative ease based on the power required for statistical analyses at one point in time, no such information is available to determine the required number of observations in longitudinal studies. Using a corpus of well over 2000 writings, Murakami illustrates the complexity of such an estimation, which depends on a variety of interrelated factors, including the features of the indices used to measure complexity. The longitudinal exploration of the interrelationships between various complexity dimensions in L2 learners’ performance is extended as part of Chapter 3 (Bulté and Housen). The results of a two-year study of 10 L2 learners reveal a high degree of variability, both within and across learners, and show that different complexity dimensions do not develop in parallel and may even enter into competitive relationships. Very much in line with Murakami’s conclusions, Bulté and Housen’s findings demonstrate the importance of including multiple complexity dimensions in the analyses of L2 development in order to obtain a full and comprehensive picture of the developmental process. The chapter by Peng, Jager, Thorne and Lowie (Chapter 4) focuses on learning outside of the classroom. Taking a person-centred approach to L2 learning as an important requirement of DUB studies, this chapter discusses how different learners make use of diverse and multiple technological learning resources that articulate with their personal goals, learning interests and preferences, prior knowledge and language and digital competencies. Using an empirical example of a clustering approach to analyse learning experiences mediated by mobile technologies, this chapter elucidates how the application of person-centred methods can help to advance our understanding of complex phenomena in L2 development. It shows that although the developmental trajectory may be strongly individual, it is still useful to portray learner clusters that emerge from the data. The theoretical perspective of a person-centred approach to L2 development is also the foundation of the study described in Chapter 5, where Eskildsen reports on the qualitative analysis of usage-driven creativity

4  Usage-Based Dynamics in Second Language Development

and routinisation over time in L2 English. Adopting the trace-back methodology from child language studies to L2 data, Eskildsen’s work reveals that the syntactic operations identified in children, most notably the substitution of semantically similar items in open slots in recurring constructions (e.g. ‘I got the …’), also apply to beginning adult L2 learners. Using a longitudinal analysis of a single learner, the chapter demonstrates how contextualised activities have an impact on the dynamic development of creativity and routinisation in L2 acquisition. In Chapter  6, Wind and Harding also provide in-depth qualitative explorations of dynamic changes of L2 performance in an L2 writing case study. Different from the more methodological orientation of the preceding chapters, Wind and Harding focus on the theoretical understanding of the emergence of salient attractor states in the development of the linguistic and motivational systems of the L2 learner. Their qualitative analysis resulted in the finding that the student’s motivational system resided in an attractor state related to boredom, frustration and low selfefficacy belief, which may have influenced the stability in his linguistic system. The empirical observations in this study thus illustrate the complex interaction of linguistic and non-linguistic subsystems discussed in the theoretical orientation of the volume. In Chapter  7, MacIntyre and Ayers-Glassey also take a dynamic approach to language development, as they offer a conceptualisation of the changing nature of competence appraisals in L2 learning. Even as speakers assemble and deliver their message, a self-evaluation of competence occurs continuously, integrated with the process of deciding what to say and how to say it. In this chapter, MacIntyre and Ayers-Glassey show that the explanation of the development of a concept draws on Complex Dynamic Systems Theory, Action-Assembly Theory and Stimulus Appraisal Theory. Very much in line with a DUB approach to language development, they use CDST as a meta-theoretical and multidimensional perspective to account for continuous ebbs and flows in the development of the learner’s communication processes. Sulis, Davidson and Michel (Chapter 8) focus on fluctuations in motivation and willingness to communicate (WTC) in L2 learning, as observed in an authentic L2 classroom context. Taking a micro-perspective, this chapter investigates the dynamic changes and interrelationship of motivation and WTC over the course of two 45-minute lessons. Findings show that self-confidence, individual involvement and the social relationships within the classroom played a crucial role in providing favourable conditions for both high motivation and WTC. The study concludes by discussing directions for future research and formulating implications for the L2 classroom. In Chapter  9, Langacker presents his theoretical take on construction grammar by example of locative constructions. Langacker discusses how the occurrence of nested locative constructions in English (e.g. The report is in the study, on my desk, in a folder) illustrates the dynamic

Introduction 

5

nature of linguistic structures. The chapter also shows the iconicity of language, the characterisation of which hinges on correct identification of the linguistic and ‘extralinguistic’ structures involved and the nature of their relationship. This discussion emphasises the relevance of the cognitive linguistic (CL) foundation of a DUB approach to language learning, showing that linguistic and extralinguistic structures cannot be fundamentally distinguished. Accordingly, the models and theories of language learning discussed elsewhere in the book constitute a logical reflection of the dynamic and iconic characteristics of language itself. In Chapter 10, Tyler, Jan, Mahpeykar and Tullock bring the chapters full circle by revisiting the CL orientation that forms the central underlying building block of the volume. The authors report on an original classroom application study targeting the specific linguistic structures of English phrasal verbs. This study is a direct application of the role of CL structures as described in Chapter 9. The difficulty of learning L2 constructions is approached from the perspective of linguistic regularity. Based on the CL conceptualisation of meaning that is at the centre of language, and while acknowledging its usage-based nature, the study uses theoretical insights provided by CL to show how language learning is characterised by discovering systematicity. Despite the seemingly arbitrary nature of phrasal verbs, the linguistic analysis worked out in this chapter elucidates the learnability of such phrasal verbs. Inspired by the DUB conceptualisation of (statistical) learning as an effect of use, characterised as ‘implicit’ learning, Piggott, Tribushinina and de Graaff (Chapter  11) report on their studies of the classroom setting of L2 learning in which they investigate the optimal type of instruction provided by the teacher. As part of an intervention study, they compared a setting of explicit form-focused instruction (FFI) to a setting that initially focused on implicit meaning-focused instruction followed by delayed short-term explicit grammar instruction. The results tentatively indicate that the importance of continuous grammar instruction is overrated and that – following a period of implicit FFI – only minimal explicitness and practice is sufficient to score well on a common grammar test. On top of these observations of the classroom setting and inspired by Marjolijn Verspoor’s work, Kassenberg, Galati, de Vries-Zhuravleva and Menke-Bazhutkina (Chapter  12) show how DUB insights on language learning can be translated into a practical teaching approach using film materials in the classroom. Film and language integrated learning (FLIL) is scaffolded through repetition to optimally support the learning process, by creating authentic, contextualised target language input following DUB principles. The success of this approach shows the value of this type of DUB-inspired L2 instruction. Finally, the epilogue by Larsen-Freeman draws important conclusions and provides directions for future research on the provided realm of DUB approaches, both in terms of theory and application.

6  Usage-Based Dynamics in Second Language Development

Given its state-of-the-art nature, currency and comprehensiveness, we believe this book transcends extant volumes on usage-based dynamics (e.g. Verspoor et al., 2011), and we believe it signifies DUB as a landmark in the field of L2 research for years to come. As the editorial team of this volume, we are immensely grateful for the speedy and enthusiastic collaboration of a distinctive assembly of colleagues who represent all layers of scholars in the dynamic field of applied linguistics, from practitioners and PhD students to the most eminent members of our field of research. The exceptional willingness to contribute to this volume can only be explained by its unique occasion. It is a great honour to dedicate this volume to Marjolijn Verspoor, whose work has been a considerable source of inspiration for all of the contributors to this volume. Every aspect of this book, from CL theory to theories of L2 development, and from indepth empirical investigations to innovative teaching applications, all are founded on Marjolijn’s inexhaustible source of ideas, initiatives and inspiration, perhaps best characterised as a DUB dynamo. Wander Lowie, Marije Michel, Audrey Rousse-Malpat, Merel Keijzer, Rasmus Steinkrauss (editors) References De Bot, K., Lowie, W.M. and Verspoor, M.H. (2007) A dynamic systems theory approach to second language acquisition. Bilingualism: Language and Cognition 10 (1), 7–21. Langacker, R.W. (2000) A dynamic usage based model. In M. Barlow and S. Kemmer (eds) Usage-Based Models of Language (pp. 1–63). Stanford, CA: CSLI. Larsen-Freeman, D. (1997) Chaos/complexity science and second language acquisition. Applied Linguistics 18 (2), 141–165. Larsen-Freeman, D. (2012) Complex, dynamic systems: A new transdisciplinary theme for applied linguistics? Language Teaching 45 (2), 202–214. Larsen-Freeman, D. and Cameron, L. (2008) Complex Systems and Applied Linguistics. Oxford: Oxford University Press. Schmid, H.-J. (2020) The Dynamics of the Linguistic System. Usage, Conventionalization, and Entrenchment. Oxford: Oxford University Press. Tomasello, M. (2003) Constructing a Language: A Usage-Based Theory of Language Acquisition. Cambridge, MA: Harvard University Press. Verspoor, M.H. (2017) Complex Dynamic Systems Theory and L2 pedagogy: Lessons to be learned. In L. Ortega and Z. Han (eds) Complexity Theory and Language Development (pp. 143–162). Amsterdam/Philadelphia, PA: Benjamins. Verspoor, M.H. and Schmitt, N. (2013) Language and the lexicon in SLA. In P. Robinson (ed.) The Routledge Encyclopedia of Second Language Acquisition (pp. 353–360). New York/London: Routledge. Verspoor, M.H., De Bot, K. and Lowie, W.M. (2004) Dynamic Systems Theory and variation: A case study in L2 writing. In R. Lyall (ed.) Words in Their Places. A Festschrift for J. Lachlan Mackenzie (pp. 407–421). Amsterdam: Free University Press. Verspoor, M.H., Lowie, W.M. and Van Dijk, M. (2008) Variability in second language development from a dynamic systems perspective. Modern Language Journal 92 (2), 214–232. Verspoor, M.H., De Bot, K. and Lowie, W.M. (2011) A Dynamic Systems Approach to Second Language Development: Methods and Techniques. Amsterdam/Philadelphia, PA: Benjamins.

1 Thinking for Speaking in an L2: From Research Findings to Pedagogical Implications Teresa Cadierno

Since its formulation in the 1990s, Slobin’s thinking-for-speaking (TFS) hypothesis has gained increasing attention in the field of second language acquisition (SLA) (e.g. Cadierno, 2008a; Han & Cadierno, 2010; Pavlenko, 2011). Under this perspective, learning a second/foreign language (L2) entails learning alternative ways of thinking for speaking (Cadierno, 2004) or learning to re-think for speaking (Robinson & Ellis, 2008), i.e. learning the particular vebalized orientation to experience encoded in the lexico-grammatical resources of the L2. This chapter is divided into two main parts. The first part discusses the implications of TFS for the process of L2 learning, and outlines some of the main findings in this research area, with particular emphasis on the domain that has received most attention in the literature, i.e. that of motion. L2 studies that examine language-specific effects on linguistic encoding and that deal with both voluntary/spontaneous and caused motion are considered. The second part discusses the pedagogical implications of these findings, and reviews some recent intervention studies that have combined insights from TFS research and different L2 pedagogical approaches. Introduction1

In the last decade and a half there has been an increased interest in applying usage-based/cognitive linguistics accounts of language and language learning to the field of second/foreign language acquisition and teaching (e.g. Achard & Niemeier, 2004; Boers & Lindstromberg, 2008; Cadierno & Eskildsen, 2015; De Knop & De Rycker, 2008; Ellis & Cadierno, 2009; Littlemore, 2009; Ortega & Tyler, 2016; Piquer-Píriz & Alejo-González, 2018; Robinson & Ellis, 2008; Tyler et  al., 2018a, 2018b). In addition to the dynamic usage-based (DUB) account pioneered 7

8  Usage-Based Dynamics in Second Language Development

by Marjolijn Verspoor, Kees de Bot and Wander Lowie, another theoretical framework that has attracted a great deal of attention in this field is Slobin’s thinking for speaking (TFS) hypothesis (e.g. Cadierno, 2008a; Han & Cadierno, 2010; Pavlenko, 2011). Under this perspective, learning a second/foreign language (L2) entails learning alternative ways of TFS (Cadierno, 2004) or learning to re-think for speaking (Robinson & Ellis, 2008), i.e. learning the particular verbalised orientation to experience encoded in the lexico-grammatical resources of the L2. As stated in the introduction to the present volume, the DUB account of language development and the TFS hypothesis share a common understanding of language as a dynamic system of conventionalized units. More specifically, both share a common view of language and language acquisition that is grounded in usage-based/cognitive linguistics perspectives (e.g. Langacker, 1987; Tomasello, 2003). Regarding the former, both approaches view language as consisting of conventionalized units or form-meaning pairings used for communication purposes. An important implication of this language view is the centrality of meaning in linguistic descriptions, which is at the heart of DUB- and TFS-inspired research. Regarding the latter, both approaches view language learning as usage based, i.e. as emerging from language usage in particular contexts. Furthermore, both approaches view language development as dynamic in nature, even though this aspect of language acquisition has had a more central and visible role in the DUB approach. As suggested by its name, L2 DUB-inspired research has focused on examining learners’ language development systems over time by means of longitudinal studies, and has scrutinized the role of learner-internal (e.g. conceptual knowledge, motivational resources) and external (e.g. time invested in learning, the language used by the environment) resources in language development, and the variability that characterizes it (e.g. De Bot et al., 2007). L2 TFSinspired research also assumes that the process of learning L2-appropriate TFS patterns is dynamic and influenced by learner-internal and external factors; however, the cross-sectional design of most research conducted under this approach has not allowed for a detailed documentation of the dynamic nature of TFS developmental patterns within single individuals (but see e.g. Li et al., 2014; Stam, 2010). This chapter is divided into two main parts. The first part provides a brief account of the TFS hypothesis and its empirical basis, discusses the implications of TFS for the process of L2 learning and outlines some of the main findings in this research area, with particular emphasis on the domain that has received most attention in the literature, i.e. that of motion. L2 studies that examine language-specific effects on linguistic encoding, and that deal with both voluntary/spontaneous and caused motion are considered. The second part of the chapter discusses the pedagogical implications of these findings, and reviews recent intervention studies that have examined the effects of instruction on second/foreign

Thinking for Speaking in an L2  9

(L2) learners’ development of appropriate L2 TFS patterns. These studies have combined insights from TFS-inspired research and different L2 pedagogical approaches. Thinking for Speaking: What is It and What Empirical Evidence is There for It?

The TFS hypothesis proposed by Slobin (1991, 1996) is concerned with the possible effects of language on the kind of thinking that takes place online when engaged in language-mediated activities. The main idea underlying TFS is that the structure of a language channels the attention of its speakers to specific aspects of experience when talking about them. Each language thus ‘invites’ its speakers to adopt a given perspective on events and experiences when talking about them. As a result, speakers typically attend to and verbalize those characteristics of objects and events that are readily codable in their language, and, over time, this repeated attention leads to particular rhetorical styles. As expressed by Slobin (1996: 76), ‘In the evanescent time frame of constructing utterances in discourse, one fits one’s thoughts into available linguistic forms. Thinking for speaking involves picking those characteristics that (a) fit some conceptualization of the event, and (b) are readily encodable in the language’. The TFS hypothesis has received empirical support from studies examining the expression of motion in discourse by native speakers (NSs) of different languages. Motion is a semantic domain that is important in all languages and one where differences in conceptual representations between languages can be found (Jarvis & Pavlenko, 2008). Most of this crosslinguistic work on motion has been based on Talmy’s (1985, 1991, 2000) well-known typological framework, which involves the systematic relations in language between meaning and surface expression. According to Talmy, there are two main lexicalization patterns in the expression of motion events in different languages of the world. In satellite-framed languages (S-languages), which include all the Indo-European languages except for the Romance languages, the main verb tends to express Motion and Manner of motion, while Path tends to be encoded in the so-called satellites, which are defined as those elements that appear outside the verb and are not nominal or prepositional phrases, such as particles and affixes. The following expression illustrates this pattern of lexicalization: The bottle floated out of the cave, where the verb float expresses Motion and Manner of motion and the satellite out encodes Path. On the other hand, in verb-framed languages (V-languages), which include Romance and Semitic languages, the main verb tends to express Motion and Path while Manner of motion tends to be encoded in a separate constituent such as a gerund or prepositional clause. For example, La botella salió de la cueva flotando, where the verb salir expresses Motion and Path and the gerund flotando encodes Manner of motion.

10  Usage-Based Dynamics in Second Language Development

However, in order to provide a more accurate description of the typological patterns of the two types of languages, we need to take into account the so-called boundary-crossing constraint (Aske, 1989; Slobin & Hoiting, 1994). This constraint refers to whether or not a given Path involves the crossing of a spatial boundary. Boundary-crossing situations are those where the initial and final points (locations) of movement take place in two different spaces. In S-languages, the main verb can express Manner of motion in both +/– BC situations (e.g. +BC: He ran into the house; –BC: He ran towards the house), while in V-languages, Manner of motion can only be expressed in the main verb in –BC situations (e.g. Corrió hasta la casa [He/she ran to the house (without entering)]). In +BC situations, Manner must be encoded outside the main verb, for instance in a gerund as in Entró en la casa corriendo [He/she entered the house running]. This is due to the fact that crossing a spatial boundary is conceived as a change of state, and this change in V-languages has to be encoded in the verb (e.g. subir ‘go up’, bajar ‘go down’ or cruzar ‘cross’) in contrast to S-languages in which the change of state can be expressed in a satellite (e.g. up, down, across) (Aske 1989). Research conducted on the expression of motion has shown differences in how NSs of typologically different languages talk about motion (e.g. Berman & Slobin, 1994; Slobin, 1996, 1997, 1998, 2000, 2003, 2004, 2006). Generally, this research has shown a greater degree of elaboration of the semantic component of Path by speakers of S-languages. Speakers of these languages tend to provide more elaborated and tightly packaged descriptions of paths within a clause than speakers of V-languages, who, in contrast, tend to provide static descriptions of the static scene in which the movement took place to serve as a backdrop for the Path and Manner information. In addition, speakers of S-languages provide more elaborated manner descriptions than speakers of V-languages, an elaboration that is reflected both in terms of the frequency with which the manner information is supplied and in terms of the manner distinctions that are made (see Cadierno [2017] for a more detailed account of these results). Studies conducted in the 2000s (e.g. Strömqvist & Verhoeven, 2004) have further revealed the existence of intra-typological differences within the same language type, in both S-languages (e.g. between Icelandic and Swedish in Ragnasdottir and Strömqvist [2004] or between Serbian and English in Filipović [2007]) and V-languages (e.g. between Tzeltal and Spanish in Brown [2004] and between Basque and Spanish in IbarretxeAntuñano [2004]). The existence of these intra-typological differences in the expression of both Path and Manner have prompted some authors (Ibarretxe-Antuñano, 2004, 2009; Slobin, 2004, 2006) to propose scales or continua of ‘salience’. Languages with high Manner or Path salience are those that have a high level of encoding and frequent use of the semantic component in question, while languages with a low salience are those with few encoding resources and infrequent use of the semantic component

Thinking for Speaking in an L2  11

in question. In other words, a direct relationship is proposed between the encoding of a semantic component and the linguistic resources of languages to express it: the greater the number and variety of linguistic resources, the greater the likelihood that a language encodes the semantic component and occupies a higher place on the scale of salience (IbarretxeAntuñano, 2009). Also observed was the importance of examining gestures in combination with speech when examining the TFS patterns in different languages. McNeill and colleagues (e.g. McNeill, 1992, 2000; McNeill & Duncan, 2000) found differences between speakers of S- and V-languages in the synchronization of gestures and speech. In V-languages, gestures that expressed Path were synchronized with the verb that encodes Path, Ground or a combination of both, while in S-languages, gestures that expressed Path were synchronized with the satellite, Ground or a combination of both. In terms of the expression of Manner, speakers of V-languages tended to use gestures that encode this semantic component in the absence of the expression of Manner in speech, a phenomenon that has been named manner fog (but see Gullberg [2009a, 2011] for contradictory findings). In contrast, in S-languages, gestures that expressed Manner were used as an element to modulate it. This modulation can help reinforce the information of Manner in cases where it is important for communication (in this case the gesture of Manner is synchronized with the manner verb) or to minimized it in cases where the information of Manner is less important. In this last case, speakers of S-languages tended to express Manner in speech and Path in gesture. Differences were also observed in the form and content of the gestures and in the way in which motion semantic components are packaged (e.g. Özyürek, 2002; Stam, 2006). Speakers of V-languages tended to produce gestures that express Path and Manner in separate clauses whereas speakers of S-languages tended to package Path and Manner in one single gesture. For example, when speakers of V-languages produce an utterance such as El gato rueda calle abajo (Lit: ‘the cat rolls the street down’), the gesture of rolling and the gesture of downward motion tend to be produced separately. In contrast, when speakers of S-languages produce the utterance The cat rolls down the street, a single gesture combines the expression of rolling and downward movement. These results have clear implications for language acquisition. According to Slobin (1996), language acquisition involves the development of language-specific forms of thinking or TFS patterns. As expressed in Berman and Slobin (1994: 611), ‘in becoming a native speaker of a given language, the child learns to attend to particular aspects of experience and to relate them verbally in ways that are characteristic of that language. Becoming a native speaker thus … requires attention to the grammaticized semantic distinctions of the language and to the ways in which grammatical forms are deployed in the construction of connected discourse’. Each language thus trains its NSs to pay different kinds of attention to particular details when engaged in language activities, and

12  Usage-Based Dynamics in Second Language Development

this training that is carried out during childhood could be resistant to restructuring in adult learning of an L2. Thinking for Speaking and Second Language Learning

Slobin’s TFS has important implications for adult second language acquisition (SLA). Under this perspective, L2 learning involves developing alternative ways of TFS (Cadierno, 2004, 2008a) or learning to ‘rethink for speaking’ (Robinson & Ellis, 2008), that is, learning the ways in which the NSs of the L2 categorize and construe the world and thus learn the particular verbalized orientation to experience encoded in the lexicogrammatical resources of the L2 (Ellis & Cadierno, 2009). In recent years, research on TFS in an L2 has increased exponentially, as exemplified in recent books by Jarvis and Pavlenko (2008), Han and Cadierno (2010), Pavlenko (2011, 2014) and Cook and Bassetti (2011). In addition to these volumes, special issues of journals have been dedicated to issues related to TFS (Benazzo et al., 2012; Bylund & Athanasopoulos, 2015; Jarvis, 2011). Why is this the case? Why have Slobin’s TFS hypothesis and Talmy’s typological framework had such a strong influence on SLA research? I believe that an important reason is their focus on crosslinguistic variation. As reviewed above, studies conducted on the expression of motion by NSs of different languages have evidenced both inter- and intratypological differences with respect to both speech and gesture. The existence of these differences has enabled SLA researchers to develop a ‘modern’ and empirically based account of ‘contrastive analysis’ (CA): an account that is based on a usage-based approach to language acquisition rather than the behaviourist one that was behind the traditional contrastive analyses carried out in the 1950s and 1960s; and an account which is based on a semantically-based type of linguistic analysis rather than the structurally-based type of analysis that characterized traditional CA. Furthermore, Slobin’s TFS hypothesis and Talmy’s typological framework have also enabled SLA researchers to adopt a new perspective on the phenomenon of crosslinguistic influence (CLI) that goes beyond the formal aspects of language and examines CLI at the conceptual level. Work conducted under the TFS framework and under what has been referred to as conceptual transfer by Jarvis (2011) and Jarvis and Pavlenko (2008) is concerned with examining the influence of learners’ first language (L1) conceptualization patterns on their L2.2 Research conducted in the area of TFS and L2 learning has attempted to answer three main research questions: (1) Are adult learners of an L2 able to learn the L2 TFS patterns (in verbal and gestural expression)?; (2) To what extent is this learning influenced by the L1 TFS patterns (in verbal and gestural expression)?; and (3) Can learners’ L2 influence the already established L1 TFS patterns (in verbal and gestural expression)?

Thinking for Speaking in an L2  13

Most of this work has been conducted in the domain of motion events, but studies have also examined other domains (see Jarvis & Pavlenko [2008] and Pavlenko [2014] for recent overviews), such as grammatical gender (e.g. Boroditsky et al., 2003; Dewaele & Veronique, 2001); grammatical number (e.g. Cook et al., 2006; Han, 2010); time (e.g. Alloway & Corley, 2004; Pavlenko & Diagrina, 2006); definiteness (Ekiert, 2010; Han, 2010); emotion (e.g. Pavlenko, 2005; Pavlenko & Diagrina, 2007); objects (e.g. Malt & Pavlenko, 2011); and colour (e.g. Athanasopoulos, 2009). In addition, considerable research has been conducted on the role of grammatical gender in motion event construal and information structure by advanced L2 learners of different languages. This line of research, initiated by von Stutterheim and colleagues (e.g. Carroll & von Stutterheim, 2003; Carroll et al., 2004; von Stutterheim & Carroll, 2006), has shown that speakers of non-aspect languages such as German are more likely to present motion events holistically, i.e. as bounded, and thus encode event endpoints, whereas speakers of aspect languages such as English tend to present the events as ongoing, i.e. as unbounded, and thus omit endpoints. Research conducted on advanced L2 learners under this perspective has shown that L2 learners, even at advanced stages, draw on L1 principles when construing reportable content. For example, L1 English learners of L2 German mentioned endpoints less frequently than German NSs, thus following their L1 characteristic pattern. And conversely, L1 German learners of L2 English tended to mention endpoints more frequently than English NSs. On the basis of these and otherrelated results, von Stutterheim and Carroll (2006: 51) concluded that ‘the central factor impeding the acquisitional process at advanced stages ultimately is grammatical in nature, in that learners have to uncover the role accorded to grammaticized meanings and what their presence, or absence, entails in information organization’. These results have been interpreted as providing support for the possible influence of languagespecific planning processes at the conceptualizer stage of Levelt’s (1989) model of speech production. Research conducted on the expression of motion on the basis of Talmy’s (1985, 1991, 2000) typological framework has also shown adult L2 learners’ difficulties in learning to re-think for speaking in an L2. These difficulties can be summarized into five main points.3 The first is that the influence of the learner’s L1 TFS on the L2 occurs independently of the typological directionality of the learner’s L1 and L2. Thus, learners with an L1 S-language and an L2 V-language have shown a greater elaboration of Path than the NSs of the target language. For example, Cadierno (2004) and Cadierno and Ruiz (2006) observed the phenomenon of ‘satellization’ in intermediate learners with Danish as an L1 and Spanish as an L2. Satellization refers to the use of redundant Path adverbs used with non-directional verbs of motion (e.g. El niño fue arriba de una roca ‘the boy went on top of a rock’ or El ciervo lo movió abajo al perro

14  Usage-Based Dynamics in Second Language Development

y al niño ‘the deer moved down the dog and the boy’). Difficulties with the expression of Path were also found in a study of English-speaking intermediate learners of L2 Spanish by Muñoz Carrasco (2015). When asked to describe a series of videos with Mr Bean, compact expressions such as the following were documented: La pelota de golf salta sobre el banco, encima de la valla y en el autobus ‘The golf ball jumps over the bench, over the fence and into the bus’. As noted above, this type of compact expression is characteristic of English but not Spanish. Therefore, learners are following a pattern that is typical of their L1 (i.e. the accumulation of various path segments within a clause and with a single verb) when providing spatial descriptions in their L2. Regarding the expression of Manner, learners with an L1 S-language and an L2 V-language have also been documented to experience difficulties when describing motion events that express boundary crossing. Larrañaga et al. (2011) found that L1 English learners of L2 Spanish with three levels of linguistic proficiency – beginners, intermediate and advanced – tended to amalgamate the expression of Motion and Manner in the main verb, a pattern that is not possible in Spanish, but possible in English. Additionally, it has been observed that, because these learners are habitually used to expressing Manner in their L1, they may seek ways to express it in their L2 through gestures (e.g. Choi & Lantolf, 2008; Negueruela et al., 2004). Learners who have to make the reverse transition, that is, those who have an L1 V-language and an L2 S-language, also experience difficulties when learning to re-think for speaking in their L2. For example, Carroll et  al. (2012) observed that advanced French learners of L2 English and German were unable to produce dynamic verbalizations of the trajectories in the same way as NSs. When describing spatial scenes showing a car driving along a road, learners tended to use locative expressions such as A car is driving on a road, expressions that were also frequently used by French NSs. The researchers concluded that learners were unable to pay attention to and verbalize the concepts referred to as Ground (as in English around, along, through) which are typically expressed in S-languages. Regarding the expression of Manner, Cadierno’s (2010) study found that Spanish learners of L2 Danish tended to use ‘basic level’ verbs (e.g. løbe ‘run’, gå ‘walk’) rather than more specific manner verbs when describing boundary-crossing motion scenes, a pattern that was not observed to the same extent in learners with L1 S-languages. Similarly, learning difficulties have been observed in merging Manner and Path information into a single gesture. For instance, Özyürek (2002) found that Turkish learners of L2 English tended to express Path and Manner in separate clauses and performed separate gestures of Path and Manner when speaking English, thus following the predominant pattern of their L1. A second result of the investigations, already advanced in the previous point, is that the influence of the L1 TFS patterns in the L2 has not only been observed in learners’ speech but also in their gestures.

Thinking for Speaking in an L2  15

Kellerman and van Hoof (2003) coined the term ‘manual accent’ to describe advanced learners whose foreign language is (almost) perfect at a linguistic level while their gestures follow the L1 patterns. These authors found that Spanish learners of L2 English tended to synchronize the gestures that expressed Path with the main verb (which also expressed Path) and therefore followed the same gestural pattern of Spanish NSs. A third result of the existing research is that difficulties in learning to re-think for speaking are not only experienced by learners whose L1 and L2 are typologically different. Learners with intra-typological differences between their L1 and L2 also have difficulties in ‘re-thinking for speaking’ about motion in an L2, even at advanced levels of linguistic proficiency. For example, in a study of three groups of learners with Danish as an L2, Cadierno (2010) found that German and Russian learners of L2 Danish differed significantly in a receptive vocabulary task. German learners were able to recognize a greater number of manner verbs than Russian learners, a result that was attributed to the greater degree of similarity between the lexicon of verbs of motion in Danish and German, which are both Germanic languages. The importance of intra-typological differences was also observed in two studies by Hasko (2009, 2010), which were conducted with English learners of L2 Russian. Russian has a series of manner verbs that express unidirectionality or non-unidirectionality. For example, the verb idu expresses unidirectionality in the sentence Nu vot, idu ia po ulitse Gor’kogo ‘So, I am walking down Gorky Street’, while the verb khozhu expresses non-unidirectionality in the sentence Khozhu ia znakomymi zakoulkami po liubimom tsentru ‘I am walking up and down familiar backstreets in my favorite city center’. Hasko (2009, 2010) found that learners had great difficulty in differentiating between these two types of verbs in L2 Russian, probably due to the fact that this distinction is non-existent in their L1. Finally, in a study on the expression of motion in L2 Spanish by L1 learners of German, French and Italian, Hijazo-Gascón (2011) found that NSs of Italian expressed a greater amount of Grounds in their mother tongue than speakers of other Romance languages and they continued to follow the same pattern when providing spatial descriptions in L2 Spanish. That is, the same Italian speakers produced a greater amount of Grounds in L2 Spanish vis-à-vis French and Spanish NSs. A fourth result of the existing research is that CLI occurs not only from the learner’s L1 to their L2, but also from their L2 to their L1. The existence of bidirectional influence has been documented in intermediate and advanced L2 learners. For example, Brown and Gullberg (2008, 2010, 2011, 2012) investigated the expression of motion in the speech and gestures of Japanese learners of L2 English (intermediate level) and found that their verbal and gestural expression of Manner was similar in their L1 and L2, but different from that of the NSs of these two languages. In terms of speech, learners expressed Manner more frequently

16  Usage-Based Dynamics in Second Language Development

than NSs of Japanese but less frequently than NSs of English. In terms of gestural expression, the two authors found that learners used modulation to minimize Manner (expression of Manner in speech but not in gestures) to a greater degree than NSs of Japanese but less than NSs of English. According to the authors, these results suggest the existence of convergence between the conceptual patterns of the learner’s L1 and L2 (Pavlenko, 1999, 2005, 2014), that is, the creation of a pattern that is different to the one used by monolingual speakers of each language. In a recent study, Muñoz and Cadierno (2019) found that, when compared to English NSs with no knowledge of Spanish, upper intermediate English learners of L2 Spanish (but not learners with lower L2 proficiency levels) used more Path verbs when describing non-boundary-crossing motion events in their L1 English. These findings suggest that the higher a learner’s level of L2 proficiency, the stronger the influence of the L2 on the L1. In addition, they provide empirical support for Grosjean’s (1992) notion that a bilingual speaker does not correspond to the sum of two monolingual speakers in one head, and for Cook’s (1992) notion of ‘multicompetence’, according to which the competences of a bilingual or multilingual speaker are not the same as those of a monolingual speaker; nor do they have to be. A final finding worth mentioning is that the development of L2-appropriate patterns is not uniform within single L2 learners. More advanced L2 learners are able to develop some L2-appropriate patterns but this is not necessarily true for all aspects of a motion event. For example, Cadierno (2004) and Cadierno and Ruiz (2006) found that Danish learners of L2 Spanish paid appropriate linguistic attention to static scenes, whereas they showed instances of satellization in the expression of Path. Similarly, Choi and Lantolf (2008) found that English learners of L2 Korean expressed Path appropriately, but not Manner. The findings reported above concern the expression of voluntary motion, which is the type of motion that has been most widely investigated in the literature. More recently, however, researchers have begun paying attention to the expression of caused motion by L2 learners, and more specifically, the expression of placement events. Following Talmy (1985, 2000), placement events are those in which an agent causes an object to move to a given location in space, as in The woman puts the candle into a candle stand. Studying the expression of placement events in an L2 is interesting due to the documented crosslinguistic variation in the linguistic conceptualization of this domain by NSs of different languages. For example, differences have been observed with respect to the lexical semantics of verbs. Languages like Spanish have a generalpurpose ‘putting’ verb that applies to a wide range of scenes – poner ‘put’ or dejar ‘leave’ – (Ibarretxe-Antuñano, 2012) whereas Swedish has posture verbs that express properties of the Figure object and its orientation with respect to the Ground – sätta ‘set’, ställa ‘stand’ and lägga ‘lay’

Thinking for Speaking in an L2  17

– (Gullberg & Burenhult, 2012). Other languages like English have both a general verb – put – that is more widely used and a set of positional verbs – set, lay, stand – generally used for contrastive and pragmatically motivated reasons (Gullberg, 2011). Research on the expression of placement events by adult L2 learners has examined how adult L2 learners reconstruct the meaning of L2 placement verbs when moving from a more general system – with one general L1 verb – to a more specific system – with two or more caused posture verbs – (e.g. Gullberg, 2009a; Viberg, 1998) or when moving in the opposite direction, i.e. from a more specific system to a more general one (e.g. Gullberg, 2009b, 2011). Whereas these studies examined the relative difficulty of the direction of the transition in separate studies involving different combinations of L1 and L2 language pairs, Cadierno et al. (2016) investigated verb meaning reconstruction by means of a bidirectional design incorporating learners who had to move from a more general system to a more specific one (i.e. intermediate Spanish learners of L2 Danish) and learners who had to move from a more specific system to a more general one (i.e. intermediate Danish learners of L2 Spanish). The results of this study showed learning difficulties for both groups, irrespective of the type of transition to be made. In line with previous findings (e.g. Gullberg, 2009b; Viberg, 1998), both groups overgeneralized one or two verbs. Spanish learners of L2 Danish overgeneralized the Danish verb lægge ‘lay’ for vertical placement (e.g. Put cup on table) and the verb sætte ‘set’ for tight-fit containment (e.g. Put head into bucket). Danish learners of L2 Spanish generalized the Spanish verb poner ‘put’ for all types of placement scenes. These results show that even when learners used the same verbs as L1 speakers, they did not use them in the same way, i.e. they were not able to use the appropriate verbs for L2-relevant semantic distinctions. In sum, research into the expression of both voluntary and caused motion indicates that learners at different levels of L2 proficiency experience difficulties in the process of re-thinking for speaking. These results can be interpreted as providing support for Kellerman’s (1995) ‘transfer to nowhere principle’, which is concerned with differences in how languages may predispose speakers to conceptualize experience in verbally specific ways. That is, when verbalizing events in an L2, learners may use the linguistic tools that allow them to maintain their L1 perspective. This use is based on an unconscious assumption on the part of the learner that ‘the way we talk or write about experience is not something that is subject to between-language variation’ (Kellerman, 1995: 141). In other words, learners may not be aware of the crosslinguistic differences between their L1 and L2 in relation to TFS patterns. If this is the case, learners may benefit from pedagogical interventions that explicitly focus on the development of appropriate L2 TFS patterns, an issue that is discussed in the following section.

18  Usage-Based Dynamics in Second Language Development

Thinking for Speaking: Pedagogical Implications

Given learners’ documented difficulties with L2 re-thinking for speaking and given their possible lack of awareness of crosslinguistic differences in this respect, directing learners’ attention towards this language dimension may be necessary. As formulated by Ellis (1992: 175), even though ‘… the real stuff of language acquisition is the slow acquisition of form-function mappings and the regularities therein… without any focus on form or consciousness raising…, formal accuracy is an unlikely result; relations that are not salient or essential for understanding the meaning of an utterance are otherwise only picked up very slowly, if at all…’. In line with this argumentation, several authors have advocated the usefulness of providing learners with explicit instruction (e.g. Cadierno, 2008b; Ellis & Cadierno, 2009; Norris & Ortega, 2000; Treffers-Daller & Tidball, 2015). The development of L2-appropriate TFS patterns is a relatively neglected area in foreign language classrooms (Cadierno, 2008b). Attwood (2014) examined 35 textbooks used for teaching English in the UK and found that attention to manner verbs and path satellites was scant, and that, when attention was given, emphasis was placed on the lexical meaning of the verb and not on the challenges involved in processing the entire motion event. In line with these suggestions, the last years have witnessed the appearance of several intervention studies examining the effects of explicit instruction on learners’ development of appropriate L2 TFS patterns. These studies have combined insights from TFS research and different L2 pedagogical approaches: Lindstromberg and Boers (2005) and Elliott and Yountchi (2009) used Total Physical Response (TPR); Attwood (2017) employed processing instruction; and Evans (2015) and Stam et  al. (2017) used concept-based instruction. An alternative approach was followed by Cadierno and Robinson (2009), who used the insights from TFS in the design of pedagogic tasks for the classroom. All the studies were concerned with the expression of voluntary motion and targeted learners of L2 S-framed languages. Overall, the results of these studies are promising. Lindstromberg and Boers (2005) investigated the effect of TPR (i.e. teaching language via physical activity) on L1 Dutch learners’ understanding and brief retention of L2 English manner of motion verbs. The study included an experimental group where learners were asked to enact the meaning of verbs to each other, and a control group where learners were asked to convey the meaning of verbs verbally. The results of the study showed a significant advantage for the experimental group, i.e. enacting was superior to verbal explanations. In addition, within the experimental group, those learners who invested effort in demonstrating verb meanings were significantly better than those who merely attended to physical demonstration. According to the authors, this learning effect may be due to an increase

Thinking for Speaking in an L2  19

in the depth of processing (i.e. more cognitive effort) when enacting vs verbally conveying verb meanings. Furthermore, this finding seems to be consistent with claims in support of dual coding, with motoric imagery especially likely in the case of auto-demonstration. Elliott and Yountchi (2009) also investigated the effect of TPR on English learners’ acquisition of L2 Russian verbs of motion. The study included an experimental group who received TPR-based instruction incorporating physical movement and a control group who received traditional instruction consisting of grammar and translation activities. Learners in the experimental group were provided with Russian sentences describing motion events and were asked to act out the event portrayed in the sentences. Specifically, they were required to distinguish between unidirectional and multidirectional movement (i.e. going one way or a round trip) and between different modes of transportation (e.g. by wheels or on foot), which are aspects coded in Russian motion verbs. The results of the study showed that the TPR group slightly outperformed the control group in only one of the two post-test measures used. According to the authors, these modest results may be due to the small sample size included in the study (n = 4 for the experimental group; n = 5 for the control group). Attwood (2017) examined the effect of two instructional approaches to teaching boundary-crossing motion events (i.e. entering and exiting): an experimental group who received input-based processing instruction (VanPatten & Cadierno, 1993) and a control group who received input/ output-based instruction. All participants were learners of L2 English with different L1s. The results of the study showed that both groups improved significantly between pretest and post-tests in interpretation and production tasks, but the experimental group outperformed the control group at the delayed post-test in the production task. The interpretation task involved the recognition of whether various English utterances were grammatically (un)usual whereas the production task involved the use of English characteristic lexicalization patterns (i.e. expressions including a manner verb and a path satellite). Evans (2015) investigated the effect of a pedagogical intervention consisting of explicit rule explanation and the provision of negative evidence, paired with aspects of concept-based instruction on the use of English motion verbs by L1 Spanish learners. Concept-based instruction is a type of instruction that is based on Vygotsky’s sociocultural theory and promotes the process of conscious conceptual mediation in L2 learning (see Lantolf & Thorne, 2006; Negueruela & Lantolf, 2006; White, 2012). In a series of lessons, participants were explicitly instructed on typological differences between V- and S-languages, presented with visualizations of motion events and introduced to target-like expressions in English and Spanish. Attention was given to both the use of English path satellites and manner of motion verbs. Consistent with the concept-based instruction,

20  Usage-Based Dynamics in Second Language Development

learners were asked to create graphic depictions of different motion events and discuss them with their peers. The analyses of pre- and postintervention writing samples showed an increase in the appropriate use of motion expressions, particularly in relation to expressions employing English manner of motion verbs. Stam et al. (2017) also investigated the effect of concept-based instruction on the speech and gesture patterns of seven L1 Spanish learners of English. The treatment provided to the learners consisted of three phases. The first involved raising learners’ awareness about motion events by means of, for example, comparisons of NSs’ narratives and their own; introducing the concept of ‘motion event’ via graphic representations; and introducing and practicing manner verbs and satellites through pictures/videos, enacting and creating stories using manner verbs and satellites. The results of the study showed that the instruction provided produced changes in L2 TFS patterns, both in relation to speech and gesture. For example, learners were able to accumulate Path segments within single clauses and combine Path and Manner information in single gestures. Cadierno and Robinson (2009) investigated the extent to which the manipulation of pedagogic tasks in terms of cognitive complexity (tasks referring to events happening Here-and-Now [simple] vs There-andThen [complex]) promoted the development of more target-like constructions for the expression of motion and therefore more appropriate L2 ways of TFS by adult learners with a typologically similar and typologically different L1 and L2: Danish vs Japanese L1 learners of L2 English. The results of the study showed that typological similarity between the L1 (Danish) and L2 (English) resulted in greater use of L2 characteristic motion constructions incorporating mention of Ground of motion compared to their use by Japanese L1 speakers, and that more cognitively complex tasks led to the production of more target-like lexicalization patterns, but only for speakers of the typologically similar L1, Danish. Finally, a recent study by Koster and Cadierno (2019) examined another dimension of TFS, namely, the ‘consequential effects’ of TFS. According to Slobin (2003), a full framework for the study of TFS needs to consider not only the so-called speaking time frame (i.e. the time in which linguistically codable dimensions must be accessed and attended to), but also experience time, i.e. the time of prelinguistic or non-linguistic encoding when the anticipatory effects of language may play a role, and testing time, which involves examining the consequential effects of language, i.e. whether prior linguistic encoding has an effect on subsequent recall or recognition. In their study, Koster and Cadierno (2019) examined whether L1 German and L1 Spanish NSs showed different recognition memory for object position in placement scenes (as a function of crosslinguistic differences in placement verbs), and if they did, whether instruction on the meaning of L2 German placement verbs could improve

Thinking for Speaking in an L2  21

recognition memory for Spanish learners of L2 German. A memory recognition task was used where participants heard a prime sentence while watching a picture depicting a placement event and had to indicate whether the sentence matched the picture (prime trials). Then, after 750  ms, they saw another picture (now without an accompanying sentence) that displayed the same object position as the first (prime) picture or a different one, and were asked to indicate whether the pictures were the same or different. The results of the study showed that, as expected, L1 German speakers had better recognition memory for object position than L1 Spanish speakers. In addition, the recognition memory of Spanish learners of L2 German was better than that of L1 German NSs. This unexpected finding was probably due to the fact that instruction on the meaning of German verbs primed L2 learners into thinking about object orientation. This priming effect would explain learners’ memory advantage for spatial position when tested immediately after instruction. In any case, instruction was seen as being successful in helping learners understand the meaning of L2 placement verbs, with consequences for subsequent memory recognition. An alternative, more radical approach suggested by authors such as Byrnes (2019: 516) is to adopt a conceptual shift to second language instruction in the form of curricular thinking which is understood as ‘… a contextualized, situated, and dynamic understanding of educational practice embedded in an encompassing language educational vision for an entire program…’. Under this approach, L2 learners could experience from the beginning an instructional approach that is usage based/ cognitive linguistics based; that is, an approach which would consistently present the lexico-grammatical constructions of a language as meaning oriented, and which would function as the underlying educational philosophy for an entire curriculum.4 Conclusion

Was Slobin (1996) right when he stated that L1 TFS patterns would be resistant to restructuring in adult L2 acquisition? As shown in this chapter, the answer is yes: at least (some) aspects of L1 TFS are indeed difficult to restructure in an L2, even for advanced language learners. Given this fact and given that L2 learners seem to follow the ‘Transfer to Nowhere’ principle (Kellerman, 1995), explicit instruction on appropriate L2 TFS patterns may be advised. The results of existing intervention studies are promising but more research is needed, especially with learners of L2 V-languages as studies conducted so far have only targeted the acquisition of S-languages. In addition, studies could compare the relative effectiveness of different types of pedagogical approaches within single studies. Finally, in addition to examining the ‘thinking’ patterns in relation to the speaking time frame, future research could further

22  Usage-Based Dynamics in Second Language Development

examine the effects of instruction on Slobin’s (2003) suggested ‘experience’ and ‘testing’ time frames. That is, investigate whether instruction on appropriate TFS patterns can have a positive effect on the kind of thinking that takes place before and after linguistic encoding. Eye tracking methodology as in Flecken (2011) could be used for the former, and recognition memory tasks as in Koster and Cadierno (2019) and Filipović (2011) could be used for the latter. Notes (1) Part of the content of this chapter has appeared in Cadierno (2017). See https://benjamins.com/catalog/hcp.59 (accessed 5 April 2020). (2) For a detailed discussion of the similarities and differences between the two approaches, see Jarvis (2011). (3) The present review focuses on SLA research conducted on S- and V-languages. In addition to this, several studies have examined equipollently framed languages like Chinese as a source or target language (e.g. Brown, 2015; Wu, 2011; Yang, 2003). (4) I would like to thank the anonymous reviewer for bringing this alternative approach to my attention.

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Brown, A. and Gullberg, M. (2011) Bidirectional cross-linguistic influence in event conceptualization? Expressions of path among Japanese and learners of English. Bilingualism: Language and Cognition 14 (1), 79–94. Brown, A. and Gullberg, M. (2012) L1-L2 convergence in clausal packaging in Japanese and English. Bilingualism: Language and Cognition 16 (3), 477–494. Brown, P. (2004) Position and motion in Tzeltal frog stories: The acquisition of narrative style. In S. Strömqvist and L. Verhoeven (eds) Relating Events in Narrative: Typological and Contextual Perspectives (pp. 37–58). Mahwah, NJ: Lawrence Erlbaum. Bylund, E. and Athanasopoulos, P. (eds) (2015) The language and thought of motion in second language speakers. The Modern Language Journal 99 (Supplement 2015), 138–153. Byrnes, H. (2019) Affirming the context of instructed SLA: The potential of curricular thinking. Language Teaching Research 23 (4), 514–532. Cadierno, T. (2004) Expressing motion events in a second language: A cognitive typological perspective. In M. Achard and S. Niemeier (eds) Cognitive Linguistics, Second Language Acquisition, and Foreign Language Teaching (pp. 13–49). Berlin: Mouton de Gruyter. Cadierno, T. (2008a) Learning to talk about motion in a foreign language. In P. Robinson and N.C. Ellis (eds) Handbook of Cognitive Linguistics and Second Language Acquisition. New York/London: Routledge. Cadierno, T. (2008b) Motion events in Danish and Spanish: A focus on form pedagogical approach. In S. De Knop and T. De Rycker (eds) Cognitive Approaches to Pedagogical Grammar (pp. 239–275). Berlin/New York: Mouton de Gruyter. Cadierno, T. (2010) Motion in Danish as a second language: Does the learner’s L1 make a difference? In Z-H. Han and T. Cadierno (eds) Linguistic Relativity in SLA: Thinking for Speaking (pp. 1–33). Bristol: Multilingual Matters. Cadierno, T. (2017) Thinking for speaking about motion in a second language. Looking back and forward. In I. Ibarretxe-Antuñano (ed.) Motion and Space across Languages: Theory and Applications (pp. 279–300). Amsterdam/Philadelphia, PA: John Benjamins. Cadierno, T. and Ruiz, L. (2006) Motion events in Spanish L2 acquisition. Annual Review of Cognitive Linguistics 4, 183–216. Cadierno, T. and Robinson, P. (2009) Language typology, task complexity and the development of L2 lexicalization patters for describing motion events. Annual Review of Cognitive Linguistics 7, 245–276. Cadierno, T. and Eskildsen, T. (eds) (2015) Usage-Based Perspectives on Second Language Learning. Berlin/Boston, MA: Mouton de Gruyter. Cadierno, T., Ibarretxe-Antuñano, I. and Hijazo-Gascón, A. (2016) Semantic categorization of placement verbs in L1 and L2 Danish and Spanish. Language Learning 66 (1), 191–223. Carroll, M. and von Stutterheim, C. (2003) Typology and information organisation: Perspective taking and language-specific effects in the construal of events. In A.G. Ramat (ed.) Typology and Second Language Acquisition (pp. 365–402). New York: Mouton de Gruyter. Carroll, M., von Stutterheim, C. and Nuese, R. (2004) The language and thought debate: A psycholinguistic approach. In T. Pechmann and C. Habel (eds) Multidisciplinary Approaches to Language Production (pp. 281–218). Berlin: Mouton de Gruyter. Carroll, M., Weimar, K., Flecken, M., Lambert, M. and von Stutterheim, C. (2012) Tracing trajectories: Motion event construal by advanced L2 French-English and L2 French-German speakers. Language, Interaction and Acquisition 3 (2), 202–230. Choi, S. and Lantolf, J.P. (2008) Representation and embodiment of meaning in L2 communication: Motion events in the speech and gesture of advanced L2 Korean and L2 English speakers. Studies in Second Language Acquisition 30 (2), 191–224. Cook, V.J. (1992) Evidence for multi-competence. Language Learning 42 (4), 557–591.

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Cadierno (eds) Linguistic Relativity in SLA: Thinking for Speaking (pp. 35–58). Bristol: Multilingual Matters. Hijazo-Gascón, A. (2011) La Expresión de Movimiento y su Adquisición en Segundas Lenguas. Unpublished PhD dissertation, University of Zaragoza. Ibarretxe-Antuñano, I. (2004) Motion events in Basque narratives. In S. Strömqvist and L. Verhoeven (eds) Relating Events in Narrative. Typological and Contextual Perspectives (pp. 89–111). Mahwah, NJ: Lawrence Erlbaum. Ibarretxe-Antuñano, I. (2009) Path salience in motion events. In J. Guo, E. Lieven, N. Budwig, S. Ervin-Tripp, K. Nakamura and Ş. Özçalışkan (eds) Crosslinguistic Approaches to the Psychology of Language: Research in the Tradition of Dan Isaac Slobin (pp. 403–414). New York: Psychology Press. Ibarretxe-Antuñano, I. (2012) Placement and removal events in Basque and Spanish. In A. Kopecka and B. Narasimhan (eds) Events of Putting and Taking. A Crosslinguistic Perspective (pp. 123–143). Amsterdam/Philadelphia, PA: John Benjamins. Jarvis, S. (ed) (2011) Crosslinguistic influence in bilinguals’ concepts and conceptualizations. Special Issue. Bilingualism: Language and Cognition 14 (1). Jarvis, S. and Pavlenko, A. (2008) Crosslinguistic Influence in Language and Cognition. New York/London: Routledge. Kellerman, E. (1995) Cross-linguistic influence: Transfer to Nowhere? Annual Review of Applied Linguistics 15, 125–150. Kellerman, E. and Van Hoof, A. (2003) Manual accents. International Review of Applied Linguistics 41, 251–269. Koster, D. and Cadierno, T. (2019) The effect of language on recognition memory in L1 and L2 speakers: The case of placement events. International Journal of Bilingualism 23 (2), 651–669. Langacker, R.W. (1987) Foundations of Cognitive Grammar, Vol. 1. Theoretical Prerequisites. Stanford, CT: Stanford University Press. Lantolf, J.P. and Thorne, S.L. (2006) Sociocultural Theory and the Genesis of Second Language Development. Oxford: Oxford University Press. Larrañaga, P., Treffers-Daller, J., Tidball, F. and Gil Ortega, M. (2011) L1 transfer in the acquisition of manner and path in Spanish by native speakers of English. International Journal of Bilingualism 16 (1), 117–138. Levelt, W. (1989) Speaking: From Intention to Articulation. Cambridge, MA: MIT Press. Li, P., Eskildsen, S.W. and Cadierno, T. (2014) Tracing an L2 learner’s motion constructions over time: A usage-based classroom investigation. The Modern Language Journal 98 (2), 612–628. Littlemore, J. (2009) Applying Cognitive Linguistics to Second Language Learning and Teaching. Basingstoke/New York: Palgrave Macmillan. Lindstromberg, S. and Boers, F. (2005) From movement to metaphor with manner-ofmovement verbs. Applied Linguistics 26 (2), 241–261. Malt, B.C. and Pavlenko, A. (2011) Kitchen Russian: Cross-linguistic differences and firstlanguage object naming by Russian-English bilinguals. Bilingualism: Language and Cognition 14 (1), 19–45. McNeill, D. (1992) Hand and Mind: What Gestures Reveal about Thought. Chicago, IL: Chicago University Press. McNeill, D. (2000) Analogic/analytic representations and cross-linguistic differences in thinking for speaking. Cognitive Linguistics 11 (1/2), 43–60. McNeill, D. and Duncan, S.D. (2000) Growth points in thinking-for-speaking. In D. McNeill (ed.) Language and Gesture: Window into Thought and Action (pp. 141– 161). Cambridge: Cambridge University Press. Muñoz, M. and Cadierno, T. (2019) Mr. Bean exits the garage driving or does he drive out of the garage?: Bidirectional transfer in the expression of Path. In R. Llopis and A. Hijazo-Gascón (eds) Special issue on Applied cognitive linguistics to L2 acquisition

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2 On the Sample Size Required to Identify the Longitudinal L2 Development of Complexity and Accuracy Indices Akira Murakami

Studying second language (L2) development longitudinally at the level of the individual learner is generally preferred to inferring individuals’ development based on aggregated data. An important question in this context is how many data points there should be per learner to reliably identify his/her longitudinal development. This study examines whether changes in accuracy and complexity measures can be identified in the longitudinal development of the writings of individual learners and investigates the number of writings necessary to identify such changes. It specifically examines whether the necessary sample size varies as a function of (i) specific indices of measurement; (ii) whether the analysis incorporates the specific values of the nominator and denominator when the index of measurement is a ratio or proportion; and (iii) whether the statistical model incorporates potential nonlinearity in development. Data were drawn from a large-scale learner corpus consisting of learners’ writings submitted to an online school. Due to the nature of the data, it is possible to track the development of individual learners, and teachers’ feedback can be exploited to identify errors in the corpus. The subcorpus analyzed in the study included 40 writings each by 54 learners, totaling 2160 writings. The following complexity and accuracy measures were targeted: mean sentence length, subordinate clause per T-unit, mean clause length, the measure of textual lexical diversity (MTLD) and the target-like use (TLU) scores of articles, plural -s and past tense -ed. Statistical models revealed that the necessary sample size varies widely across different measures and depends on the amount of information incorporated into the model. This study points out the differences in the 29

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frequencies of the components of the indices (e.g. all vs selected words) as a potential reason for differences in the necessary sample size, and further highlights the importance of weighting individual data points appropriately in statistically modeling the indices. Introduction

Averages cannot describe individuals. It is well known that the averaged developmental pattern differs from constituent individual patterns (e.g. Heathcote et al., 2000; Murre & Chessa, 2011). This line of research has repeatedly demonstrated that averaging over participants can distort the learning curve and that individual learning curves cannot be properly inferred from the aggregate learning curve. Thus, as Heathcote et  al. (2000: 199) argued, testing should not be conducted on averaged data, and ‘[r]esearchers can no longer afford to ignore or, worse, to dismiss the effect of averaging as being irrelevant to real data from the paradigms used in the study of learning’. Second language (L2) acquisition is no exception. For example, researchers working within Dynamic Systems Theory (e.g. Verspoor et  al., 2011) have repeatedly called for a stronger focus on individual learners because group-level data are highly unlikely to apply to individuals (Lowie & Verspoor, 2019). There are indeed studies that have demonstrated a discrepancy between group-level developmental patterns and the patterns at the level of the individual learner in L2 acquisition. Murakami and Alexopoulou (2016), for instance, illustrated that the learning trajectories of the accuracy of L2 English articles in individual learners can differ from their aggregated patterns, while Bulté and Housen (2018) showed the same in the development of syntactic complexity. Studying L2 development at the level of the individual learner entails collecting multiple data points per learner over a period of time (i.e. longitudinal study). L2 longitudinal research, however, often shares one or more of the following characteristics and limitations: (i) laboratorybased studies exploiting an artificial language (e.g. DeKeyser, 1997), achieving high internal validity with a potential compromise on ecological validity; (ii) small-scale case studies based on natural language data (e.g. Lightbown, 1983), casting doubt on the generalizability of their findings; and (iii) quantitative studies that analyze development by calculating the scores of a metric at distinct time points (e.g. Connor-Linton & Polio, 2014a), but which fail to demonstrate the path the metric follows over the course of development. Illustrating such a trajectory is essential because L2 development often proceeds nonlinearly (e.g. Murakami, 2016), and failing to closely observe the learning curve can result in inaccurate estimates of learners’ development. It is therefore desirable to carry out longitudinal quantitative analyses using intensively sampled natural language data (see Larsen-Freeman & Cameron, 2008).

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In the early days of SLA, conducting a quantitative longitudinal study based on intensive production data was more challenging than it is today because collecting such data is time-consuming and SLA researchers were not equipped with appropriate analytical tools. These days, however, more quantitative longitudinal data are becoming available (e.g. Geertzen et  al., 2014; Meunier, 2016), while appropriate statistical tools to analyze such data have been developed and introduced into the field (e.g. Barkaoui, 2014; In’nami & Murakami, forthcoming; Murakami, 2016). To draw inferences at the level of the individual learner, however, one needs a certain amount of data per learner. A question that arises is how much data are sufficient to identify the development of an individual learner. This depends on several factors, most notably the target index of development (e.g. the mean length of the T-unit vs the ratio of dependent clauses). The difference between indices in terms of the necessary sample size may reflect the difference in the developmental rates of the underlying constructs of the indices (e.g. some constructs develop at faster rates than others, and thus require smaller amounts of data for their development to be identified). Another potential source of between-index differences, however, is the difference in the measurement reliability. In this chapter, how the latter could influence the number of data points necessary to reliably identify a change in the index value is examined. This issue is not a trivial one because if such an effect is large, the fact that one observes a significant change in one index but not in another does not necessarily indicate the difference in the extent to which the constructs underlying the two indices underwent changes (see also Gelman & Stern, 2006). I will explore how significant the impact of the difference in the mathematical nature of the index is in identifying its longitudinal development. Specifically, as the initial step, this chapter examines whether and to what extent the sample size necessary to reliably identify the longitudinal development of a learner in his/her written production depends on the following factors: (i) specific indices of measurement; (ii) whether the analysis incorporates information that the nominator and denominator of the metric include separately; and (iii) the assumed model of development. The first two factors are related to each other and concern reliability. In general, the larger the change relative to noise, the easier it is to identify longitudinal development and the fewer data points required. An important point, however, is that certain indices are inherently noisier than others due to what is counted in their calculation. For instance, if we compare the number of subordinate clauses per sentence and the mean length of clauses in words, it is clear that in a given speech sample or an essay, the nominator of the mean length of clauses (i.e. number of words) is always larger than that of the number of subordinate clauses per sentence (i.e. number of subordinate clauses), and the same holds for the denominator

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(i.e. number of clauses vs number of sentences). This suggests that the mean length of clauses can be more reliable than the number of dependent clauses per sentence because a small change in the nominator or the denominator does not affect its value as strongly as it affects the value of the number of subordinate clauses per sentence, which in turn implies that we may need fewer data points to identify the longitudinal development of the mean clause length than of the number of subordinate clauses per sentence if the underlying constructs of the two indices are similar. Related considerations hold for comparison within a measure. Many developmental indices (e.g. mean sentence length) are calculated by dividing a certain value by the number of units the value is observed in (e.g. the number of words divided by the number of sentences). Quantitatively analyzing such indices as they are could be problematic. For instance, if an essay includes 100 words over 10 sentences and another includes 10 words over 1 sentence, both have a mean sentence length of 10 words, although the former value is more reliable. When analysing those indices as the dependent variable in regression models, therefore, the analysis should incorporate such uncertainty by weighting each observation according to its reliability (i.e. the magnitude of the nominator and denominator). An unweighted ordinary regression analysis ignores such uncertainty and fails to exploit the larger amount of information available in the dependent variable. Finally, the assumed model of development could also influence the number of data points needed to examine longitudinal development. In this chapter, two patterns are compared: linear and nonlinear development. In nonlinear development, no particular form of development is assumed and it is determined in a data-driven way. The expectation is that the analysis assuming linear developmental patterns will be overconfident because an overly simplistic pattern is assumed. The guiding question of the study is how the number of data points necessary to identify the longitudinal development of individual learners varies as a function of (i) target indices; (ii) whether ratios and quotients are analyzed with the models that account for the magnitude of the nominators and denominators; and (iii) whether nonlinear developmental patterns are allowed. The study highlights the potential challenges in the analysis of the ratios and quotients that are common in complexity and in accuracy indices. Longitudinal development in this study refers to any quantitative change of the target index that is not random noise. The identified patterns may or may not be meaningful from a theoretical perspective or represent increases in proficiency. Nevertheless, an investigation into changes in general is the first step toward a more solid understanding of the necessary sample size in L2 longitudinal developmental research. The choice of the variable representing time is a difficult issue in longitudinal data analysis (Long, 2012). In this chapter, the order of writing (e.g. first writing, second writing, third writing) instead of chronological

Sample Size Required to Identify Longitudinal L2 Development  33

time is examined, because using the latter could be problematic when the data are collected unevenly across time. In online learning platforms, a student, for example, can submit two essays with a one-hour interval and then might not engage with the course for a while, before submitting another essay a week later. When a linear developmental pattern is assumed and chronological time is used, the difference between the first and the final essay (i.e. a week apart) in the target index is assumed to be 168 times (i.e. 24 ⋅ 7) larger than that between the first two essays (i.e. one hour apart). This can well be an unreasonable assumption given that learning may not take place with the same intensity for one week as it did during the one hour that the learner was engaged with the course. The order of writing may not be linearly related to target indices either, but since the data for the study reported in this chapter were collected at an online school where learners are engaged with various activities at each teaching unit, it is more reasonable to assume a linear relationship between teaching units and target indices. The problem is less severe when developmental patterns are determined in a data-driven manner, and the difference between using chronological time and writing order as the time variable may not be large. Nevertheless, in order to allow a sufficient change in target indices between adjacent data points, writing order is still more desirable than chronological time. Method Rationale and overview of the method

A conventional technique to determine the necessary sample size to identify a specific effect such as power analysis is not as useful as we would desire in this context because it generally needs to assume a particular functional form of development and also because the expected effect size is not straightforwardly determined, particularly when one employs a technique other than ordinary least-squares regression models. The task of identifying the necessary sample size, therefore, was tackled empirically by exploiting a learner corpus in this chapter. Nevertheless, as a reference point, we can calculate the necessary sample size based on an ordinary linear regression model by drawing on the effect sizes identified in the methodological synthesis of multiple regression in L2 research (Plonsky & Ghanbar, 2018). Plonsky and Ghanbar (2018) reviewed 541 multiple regression models in L2 research and found that the median coefficient of determination (R2) was 0.32. Based on the WebPower package (Zhang & Ke-Hai, 2018) in R, the necessary sample size was then computed for a simple regression model with the corresponding f2 effect size (Cohen, 1988), which can be calculated from R2, with a statistical power of 0.80 and a significance level of 0.05. The result showed that a sample size of 19 is sufficient. It is, however, expected that a larger sample size is necessary to identify the equivalent effect in more complex models (e.g.

34  Usage-Based Dynamics in Second Language Development

generalized additive models [GAMs] with autoregressive errors). A larger number of data points per learner was used, as detailed below. In the following, the corpus from which the data for the study were drawn is introduced, after which the target indices are described. Then, the subcorpus used in the study and the ways the indices were calculated are explained, followed by a detailed explanation of the analytical procedure. Data

The data were drawn from the EF-Cambridge Open Language Database (EFCAMDAT; Geertzen et al., 2014). EFCAMDAT is a longitudinal, partially error-tagged learner corpus including the writings submitted to Englishtown, an online school operated by EF Education First.1 The course in Englishtown consists of 16 levels with eight units each. Each unit includes a free writing task on a variety of topics (see Alexopoulou et al., 2017; Michel et al., 2019), and the responses to the writing tasks constitute the corpus. If a learner starts at the beginning and completes the course, she/he is supposed to have submitted 128 writings. In practice, however, the number of writings per learner was much smaller, possibly because learners discontinued their study on Englishtown or the data collection phase for the current version of EFCAMDAT ended while they were still in progress. Writings submitted to Englishtown are corrected by teachers and returned to students. Those corrections are annotated as error tags in EFCAMDAT, and error annotation is available in approximately two-thirds of the writings in EFCAMDAT. Quantitative measures

Four complexity measures and the accuracy of three linguistic features were targeted: (i) mean sentence length in words; (ii) number of subordinate clauses per T-unit; (iii) mean clause length in words; (iv) measure of textual lexical diversity (MTLD); (v) target-like use (TLU) score of articles; (vi) TLU of plural -s; and (vii) TLU of past tense -ed. The four complexity measures were selected to represent different aspects of linguistic complexity (i.e. overall complexity, complexity by subordination, phrasal complexity and lexical diversity; Norris & Ortega [2009]) and were used in our previous study as well (Alexopoulou et al., 2017). The magnitudes of the values of their nominators and denominators differ (e.g. sentence vs clauses vs subordinate clauses), which makes them suitable for the analysis of the potential effect of the measures’ reliability on the number of writings necessary to identify longitudinal development. Accuracy was represented by the TLU score, which equals the proportion of accurate uses to the sum of obligatory contexts and overgeneralization errors. Obligatory contexts in the present study were operationalized as the sum of accurate uses and omission/misformation

Sample Size Required to Identify Longitudinal L2 Development  35

errors. Articles and plural -s were chosen because both are frequent enough in English to allow a longitudinal analysis at the level of the individual learner. Past tense -ed was included because it is less frequent than the other two features, and thus it would be interesting to examine whether it performs less well in capturing longitudinal development than the other two features due to its less informative nature. Articles included both definite and indefinite forms. Plural -s included regular plural forms (i.e. -s, -es, -ies) but did not include irregular plurals (e.g. children). Overgeneralized mass nouns (e.g. informations) were counted as errors. Past tense -ed only included regular past tense forms and did not include irregular verbs (e.g. hit, went). Subcorpus

The subcorpus used in this study included the 2160 writings by the 54 learners that met the following criteria: (i) their first 40 writings were error annotated; (ii) their first writing was submitted at Level 1 Unit 1; (iii) the complexity measures had no missing values and the values were finite in the 40 writings; and (iv) none of the 40 writings had a mean sentence length larger than 35, a mean clause length larger than 30, a subordinate clause per T-unit larger than 3 or an MTLD larger than 150. The number 40 was chosen to balance the number of learners and longitudinal length, and only the first 40 writings of those learners were included in the subcorpus even when they contributed more writings to EFCAMDAT. Only the learners who started at the very beginning of the course were included to control for potential proficiency effects on the results. This, however, does not mean that all the learners underwent the first 40 units in Englishtown (i.e. Level 1 Unit 1 through Level 5 Unit 8) as some learners skipped or repeated units. The third condition was only applied to complexity measures because the number of obligatory contexts of plural -s or past tense -ed was often 0. The thresholds in the final condition above were chosen because exploration suggested that the target measures were unlikely to be valid in the writings that did not meet the criteria due, for instance, to a list-like structure of the writings or to the writing being too short. The mean length of a writing in the subcorpus was 58 words (SD = 25). The nationalities of the learners varied, but 21 (39%) were Brazilians and another 8 were Chinese (15%). The mean duration in the submission between the first and the fortieth writing was 148 days (SD = 81). Data extraction

In order to calculate complexity metrics, the following procedure was used for each writing. If the writing included punctuation or capitalization errors, the teacher-corrected portion was retained in so far as those errors were concerned because those two error types lower the accuracy

36  Usage-Based Dynamics in Second Language Development

of automated analysis (Huang et  al., 2018). Spelling errors often invite parsing errors as well, but they were retained uncorrected, since other errors (e.g. the correction of grammatical morphemes) are sometimes coded as spelling errors in EFCAMDAT. For the remaining errors, learners’ original writings were retained. Each writing was then syntactically parsed with the Stanford lexicalized constituency parser (Klein & Manning, 2003) with the provided English model. Sentences over 50 words long, however, were excluded because parsing long sentences is often computationally intractable. The numbers of sentences, T-units, clauses and subordinate clauses were then counted in each writing based on the Tregex patterns (Levy & Andrew, 2006) used in an L2 Syntactic Complexity Analyzer (Lu, 2010). The MTLD was separately computed based on the koRpus package (Michalke, 2018) in R. For accuracy measures, the number of errors was counted based on error annotation. For plural -s and past tense -ed, only instances where no change was made to the stem of the word were counted. Accurate uses were operationalized as the occurrences of the target features outside of error tags, regardless of whether the error pertained to the target feature. In counting errors and accurate uses, TreeTagger (Schmid, 1994) was employed to part-of-speech tag the writing with the provided English model in order to resolve ambiguities (e.g. plural -s vs third person -s). Analysis

For each measure, the overall approach was to calculate the proportion of learners whose complexity and/or accuracy values significantly changed (i.e. writing number was a significant predictor) over the first n writings with a significance level of p < 0.05, where n was gradually incremented from 10 to 40. For instance, the proportion of learners whose mean sentence length underwent a significant change over the first 10 writings was calculated, after which the same proportion over the first 11 writings was computed and so forth. This was repeated under four conditions that differed with respect to whether the model was an ordinary regression model (or its variant) or an extension of generalized linear models (GLMs) and whether it assumed linear development. The model specification was as follows. In order to model potentially nonlinear developmental patterns, the study employed generalized additive modeling (Murakami, 2016; Wieling, 2018), which allows the estimation of flexible learning curves in a data-driven manner rather than pre-specifying particular functional forms of development. The value of each complexity and/or accuracy measure was modeled as a function of the nonlinear effect of the writing number (i.e. 1 for the first writing of the learner, 2 for the second writing and so forth). Nonlinearity was achieved via thin plate regression

Sample Size Required to Identify Longitudinal L2 Development  37

splines (Wood, 2003), and the models were built with the mgcv package (Wood, 2017) in R. When the default basis dimension was too large for the smoothing parameter to be estimated, it was decreased to the number of legitimate (i.e. non-missing and finite) data points targeted in the model. When the number of legitimate data points was five or fewer due, for example, to the absence of obligatory contexts or overgeneralization errors in TLU scores, the model was not constructed. To address the potential autocorrelation of errors (Sóskuthy, 2017), first-order autoregressive models (AR1) were specified, with the degree of autocorrelation estimated by the residual lag-1 autocorrelation of the model without an autoregressive error model. When the residual autocorrelation was 0.1 or smaller, however, autocorrelation was considered negligible and AR1 was not employed. Linear models were built by replacing the nonlinear smooth term with the corresponding linear effect of writing number. Most of the target measures take the form of a ratio (e.g. number of words per sentence) or can be considered as an extended form of proportion (e.g. number of accurate uses out of obligatory contexts and overgeneralization errors). Employing ordinary regression models is suboptimal in these cases because information about the differences in uncertainty between data points would be lost (see Introduction). Therefore, the present study used the following models to incorporate the uncertainty of each data point. For subordinate clause per T-unit, Poisson regression models (i.e. GAMs with Poisson distribution and logarithm link function or the corresponding GLMs in the case of linear models) were employed with the number of subordinate clauses as the dependent variable and the log-transformed number of T-units as the offset term. Poisson regression is used to model count data, and offset terms are predictors with the coefficients fixed at 1 (e.g. Winter, 2020; see also Cheng et  al., 2008). In the present study, including an offset term allowed us to model the frequency of subordinate clauses given the number of T-units. In mean sentence length and mean clause length, Poisson models tended to be severely overdispersed. Therefore, negative binomial regression models (i.e. GAMs with a negative binomial distribution and logarithm link function, or corresponding linear models) were employed instead. Negative binomial regression is a generalized form of Poisson regression that allows for a larger dispersion of data. The number of words was the dependent variable, and the number of sentences or clauses was included as an offset term. The MTLD was modeled with the usual ordinary GAM or simple ordinary regression. TLU scores were modeled with binomial logistic regression models (i.e. GAMs with a binomial distribution and logit link function, or corresponding linear models). The number of accurate uses represented the number of successes, and the sum of obligatory contexts and overgeneralization errors minus accurate uses represented the number of failures.

38  Usage-Based Dynamics in Second Language Development

Each measure was also modeled with simple ordinary regression. This allows the evaluation of the potential influence of employing ordinary regression models, which ignore the differences in the reliability between data points, instead of presumably more appropriate GAMs and GLMs, and when the results of the two approaches converge, it also ensures that the resulting differences between the measures are not due to the difference in the types of regression models employed (e.g. Poisson regression vs binomial regression). As is clear from the above, a large number of statistical models were constructed during this process, and consequently, it was not realistic to interpret and explore each model. The rich information of the statistical model was, therefore, reduced to binary data (i.e. whether the writing number was a statistically significant parameter), a practice that has been criticized recently (e.g. Amrhein et al., 2019). Nevertheless, constructing one model for each learner without pooling information across learners is arguably in line with the approaches that value individual variation (e.g. Dynamic Systems Theory), and aggregating the results of individual models as was done in this study is more appropriate than analyzing aggregated data (Rose, 2015). Results Descriptive analysis

Figure 2.1 shows the cross-sectional (left) and longitudinal (right) development of the target measures. Readers are referred to the figure caption for details. In the set of panels on the left, we can see clear increases in complexity and accuracy in some measures (e.g. mean sentence length, MTLD), while the tendency is much less clear in others (e.g. mean clause length, accuracy of past tense -ed). The accuracy of plural -s is at the ceiling level from the beginning to the end, and thus we may not be able to observe much change in the accuracy of individual learners, while in article accuracy, the variability is so large that we may not be able to reliably identify accuracy changes, either. On the right are the developmental patterns in randomly selected learners. Whereas the longitudinal developmental pattern in some learners in some measures (e.g. mean sentence length in Learner 57096) matches the overall crosssectional pattern, others significantly deviate from the aggregated pattern (e.g. MTLD in Learner 131779). Although most of the learners appear to exhibit more or less systematic patterns of development in at least some measures, the question is whether we can reliably identify the development, to which we now turn. Correlation analysis

To gain systematic insights into the way the target measures vary with respect to the extent to which their development is readily identifiable,

Figure 2.1  Left: Cross-sectional developmental patterns of the target measures across Englishtown levels. Thin lines represent the development of individual learners. The thick line in each panel is a trend line, and the gray band represents the 95% confidence interval (CI). The trend lines were computed based on generalized additive mixed models (e.g. Murakami, 2016; Wieling, 2018). The model structure was similar to the model explained in the Method section, except that it also included the nonlinear effect of proficiency, as well as the factor smooth modeling individual variation in nonlinear learning curves. Right: Longitudinal developmental patterns in 10 randomly selected learners across 40 writings. Thin lines are observed data points and thick lines are trend lines. Their CIs were not added in plural -s and past tense -ed because some panels showed very small variability (plural -s) or only included a few data points (past tense -ed), and CIs are unreasonably large in those cases

Sample Size Required to Identify Longitudinal L2 Development  39

40  Usage-Based Dynamics in Second Language Development

the writing number representing longitudinal development was linearly and nonlinearly correlated with each measure for each learner, and the distribution of the correlation coefficients was examined. If, for instance, the majority of the coefficients are far from 0 for a measure, the measure is likely to capture development well. In order to capture potentially nonlinear developmental patterns, the association measure, called the maximal information coefficient (MIC; Reshef et al., 2011), was employed on top of Pearson’s correlation. MIC is an information-theoretic measure of the dependence of two variables and captures both linear and nonlinear relationships. It is similar to the coefficient of determination (R2) in regression models when the relationship between two variables can be modeled by a function. MIC was calculated with the minerva package (Albanese et al., 2013) in R. Figure 2.2 shows the distribution of Pearson’s correlation coefficients (left) and MIC (right). The figure suggests that there is substantial diversity in how strongly the writing number and the target measures are correlated. In mean sentence length, subordinate clause per T-unit and MTLD, their values and the writing number correlate to a certain degree in many learners. The mean Pearson’s correlation coefficients are above 0.33 in the three measures, and the mean MICs are above 0.36. On the other hand, there is practically no correlation between the writing number and the accuracy of plural -s or of past tense -ed. Their mean Pearson’s correlation coefficients are very close to 0, and there are a large number of learners whose MIC is close to 0 in both measures. Mean clause length and the accuracy of articles appear to fall somewhere in between. The mean Pearson’s correlation coefficients are fairly close to 0, but the center of the distribution is clearly on the positive side. Similarly, their mean MIC values are not very different from the three complexity measures mentioned above. From the correlation analysis, therefore, we can expect longitudinal development to be more readily identified in some measures than in others. A potential drawback of this correlation analysis is that it neglects the reliability difference between data points (e.g. 20 words over 4 sentences vs 60 words over 12 sentences). This issue is addressed in the next section. Statistical modeling

Figure 2.3 shows the proportion of learners for whom a significant change was identified over the course of their development in each complexity and accuracy measure. Note that no adjustments for multiple comparison were made because the purpose of the analysis is to identify the overall differences between measures and models rather than strictly testing the presence of change in each learner. Several observations can be made regarding Figure 2.3. First, the overall patterns largely match between the linear and potentially nonlinear

Sample Size Required to Identify Longitudinal L2 Development  41

Figure 2.2  Distribution of the correlation coefficients between the writing number and complexity or accuracy measures based on Pearson’s r (left) and MIC (right). The solid vertical line represents the mean value in each subpanel. In the left panels, the dashed line represents the correlation coefficient of 0, and different shades of bins indicate whether the coefficient is statistically significant at p < 0.05. No adjustments of p-values were made for multiple comparison

Figure 2.3  Proportion of the learners who showed significant changes in complexity and/or accuracy in longitudinal development. The upper group of panels corresponds to the models that allow a nonlinear developmental pattern, whereas the lower group corresponds to the models that assume linear development. The upper panels in each group are based on negative binomial regression (mean sentence length and mean clause length), Poisson regression (subordinate clause per T-unit), ordinary regression (MTLD) and binomial regression (TLUs of articles, plural -s and past tense -ed), whereas the lower panels are based on ordinary regression models

42  Usage-Based Dynamics in Second Language Development

Sample Size Required to Identify Longitudinal L2 Development  43

models. This implies that the learning curves of the target measures were reasonably linear in the target data, and the differences between the measures described below are unlikely to be due to differences in the form of learning assumed. There are, however, some differences between the types of regression models employed. Specifically, ordinary regression models identified significant development in fewer learners in mean sentence length and subordinate clause per T-unit, whereas they identified development in a larger number of learners in the TLU score of plural -s and that of past tense -ed, although their differences were small. Since ordinary regression models are a subset of GLMs (or GAMs), the figures based on negative binomial, Poisson or binomial regressions incorporating larger amounts of information are generally more credible. That said, the relationship between different indices is generally comparable between the types of models, and the statistical models employed are unlikely to affect the overall pattern in the differences between the measures explained below. Below, the focus is on the uppermost panels because the models on which the panels are based are presumably more plausible as they take into account a larger amount of information and allow potentially nonlinear learning curves. There is significant variation between the target measures in terms of the proportion of learners whose development was identified. In mean sentence length and subordinate clause per T-unit, approximately half of the learners show significant changes in the complexity values across 31 or 32 writings, and around 83% of the learners exhibit changes after 40 writings. On the other hand, longitudinal development was not identified at all in the accuracy of plural -s or past tense -ed. The other three measures fall somewhere in between. The longitudinal development of MTLD is identified in some of the learners, but the proportion (i.e. around 59% after 40 writings) remains lower than that observed for mean sentence length and subordinate clause per T-unit. Article accuracy shows a similar tendency to MTLD, but the development is identified only in approximately 20% of the learners even after 40 writings. The corresponding proportion in mean clause length is rather low and is not very different from the nominal significance level (5%) in some parts of Figure 2.3. Possible reasons for these differences are considered in the following section. Discussion and Conclusion

This study examined whether and to what extent the number of data points necessary to reliably identify longitudinal development at the individual level depends on the measures and the specification of statistical models. The results show that whether the model allows nonlinearity in the learning curve does not significantly influence the pattern within each

44  Usage-Based Dynamics in Second Language Development

measure. This is, in a sense, reassuring because most previous studies analyzing complexity measures assumed linear development when the time variable was quantitative. The present study points toward the possibility that their findings might not have differed greatly even if they had employed presumably more appropriate nonlinear modeling techniques. Nevertheless, this is only because in the subcorpus of EFCAMDAT exploited in this study, the learning curves of the target measures happened to be reasonably linear, which does not necessarily hold for other measures or with other data sets, and the results in this study should not be interpreted as supporting the use of linear models to analyze L2 learning curves. Slight differences in the results were observed between ordinary regression models and GLMs or GAMs. In mean sentence length and subordinate clause per T-unit, a larger number of learners were found to undergo significant changes in GAMs, presumably because each observation was not appropriately weighted in ordinary regression models, resulting in lower statistical power. If we count a relatively unreliable data point (e.g. few T-units) as much as a more reliable one, for instance, the observed variability of the target index will be unnecessarily large and fewer learners will reach statistical significance. In contrast to the two indices above, ordinary regression models identified a larger number of learners who showed significant changes in the TLU scores of plural -s and past tense -ed than GLMs or GAMs. To understand why this occurred, recall that the average accuracy of plural -s was at the ceiling level. Ordinary regression models nevertheless ‘found’ learners who showed development presumably because the writings with few obligatory contexts tend to mark extreme values, which could entail spurious significant effects if those data points were considered as reliable as writings with a larger number of obligatory contexts. Similarly, in past tense -ed, Figure 2.1 shows outlier values at Englishtown Levels 4 through 7, where the learners’ latter half of writings tended to fall. If these were calculated based on a small number of obligatory contexts but were still considered reliable, they could well drive spurious significant results. GLMs and GAMs, on the other hand, accounted for the reliability of individual data points and did not have to suffer from the lack of reliability of TLU scores. These considerations illustrate the potential risks associated with model misspecification, and SLA researchers should move away from employing ordinary regression models including t-tests and analysis of variances (ANOVAs) in the analysis of ratios and proportions. This study found striking differences between the target indices. Mean sentence length, subordinate clause per T-unit, MTLD and article accuracy demonstrated significant changes in some learners, whereas mean clause length, the accuracy of plural -s and the accuracy of past tense -ed largely did not. This study does not provide a reason behind

Sample Size Required to Identify Longitudinal L2 Development  45

these differences, but speculations can be made. Longitudinal development was identified in a relatively large number of learners in mean sentence length and subordinate clause per T-unit, possibly because all the words in the writing were used in their calculation, and consequently their values tend to stabilize better (i.e. show less variability). In the Introduction, it was hypothesized that fewer learners would be shown to undergo significant changes in subordinate clause per T-unit than in mean sentence length because the components of the former (i.e. subordinate clauses and T-units) are not as frequent as those of the latter (i.e. words and sentences). We might thus expect a lower reliability and larger noise for subordinate clause per T-unit, as well as a lower power to identify longitudinal development. However, the fact that the development of a significant portion of learners was nevertheless identified in the index implies the robust development of subordination, at least in the learners with relatively lower proficiency levels targeted in this study. MTLD also incorporates a fair amount of information, as every word in a writing exerts some influence on the value. However, it exhibits large variability (cf. Figure 2.1), possibly because the writings in EFCAMDAT tend to be fairly short ( 0.754 or r < –0.754

Throughout the observation period, correlation coefficients range from strongly positive to strongly negative for the different learners though many values are situated around the middle (i.e. between –0.2 and 0.2). Table 3.6 shows the bivariate and detrended correlation coefficients between SCR and MLNP for the 10 learners. The bivariate correlations point to a weak to no association between SCR and MLNP scores across learners, with coefficients ranging between –0.332 and 0.235. The detrended correlations display a weak to moderate negative correlation between the two measures, with a negative coefficient for 9 of the 10 learners, which in five cases is stronger than –0.3. However, only one of these coefficients is significant. Figure 3.4 tracks the moving correlations between SCR and MLNP for the 10 learners. Even though there is considerable variation in the correlation coefficients, both within and between learners, the association tends to be either only slightly positive (i.e. not in excess of 0.2) or moderately negative (i.e. not below –0.4). A strongly positive association is only observed for one learner around the middle of the observation period (L10), and another learner shows a strongly negative association from the middle of the observation period onwards (L5). Most coefficients range between –0.25 and 0.25. Concurrent development: Group and individual level

This section investigates whether there is evidence for concurrent development of measures (and of the complexity components they capture). To this end, we examine how the scores on the two pairs of measures develop by tracking their development by means of a scatterplot that shows scores on one measure on the x-axis and on another measure on the y-axis. First we look at G (x-axis) and MLTU (y-axis). We start by examining group development (Figure 3.5).

–0.101

Detrended

*p < 0.05.

–0.025

Bivariate

L1

0.014

0.094

L2

–0.217

  0.012

L3

–0.315

–0.043

L4

 –0.679*

–0.194

L5

–0.353

–0.332

L6

Table 3.6  Bivariate and detrended correlations between SCR and MLNP (individual learners) L7

–0.431

 0.142

L8

–0.286

 0.107

L9

–0.344

 0.235

L10

–0.271

 0.084

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A DUB-Inspired Case Study of Multidimensional L2 Complexity Development  69

Figure 3.4 Moving correlations SCR and MLNP (individual learners). With α = 0.05 and df = 5, p < 0.05 if r > 0.754 or r < –0.754

Figure 3.5  Development of G and MLTU (group)

As observed earlier, for both G and MLTU the scores at the end of the study are higher than at the beginning. When studied together, three or perhaps even four stages can be discerned in the development of these two measures: first, learners score low on both G and MLTU (Task 1); MLTU scores then increase while G scores remain fairly constant (Tasks 2–4); in a next stage, G scores increase while MLTU scores stay constant (Tasks 5–6); in a final stage, G scores remain fairly constant while MLTU scores increase further (Tasks 7–11). However, when we look at the graphs for the individual learners (Figures 3.6–3.8), we see that no single learner follows the stages that we observed at the level of the group. This can be illustrated by looking at the scatterplots of Learners 1, 2 and 3. Learner 1 already starts with fairly high MLTU scores at the onset of the study, whereas her G scores

70  Usage-Based Dynamics in Second Language Development

Figure 3.6  Development of G and MLTU (Learner 1)

Figure 3.7  Development of G and MLTU (Learner 2)

Figure 3.8  Development of G and MLTU (Learner 3)

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clearly increase from Tasks 1–3 to Tasks 4–11. Apart from this clear increase in G scores, there appears to be no pattern to the changes in both MLTU and G. Learner 2 starts with low MLTU scores and fairly low G scores (Tasks 1–4, with the exception of Task 3). Then, G scores increase first while MLTU scores remain low (Task 5), after which MLTU scores also increase and G scores increase further (Tasks 6–7). This is followed by a sharp drop in G scores and relatively stable MLTU scores (Tasks 8–10). The last task registers the highest MLTU score, while G scores remain stable. The development of G and MLTU scores for Learner 3 starts off fairly linearly, with scores on both measures increasing in parallel (Tasks 1–7). In a second stage, initially MLTU scores still slightly increase, but subsequently decrease again, while G scores follow an opposite pattern (Tasks 8–11). The developmental trajectories of the remaining seven learners can be seen in Appendix A.1. The concurrent development of SCR and MLNP group scores is shown in Figure 3.9. At first, both SCR and MLNP scores are low (Task 1). Then, SCR scores increase, while MLNP scores remain fairly stable across Tasks 2–4. In a next stage, MLNP scores gradually increase while SCR scores remain fairly stable (Tasks 5–7). Finally, SCR and MLNP scores appear to alternate between high and medium-high values (Tasks 8–11). Also for these two measures, none of the learners in our sample follow the group trend. A considerable number of learners start with low SCR and MLNP scores (e.g. Learners 2, 3, 8 and 10), and some of the learners end with high SCR and MLNP scores (e.g. Learners 1, 4, 7 and  8). The paths that the learners follow, however, are very diverse. There is also no apparent consistency in the direction of the changes

Figure 3.9  Development of SCR and MLNP (group)

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between subsequent tasks: sometimes both measures increase simultaneously (e.g. between Tasks 2–3 and 5–6), sometimes one measure increases while the other remains constant, still other times both remain fairly constant (e.g. between Tasks 3 and 4) or both change in opposite directions (compare Tasks 7 and 8, where MLNP decreases and SCR increases, with Tasks 8 and 9, where MLNP increases as SCR decreases; compare also Tasks 1–2 with 4–5). Figures 3.10–3.12 show the individual patterns for Learners 1–3 while the graphs for the other seven learners are again included in Appendix A.2. Learner 1’s SCR scores are already fairly high at the onset of the study (similar to this learner’s MLTU scores, see Figure 3.6), whereas her MLNP scores are low. The MLNP scores remain fairly constant for Tasks 1–3, but then there is a clear increase in scores for Tasks 4 and 5. From Task 6 onwards, the MLNP scores do not increase substantially

Figure 3.10  Development of SCR and MLNP (Learner 1)

Figure 3.11  Development of SCR and MLNP (Learner 2)

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Figure 3.12  Development of SCR and MLNP (Learner 3)

and stay in the range of the scores recorded for Tasks 4 and 5, even though the scores for Tasks 10 and 11 are among the three highest scores obtained by this learner. At the same time, there does not seem to be a clear pattern in the evolution of SCR scores, not when considered on their own, nor in combination with MLNP scores (i.e. sometimes when MLNP scores increase, SCR scores increase as well, but at times they decrease, and vice versa). Learner 2 obtained low MLNP and low SCR scores at the onset of the study (Task 1). Both SCR and MLNP scores increase from Task 1 to Task 2, but MLNP scores decrease again from Task 2 to Task 3, while SCR scores still increase. The scores on Tasks 4 and 5 are again similar to the scores registered on the first task. Both MLNP and SCR scores then increase until Task 7. From Task 7 onward, SCR scores remain fairly constant (and high) until the end of the study, whereas MLNP scores drop between Tasks 7 and 8, to then remain fairly constant and rather low until the final task. Finally, the writing of Learner 3 appears to increase in syntactic complexity mostly through clausal subordination. The first three tasks produced by this learner contain no subordinated clauses, between 15% and 30% of the clauses in Tasks 4–6 are subordinated, around 40% in Tasks 7–10 and nearly 60% in Task 11. The pattern for phrasal elaboration, meanwhile, is less clear. The lowest MLNP scores are registered for the first and the last task, and the highest scores for Tasks 6 and 10. The scores appear to increase, decrease or remain stable without any clear pattern. Discussion

We believe that the design of our study is noteworthy among the growing body of DUB-inspired studies of linguistic complexity in L2

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development because of its longitudinal design in combination with its fairly dense data collection points and its number of learners, which with 10 learners investigated exceeds that of most previous DUB studies. Even though it has been argued that generalising across learners is not necessarily the aim of DUB studies (Lowie & Verspoor, 2019), we believe that including several learners in a study is useful (and perhaps even necessary) for yielding both more reliable and generalisable results. To this end, we compare both the developmental patterns as well as the results of individual dynamic analyses across learners. At the same time, this combination of characteristics may also account for the rich and varied, or, as some would have it, fuzzy or even messy picture that emerges from the analyses presented above, which are challenging in terms of their interpretation. The results of our analyses reveal little or no consistency in the observations at the level of individual learners, whether in terms of the developmental trajectories of the learners or the relationships between complexity dimensions in their L2 writings over time. Moreover, the patterns observed at the level of the group do not seem to be representative for those displayed by the individual learners, which appears to confirm the assertion in other DUB studies that averaged scores may not be particularly useful to describe the actual L2 development of individual learners (Lowie & Verspoor, 2019). At the same time, our results show that it might be ill-advised to formulate substantial conclusions on the basis of an analysis of a single L2 learner, considering the high degree of variability across different learners. In sum, we have not found compelling evidence of strong supporting or competing relationships between the different measures and the complexity components they tap into (in contrast to e.g. Spoelman & Verspoor, 2010; Verspoor et  al., 2008; Vyatkina, 2012), with the possible exception of a slightly competitive association found between clausal subordination and phrasal elaboration. At the group level, the positive correlations found between complexity measures seem to be influenced by the shared linear developmental trend across individual measures. Only the expected strong positive association (expected given their structural interdependency) between the global MLTU and the measure of clausal subordination (SCR) remains after detrending the data, as well as a positive relationship between the measures of lexical diversity (G) and phrasal elaboration (MLNP). The results suggest, first, that MLTU scores and SCR scores run, to a large extent, in parallel and, second, that the mean length of T-units is largely determined by the amount of subordination in a text. The positive association between lexical variety (G) and phrasal elaboration (MLNP) is potentially interesting. Greater phrasal elaboration in English requires a larger repertoire of determiners and, especially, of pre- and postmodifiers (i.e. adjectives, adverbs, prepositions, nouns). This may, in turn, be

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reflected in a greater overall lexical diversity. However, this trend and its interpretation need to be further analysed at the individual level. The findings for G and MLTU are mixed: at the group level, the standard correlation points to a mildly positive relationship, and the detrended correlation to a mildly negative one. This pattern also appears in the data of some of the individual learners, but not in those of the majority of learners. Generally speaking, the association tends to be weaker for the individual learners. The observed patterns at the group level are thus not representative of the individual learners. For SCR and MLNP, we found a weak positive association at the group level when not compensating for linear trends, but this relationship became strongly negative after detrending. This result at the group level, however, was only partially confirmed at the level of individual learners, which show a high degree of variability, in combination with generally mildly negative correlations. These findings could be taken as providing some support for the hypothesis, proposed by, inter alia, Norris and Ortega (2009), that at certain points along the L2 developmental trajectory, learners either complexify their writing at the sentential level (producing more syntactic embedding) or at the phrasal level (producing more structurally elaborate noun phrases), but not both. This negative correlation could also simply mean that (L2) writers choose to use either more subclauses or longer phrases to add propositional information to sentences, which, in turn, can be linked to the (stylistic) choices they make in the process of knowledge construction and meaning-making (Ryshina-Pankova & Byrnes, 2013). Whatever the case may be, at the individual level the moving correlations between measures vary considerably across learners, and do not point in the direction of either strong positive or negative associations between the different complexity dimensions, at least not as a general pattern or even trend. The high degree of variability between learners in their developmental patterns of complexity dimensions, especially when considered jointly (e.g. by looking at correlations or concurrent development), can in part be explained by the noise that is inherent in the measurement of L2 complexity, especially in short texts (fewer than 100 words). The link between the individual scores on complexity measures and the (development of the) L2 system of the learner is a tenuous one. It is not clear to what degree the observed variability is characteristic of the overall development of individual learners, or rather results from other factors. Possible other explanations include (a) non-developmental individual variables influencing L2 production at a given point in time (familiarity with the topic, mood, fatigue, etc.); (b) stylistically motivated or idiosyncratic linguistic choices and preferences of the individual learner; (c) the effect of the different prompts or topics on the L2 writing productions; (d) measurement noise (e.g. syntactic measures calculated on the basis

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of texts containing fewer than 10 sentences). For all these reasons, one must be cautious when interpreting the results of individual learners. We believe it is best not to attach too much weight to each individual score on each measure, and to allow for a certain degree of flexibility when interpreting graphs and correlations from individual learners. It is true that many of the factors that create noise in individual scores are cancelled out when averaging scores. In our study, however, measurement occasion coincided with task, so the possible effects of the nature of the task and topic cannot be entirely ruled out here. Apart from the increasing proficiency level of the learners over time, such task effects are likely to have a strong impact on the average scores, since they are not randomly distributed. Therefore, when calculating detrended correlations at the group level, it is possible that task effects have a considerable impact on the observed coefficients. We opted not to use detrended correlations in the moving correlations analyses, since these correlations are based on smaller subsets of data, and also smaller time periods. It is not clear whether detrending in this case means removing the overall linear time trend from the scores on the measures, or rather the linear trend that is observed in the particular observation window of the moving correlation. In case of the latter, the linear trend (which is controlled for at each step of the moving correlation analysis) potentially changes at each step of the moving correlation, which renders the interpretation particularly abstruse, and would require a more in-depth description of the observed linear patterns for each window. Also, the smaller the correlation window becomes, the more uncertain the estimates of both the linear trend and the bivariate correlation. This brings us to the choice of an appropriate window size for a given data set for moving correlations, which is not straightforward and to some extent arbitrary. The aim here should be to find the right balance between including as many data points as possible (to ensure a reliable estimation of the correlation coefficient), and keeping the window size small enough to yield a meaningful dynamic analysis (the larger the window, the more similar the moving correlations to the traditional correlation coefficient). Significance tests can provide an indication of how certain we can be about the estimated correlation coefficients, and with only five (cf. Spoelman & Verspoor, 2010) or even seven data points, only correlation coefficients that are very high or low (i.e. r > 0.878 and r > 0.754, respectively) are labelled significant. In our study, only a very small proportion of the calculated moving correlations exceeded the thresholds for significance, which could suggest that an even larger correlation window might be appropriate. In any case, it is clear that researchers should strive to include as many data points as possible per learner if their aim is to study dynamic interrelationships between L2 (complexity) components. Future studies could also look into more advanced nonlinear modelling techniques, such as generalised additive (mixed) models, to

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study dynamic interrelationships between L2 (complexity) components (Murakami, 2016). In addition to the methodological restrictions and limitations raised previously, this empirical study is limited in a number of other ways as well. First, we only focused on objective, structural complexity in the learners’ productions, without considering other aspects of L2 writing, such as accuracy. Nor did we investigate the (potentially complicated) relationship between complexity and writing quality in general, or between complexity and appropriateness. Second, we did not discuss the potential importance and/or impact of different types of instruction on the development of writing abilities in general, and L2 complexity development in writing in particular, in spite of the clear link between the two (see Bulté & Housen, 2019). Finally, we only examined complexity at the level of the text (i.e. essay or writing task), and not at the level of the individual sentences that constitute the text, thus disregarding a potential source of variability that may provide additional insights into the relationships between complexity dimensions at the level of the individual learners.8 The above methodological considerations and caveats notwithstanding, we still believe that the findings of our study confirm that different complexity dimensions develop independently, or at least not necessarily in parallel, both at the level of the group and at the level of individual learners. A consequence of these findings is that, given the multifaceted and multidimensional nature of the linguistic complexity construct, a sufficiently wide range of complexity measures is required in order to reliably assess whether progress is made over time or not, or whether the complexity scores of two groups of learners differ significantly from one another. By looking at a limited number of measures only, progress on other components or along other dimensions may be lost, leading to overgeneralisations and possibly inaccurate conclusions about the course of L2 complexity development. At the same time, we argue that, partly because of the noise inherent in complexity measurement, caution is also advisable when interpreting the scores of individual learners at specific points in time, and emerging developmental patterns need to be considered with the necessary degree of flexibility. This further underlines the importance of studying multiple learners, or at least to refrain from generalising too broadly on the basis of individual case studies (e.g. Spoelman & Verspoor, 2010; Verspoor et  al., 2008). This being said, generalising from multiple case studies, such as the ones presented in this chapter, can also prove to be difficult, since it is hard to uncover patterns across learners. This exercise thus raises a number of important issues that merit more consideration than they may have received in DUB research on L2 development so far. These issues include exactly how flexible we need to be in the interpretation of individual scores (e.g. given the presence of noise); how general (and informative) the trends that we

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look for should be; and whether and to what extent only looking for or at linear trends implies succumbing to reductionism. An even more important question we should ask is what our findings obtained through DUB-inspired analyses ultimately tell us about the nature of L2 complexity development. There appears to be a high degree of variability, both within and between learners, and different complexity components show different developmental paths, and there appear to be complex relationships between the various components. All these findings point to the fact that capturing and quantifying L2 (writing) development is a daunting task, and making claims that hold for all, a majority of or sometimes even only a substantial number of learners is not always easy, nor feasible. Variability undeniably seems to be a crucial aspect of L2 development, and of human behaviour in general. But whether, and if so, how variability actually drives L2 development, as is often claimed or implied in DUB-inspired L2 studies (e.g. Vyatkina et al., 2015), is still an open question and one that we believe cannot yet be answered on the basis of the currently available findings. Conclusion

The findings of the DUB-inspired analyses of linguistic complexity phenomena in 11 writing tasks of 10 adolescent EFL learners over a period of nearly two school years suggest that there are diverse, dynamic, potentially competing as well as supporting interrelationships between different complexity measures and components, which is in line with observations of other DUB-inspired studies of L2 development (Spoelman & Verspoor, 2010; Verspoor et al., 2008). The analyses further show that, even though the different complexity dimensions display overall increasing trends over time, their developmental trajectories are far from identical. We find some evidence of competing growth, especially between the two dimensions of syntactic complexity, and can conclude that different complexity dimensions do not necessarily develop hand in hand. The overall picture is rendered even more complex by a substantial amount of variation across learners. In this context, we pointed to the existence of various sources for this variation that are not always related to the L2 developmental process itself, such as familiarity with the topic, mood, fatigue, stylistic choices and measurement noise. Moreover, our analyses indicated that averaged group patterns are not necessarily representative for individual learners (Lowie & Verspoor, 2019), and that one should be cautious when drawing conclusions on the basis of single learners. All this goes to show that investigating L2 (complexity) development from a DUB perspective is a valuable and even necessary but also a daunting task. Valuable and necessary because a DUB perspective and DUB analytical procedures highlight and uncover fundamental aspects of the L2 developmental process that risk being neglected or remain

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uncovered in more traditional approaches to the study of L2 development. Daunting, not only because of the multifaceted and multidimensional nature of the complexity construct and its manifestations in L2 production and development, but also because of the technicality and complexity of the repertoire of analytic techniques in DUB research, and the sometimes overwhelming multitude, richness and complexity of the results which they yield, which rarely lend themselves to straightforward interpretations that are consistent with the theoretical premises of DUB perspectives on language development. Considering the relative novelty of the DUB approach to L2 development combined with an active and expanding community of researchers, we are confident that DUB research will overcome these growing pains as it reaches its full maturity. Appendix A.1

Development of G and MLTU for Learners 4–10

Figure A.1  Development of G and MLTU (Learner 4)

Figure A.2  Development of G and MLTU (Learner 5)

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Figure A.3  Development of G and MLTU (Learner 6)

Figure A.4  Development of G and MLTU (Learner 7)

Figure A.5  Development of G and MLTU (Learner 8)

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Figure A.6  Development of G and MLTU (Learner 9)

Figure A.7  Development of G and MLTU (Learner 10)

Appendix A.2

Development of SCR and MLNP for Learners 4–10

Figure A.8  Development of SCR and MLNP (Learner 4)

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Figure A.9  Development of SCR and MLNP (Learner 5)

Figure A.10  Development of SCR and MLNP (Learner 6)

Figure A.11  Development of SCR and MLNP (Learner 7)

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Figure A.12  Development of SCR and MLNP (Learner 8)

Figure A.13  Development of SCR and MLNP (Learner 9)

Figure A.14  Development of SCR and MLNP (Learner 10)

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Notes (1) Even though in recent years we have grown more critical towards certain aspects of the dynamic usage-based (DUB) approach that is advocated by Marjolijn Verspoor and colleagues at the University of Groningen (Bulté & Housen, 2020), her work was one of the main inspirations for the first author’s doctoral dissertation (Bulté, 2013) as well as certain subsequent publications (Bulté & Housen, 2018). In addition to these theoretical and methodological influences, Marjolijn was also kind enough to respond favourably to our call to share longitudinal data that matched our research needs, which not only helped us tremendously, but is also emblematic of her positive take on doing science, based on collaboration and attempting to build knowledge jointly, as a research community. We would therefore like to take the opportunity offered by this book to thank Marjolijn not only for what she has done for us personally, but also for her contributions to the field of second language acquisition, or second language development, as a whole, for example as one of the pioneers of the DUB approach. (2) In our view, and for the purposes of the analyses presented in this chapter, DUB approaches to SLA are very similar to, and overlap with such other recent ‘dynamic’ approaches that are collectively referred to as (C)DST ([Complex] Dynamic Systems Theory) approaches (Larsen-Freeman & Cameron, 2008; Verspoor et al., 2011; Fogal & Verspoor, 2020). (3) Yet, see e.g. Byrnes et al. (2010) and Ryshina-Pankova and Byrnes (2013) for an alternative approach which holds that syntax and lexicon in particular cannot be separated when studying long-term L2 development as they form an integrated repository from which learners must learn to choose in terms of their implications for different ways of meaning-making. (4) We use the terms ‘supportive’ and ‘competitive’ loosely here to refer to positive and negative relationships (i.e. correlations) between measures and the constructs they are measuring, without making claims about the cognitive nature and/or origin of these relationships. (5) We acknowledge that from certain theoretical linguistic perspectives, including the DUB perspective, and in terms of psycholinguistic reality a strict division between different levels or subsystems of linguistic organisation is questionable. Nevertheless, we also believe that for heuristic purposes classifying complexity measures into different categories based on their main focus or scope (e.g. whether lexical forms or morphological or syntactic constructions) is still a useful endeavour. (6) Detrended correlations remove the observed linear time trend from the correlation (resulting in a correlation between the residuals or error terms from two linear regressions with time as the independent variable). Detrended correlations thus show the strength of the association between the measures after the linear time trend has been removed. (7) Spoelman and Verspoor (2010) use a window size of 5, but we argue that this might be too small to yield reliable correlation coefficients (Bulté & Housen, 2020; see also Discussion). (8) We thank an anonymous reviewer for bringing this limitation to our attention.

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Bulté, B. and Housen, A. (2014) Conceptualizing and measuring short-term changes in L2 writing complexity. Journal of Second Language Writing 26, 42–65. Bulté, B. and Housen, A. (2018) Syntactic complexity in L2 writing: Individual pathways and emerging group trends. International Journal of Applied Linguistics 28 (1), 147–164. Bulté, B. and Housen, A. (2019) Beginning L2 complexity development in CLIL and nonCLIL secondary education. Instructed Second Language Acquisition 3 (2), 153–180. Bulté, B. and Housen, A. (2020) A critical appraisal of the CDST approach to investigating linguistic complexity in L2 writing development. In G. Fogal and M. Verspoor (eds) Complex Dynamic Systems Theory and L2 Writing Development. Amsterdam/ Philadelphia, PA: John Benjamins. Byrnes, H., Maxim, H. and Norris, J.M. (2010) Realizing advanced foreign language writing development in collegiate education: Curricular design, pedagogy, assessment [Monograph]. Modern Language Journal 94 (Suppl. s1). Caspi, T. (2010) A dynamic perspective on second language development. Unpublished doctoral dissertation, University of Groningen. Chan, H., Verspoor, M. and Vahtrick, L. (2015) Dynamic development in speaking versus writing in identical twins. Language Learning 65 (2), 298–325. de Bot, K., Lowie, W. and Verspoor, M. (2007) A dynamic systems theory approach to second language acquisition. Bilingualism: Language and Cognition 10 (1), 7–21. Fogal, G.G. and Verspoor, M.H. (2020) Complex Dynamic Systems Theory and L2 Writing Development. Amsterdam/Philadelphia, PA: Benjamins. Guiraud, P. (1959) Problèmes et méthodes de la statistique linguistique. Dordrecht: Reidel. Halliday, M.A.K. (1998) Things and relations: Regrammaticizing experience as technical knowledge. In J.R. Martin and R. Veel (eds) Reading Science: Critical and Functional Perspectives on Discourse of Science (pp. 185–235). London: Routledge. Heatley, A., Nation, P. and Coxhead, A. (2002) RANGE and FREQUENCY programs. See http:​//www​.vict​oria.​ac.nz​/lals​/staf​f/pau​l-nat​ion/n​ation​.aspx​ (accessed 18 January 2018). Hatch, E.M. (1983) Psycholinguistics: A Second Language Perspective. Rowley, MA: Newbury House. Kuiken, F., Vedder, I., Housen, A. and De Clercq, B. (2019) Variation in syntactic complexity: Introduction. International Journal of Applied Linguistics 29 (2), 161–170. Larsen-Freeman, D. (2006) The emergence of complexity, fluency, and accuracy in the oral and written production of five Chinese learners of English. Applied Linguistics 27, 590–619. Larsen-Freeman, D. and Cameron, L. (2008) Complex Systems and Applied Linguistics. Oxford: Oxford University Press. Lowie, W. and Verspoor, M. (2015) Variability and variation in second language acquisition orders: A dynamic reevaluation. Language Learning 65, 63–88. Lowie, W. and Verspoor, M. (2019) Individual differences and the ergodicity problem. Language Learning 69 (S1), 184–206. MacWhinney, B. (2000) The CHILDES Project: Tools for Analyzing Talk. Hillsdale, NJ: Lawrence Erlbaum. Murakami, A. (2016) Modeling systematicity and individuality in nonlinear second language development: The case of English grammatical morphemes. Language Learning 66 (4), 834–871. Norris, J.M. and Ortega, L. (2009) Towards an organic approach to investigating CAF in instructed SLA: The case of complexity. Applied Linguistics 30 (4), 555–578. Ortega, L. (2003) Syntactic complexity measures and their relationship to L2 proficiency: A research synthesis of college-level L2 writing. Applied Linguistics 24 (4), 492–518. Ortega, L. (2012) Interlanguage complexity: A construct in search of theoretical renewal. In B. Kortmann and B. Szmrecsanyi (eds) Linguistic Complexity: Second Language Acquisition, Indigenization, Contact (pp. 127–155). Berlin: de Gruyter.

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4 A Holistic Person-Centred Approach to Mobile-Assisted Language Learning Hongying Peng, Sake Jager, Steven L. Thorne and Wander Lowie

For many decades, quantitative second language (L2) researchers have been operating under the assumption that group averages reveal something about the individuals comprising the population on which they are based. This chapter constructively contests this assumption and offers an augmentative methodological and theoretical framework that emphasises person-centredness (Benson, 2019). Research has increasingly shown that L2 learning and use are essentially individually owned. This is perhaps especially the case in today’s technologised world, where L2 learners have access to diverse and myriad learning resources that articulate with their personal goals, learning interests and preferences, prior knowledge and language and digital competencies. It is with this contemporary context in view that we present an ecological person-centred account of language learning. With a focus on individual learners, the person-centred approach views each individual as a relationally constituted whole, where intra- and extra-individual attributes and resources are understood to form an entangled system that jointly contributes to the process of language development. With a brief discussion of an empirical example of a clustering approach to analysing learning experiences mediated by mobile technologies, this chapter elucidates how the application of person-centred methods can help to advance our understanding of complex L2 phenomena. The conclusion discusses implications of the person-centred approach for L2 research and teaching. Introduction

There is a growing acceptance of the view that language, as a complex and adaptive system, is interrelated with and embedded in our cultural, sociological and psychological lives (see Five Graces Group, 2009; Verspoor, 2017). In such a view, language learning is recognised as 87

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a dynamic process that results from the interplay between a wide range of learner-internal and -external variables as well as their simultaneous interaction with the learning environment (e.g. de Bot et al., 2007). Considering that the number of variables at play and the way they interact are usually different for different learners, each individual tends to show distinctive developmental trajectories (Verspoor et al., 2017). Especially in today’s globalised and technologised world, learners have available a multiplicity of language learning resources through which to explore personal goals, learning interests and preferences, and which potentially expand upon prior knowledge, language abilities and digital competencies (Kukulska-Hulme, 2016; Thorne, 2008). Emerging technologies integrate diverse online resources with opportunities for interaction and communication with people from remote corners of the globe, creating conditions under which the boundaries between classroom-based guided learning and autonomous learning in learners’ everyday lifeworlds are blurred (Thorne, 2013; Thorne et  al., 2015). Concomitant with global changes afforded by digital mediation are learners’ pursuits of differentiated learning goals. That is, today’s multilingual and technology-supported culture is redefining when, why and how languages are learned and used (Chinnery, 2006; LarsenFreeman, 2017; The Douglas Fir Group, 2016). In direct application to our study, Kukulska-Hulme (2016) further recognises that digital language learning using mobile technologies offers an augmented potential for personalisation. To cope with the increasing complexity and diversity of language use in the 21st century, taking an ecological approach that simultaneously examines individual learners and their interdependence with a spatial-temporal context is warranted. This focus on the individual operating contingently in a spatial-temporal context redirects second language (L2) research to ‘a more person-centred frame of reference’ (Larsen-Freeman, 2017: 60). It is from this perspective that we present an ecological and personcentred account of language learning in a technologised society. By focusing on individual learners, the person-centred approach views each individual as a functioning whole in interaction with components of larger systems that jointly contribute to the process of language development. Specifically, we pursue an integrative consideration of learners’ attributes (e.g. motivation, emotion, autonomy) and the contexts through which they emerge and evolve. In providing this explication, we have two main aims: (a) to advance our understanding of language learning in an increasingly technologised world, with a specific emphasis on mobile technologies, and (b) to develop innovative means for addressing the complexity of L2 learning phenomena that adequately account for individual variability and differing developmental trajectories. As noted by Verspoor et al. (2009), aspects of the publicly available linguistic environment are not uniformly noticed or passively absorbed by groups or

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communities. Rather, living persons variably interact with text, talk and other semiotic resources. This results in potentially divergent developmental processes where the ‘same’ input may be acted upon in different ways that are contingent upon a person’s immediate needs and goals. In this sense, the meaning-making experiences of persons in interaction with other persons form complex and adaptive systems that reorganise themselves based on the contingencies of the immediate goal-directed activity at hand. The chapter begins with an overview of the nature of the personcentred approach, including provisional definitions at the theoretical and methodological level, and the situation in which this approach could be used as a complementary or alternative tool to the standard variablecentred approach in the field of L2 research. It then discusses the methodological decisions essential for conducting person-centred research and presents an empirical study as an illustration of this method. The chapter concludes by highlighting issues believed to have important implications for future L2 research. Conceptual and Analytical Unit: From the Variable to the Person

There is consensus in the L2 field that learners exhibit differential success in their L2 learning. To elucidate why this is the case, abundant research has been conducted to investigate individual differences (ID) such as age, aptitude, motivation, emotion, learning belief and the use of learning strategies (see Dörnyei & Ryan, 2015). Studies have identified important factors that contribute to successful L2 learning, positively informing L2 research and pedagogy. However, quantitatively examining learners at the group level obscures learner diversity and can overshadow individual learning processes (Benson, 2019; Murakami, this volume). In addition, the dynamic nature of ID factors has gradually been acknowledged as non-stable, interconnected and contingent on context (Lowie & Verspoor, 2019), which problematises research methodologies that treat variables as inviolate conceptual and analytic units. Recent studies that have adopted a dynamic systems perspective have shown that L2 learning and use are unique to each individual (Bulté & Housen, this volume; Verspoor et  al., 2017). Different learners, even those who appear highly similar in terms of the factors/variables under investigation, tend to present distinct learning trajectories over time (Lowie & Verspoor, 2019). These individualised learning trajectories have been largely sidelined in the second language acquisition (SLA) field’s search for causal language learning variables at the group level (Larsen-Freeman, 2001). Although group studies remain useful for identifying factors influential for L2 learning and use, research efforts should equally attend to individual learning processes which involve the intricate interplay of learners’ individual attributes (e.g. motivation, emotion,

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aptitude and learning style) with the spatial-temporal contexts of human activity (e.g. Wind & Harding, this volume). This shift of focus from the variable to the individual ushers in a new person-centred era in L2 research (Benson, 2019; Larsen-Freeman, 2017). Person-Centred Approach: Theoretical and Methodological Levels

The person-centred approach views each individual as a dynamic system, with interwoven components jointly contributing to the process of individual development. By ‘components’, we mean, for example, learning behaviours, learning motivation, learner emotion and learning contexts. They are traditionally viewed as distinct variables influential for L2 learning, but in the person-centred approach they are used to construct individuals’ learning patterns and should be interpreted as constituted in relation to each other. In other words, this indivisibility of components is core to a person-centred perspective. This view is related to Complex Dynamic System Theory (CDST) thinking that has gradually been embraced in the L2 field. Four basic tenets of this approach are presented: (1) The process is partly specific to individuals. (2) The process is complex and is conceptualized as involving many factors that interact at various levels which may be mutually related in a complicated manner. (3) There is a meaningful coherence and structure (a) in individual growth and (b) in differences between individuals’ process characteristics. (4) Processes occur in a lawful way within structures that are organized and function as patterns of operating factors, where each factor derives its meaning from its relations to the others. Although there is, theoretically, an infinite variety of differences with regard to process characteristics and observed states at a detailed level, at a more global level there will often be a small number of more frequently observed patterns (‘common types’). (Bergman & Magnusson, 1997: 293) These four tenets describe a research focus on the individual and the associated phenomenal-experiential processes and practices associated with learning patterns. Specifically, each individual is seen as a functioning totality that can be studied by analysing his/her learning patterns. The identification of typically occurring patterns could reveal subgroups of learners who share those patterns. Searching for typical patterns has received considerable support from the study of language as a complex dynamic system. One characteristic of the language system is selforganisation, which refers to a process of spontaneous emergence of new patterns (van Geert, 2008) that arise from the interplay between learners’ internal and external attributes and resources. From this perspective, we could envision certain states (or what are called ‘attractors’) to occur

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more frequently than others, corresponding to the aforementioned typical patterns. Essentially, we could argue that understanding individual development, language development included, lies in a detailed examination at the individual level, with a focus on learning patterns. By way of classifying individuals with shared learning patterns into groups, distinct self-similar subgroups can be identified and a careful generalisation of individual cases can thus be made. Classification and Person-Centred Methods

As the person-centred approach values learning patterns and recognises them as the basic unit of analysis and interpretation, a focal subject of this approach is to classify individuals who share similar typical patterns into different groups (Bergman et al., 2003). Classification is a welcomed method in other fields, such as biology and psychology. For instance, individuals are often grouped into different personality types based on their shared traits (Csizér & Dörnyei, 2005). With regard to classification issues, several methods are available, but their central concepts usually remain isomorphic. One of the concepts is similarity. To classify learners/patterns based on similarity, one could consider cluster analysis (CA). As a statistical technique, CA can ‘provide a bottom-up way’ (Staple & Bieber, 2015: 243) of identifying non-overlapping clusters/groups wherein the individuals have similar typical patterns. The clustered learner groups diverge largely from the learner groups targeted in traditional group studies. In traditional group studies, it is the researcher who selects or creates learner groups based on preconceived categorisations, while person-centred methods identify learner groups composed of similar learning patterns that emerge from the data (Bergman & Magnusson, 1997; Lee et  al., 2018; Papi & Teimouri, 2014). In this section, the initial focus is on the clustering in the cross-sectional dimension, which is later used as a building block for longitudinal clustering. Cross-sectional clustering

L2 learning is a developmental phenomenon, and as we mentioned earlier, research should focus on the individual, the process and the learning pattern. It is also informative to analyse the learning patterns crosssectionally. By way of grouping L2 learners into different types based on their shared learning patterns, cross-sectional clustering provides a nuanced picture of learner complexity and diversity in a systematic manner. For example, Papi and Teimouri (2014) conducted a CA of L2 motivation with a view to identifying learner groups with distinct motivational types. The clustering procedure yielded five self-similar groups that varied in terms of their motivational configurations. They further

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identified how the five groups were different in their motivational, emotional and linguistic characteristics. The establishment of different learner types provides an approach for researching complex L2 phenomena with practical implications for L2 instruction. By acknowledging the typical patterns specific to each learner group, adaptive and personalised instruction compatible with the characteristics and needs of different learner types can thus be tailored and employed to gain optimal learning outcomes. We suggest more studies that adopt a clustering technique in research on L2 development. Longitudinal clustering

Although Papi and Teimouri’s (2014) study convincingly illustrated the applicability of person-centred methods (e.g. the CA) in L2 motivation research, they collected data indicating L2 learners’ motivational, emotional and linguistic states only at one time point, neglecting the fact that these learner attributes, from the dynamic perspective that their study took, may not be stable but rather fluctuate over time (Dörnyei et  al., 2014). The unstable nature of these attributes entails a process aspect to the person-centred approach, for example, the longitudinal CA. Longitudinal CA is often incorporated in situations where multiple data gathering occurs across time (Bergman & Wangby, 2014). As mentioned earlier, if we adopt the person-centred approach, L2 learning trajectories for individuals show variability since interacting attributes and resources are contingent upon local conditions and hence differ across individuals (Lowie & Verspoor, 2019; Verspoor et al., 2017). As such, the individual is at the core of understanding L2 learning and development and longitudinal case studies provide a significant source of insight into the L2 learning process (Lowie, 2017). Findings from cases that present shared longitudinal learning patterns can be aggregated and generalised. Ideally, a longitudinal data set with the same components measured at all time points would provide an accurate model of the individual’s complete learning patterns. However, in practice, a comprehensive, finegrained, longitudinal, person-centred analysis is not logistically feasible. Additionally, the results from numerous individual cases are often heterogeneous, hard to interpret and challenging to generalise from. A remedy for this might be a cross-sectional pattern analysis followed by linking over time (Bergman & Magnusson, 1997). First, crosssectional clustering of learning patterns could be carried out at each time point. What follows could be to link learner types/clusters at Time 1 to learner types/clusters at Time 2, and then a link between learner types/ clusters at Time 2 to those at Time 3 and so on. Between each adjacent pair of time points, cluster membership should be cross-tabulated to give information about cluster membership combinations that occur more often than expected by chance (so-called developmental types) and

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to look for individual stability (belongs to similar clusters at both time points) or dynamic changes. A case in point would be Piniel and Csizér’s (2015) examination of changes in motivation, anxiety and self-efficacy. By adopting a longitudinal clustering technique, they analysed whether persons in a given cluster remain in that group or jump to another cluster over time, the underlying idea being that ‘development is not always gradual (but is not always a matter of qualitative shifts, either) and development is clearly different between individuals, but also shows general patterns or prototypical trajectories’ (van Geert, 1994: 14) Therefore, the patterns of movement across clusters were called trajectories in their study. To capture the dynamic nature of the changes over time, Piniel and Csizér (2015) used the clustering results of the data collected at the first time point as the initial clusters for the second wave. In doing so, this study helped to unravel how interacting motivational, affective and cognitive factors shape learners’ distinct learning patterns over a semester and how the learning patterns change over time. Diverging from prior work that revealed a negative correlation between motivation and anxiety, Piniel and Csizér (2015) found the existence of different motivation–anxiety relations for different learner types. Specifically, a trajectory with high motivation and low anxiety was more typical and less variable than another trajectory wherein learners showed both high motivation and high anxiety. Their findings disavowed the linear relationship between variables that had been long-held in L2 research and rather illustrated the power interrelationship dynamic among various attributes (Lowie et al., 2017). This research suggests that a longer period of investigation with multiple points of data collection would yield a more intricate picture of developmental changes. Therefore, focusing on the learning process and applying longitudinal clustering analysis have the potential to provide insightful results, revealing the mechanism of multicausality and embedded and relationally constituted systems of L2 phenomena. Empirical Study: Latent Profiles of Mobile Language Learners Background

To elucidate how to apply an ecological person-centred perspective to L2 learning in today’s globalised and technologised world, we present an empirical example of clustering learners’ selective use of mobile technologies in their language learning. As a person-centred approach recognises language learning as a process of dynamic interactions between individuals’ internal (e.g. motivation, emotion and aptitude) and external (e.g. learning context) attributes and resources, it logically follows that language knowledge is related to learners’ everyday experience with goaldirected communication. With today’s easy access to mobile technologies, learners’ daily experience with language has expanded enormously.

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By taking this into account, the current study focuses on L2 learning and use that are mediated by mobile technologies outside the classroom. As emerging mobile technologies bring abundant opportunities for L2 learning and use, learners have immediate access to diversified and inexhaustible online resources that could serve to provide authentic language input, an essential element for L2 learning (Verspoor, 2017). Previous research has confirmed the effectiveness of mobile technologies in L2 learning (see Burston, 2015; Peng et  al., forthcoming; Sydorenko et al., 2019; see Sung et al., [2016] for meta-analyses), and examined the factors that moderate the effectiveness of mobile-assisted language learning (MALL) (e.g. Kim et  al., 2013; Xu & Peng, 2017). However, these explorations can only provide a partial and crude account of the nature of learners’ language learning with mobile technology (Lai et al., 2018). Examination of learners’ selective appropriation of mobile learning resources (i.e. their lived experience with mobile technology resources) might help to better understand the nature and quality of learners’ mobile language learning (Lai et  al. 2018). Acknowledging learners’ selective engagement with varied learning activities afforded by the mediation of mobile technology could also help teachers’ better integrate learners’ preferences with classroom instruction (Reinders & Benson, 2017). Therefore, the current study targets the investigation of learners’ engagement with learning activities that are mediated by mobile technologies. We applied Nation’s (2007) four-strands principle to guide our interpretation of these mobile learning activities, as this principle can ‘usefully be applied when learners take control of their own learning’ (Nation & Yamamoto, 2012: 173). In their perspective, a good language learner should allocate an equal amount of time to activities representing meaning-focused input (MFI; e.g. reading and listening), meaning-focused output (MFO; e.g. speaking and writing), language-focused learning (LF; e.g. vocabulary, grammar, pronunciation) and fluency development (FD; e.g. activities involving the use of known language knowledge). We thus categorised the activities into MFI, MFO, LF and FD. Considering that the MFI and MFO activities somewhat overlap with the activities of the FD strand in the mobile learning context (Nation & Yamamoto, 2012), we discuss FD in reference to a combination of MFI and MFO activities. This study specifically examines whether, and how, L2 learners differ in their selective use of mobile technologies for language learning. According to the person-centred approach, though each learner has his/her own distinctive motives, attitudes and favoured ways of processing language information, there are likely learners who share common attributes in their learning patterns. Therefore, the current study endeavours to identify the number and composition of distinct learner types. The establishment of different learner types constitutes a major contribution to L2 learning research, positively informing future L2 theory, research and pedagogical practice.

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Method

This is a two-stage study. In the first stage, by applying a clustering technique, we examined whether different homogeneous learner groups exist based on the similarity of their selective use of mobile technologies for language learning outside class, and uncovered the ways in which these clustered groups differ from each other. In the second stage, the group differences were further tested with measures indicating learners’ linguistic, motivational and emotional characteristics. As suggested by Alexander and Murphy (1999), a good way to confirm the validity of group differences would be by comparing the groups in terms of other independent variables. Sample and relationally constituted variables

This study was conducted at a university located in Southwest China, where learners have limited use of English for communication and the medium of class instruction is Chinese (i.e. their first language [L1]). A total of 238 learners participated in the study. They were all freshmen and averaged 19 years old, among whom 17 were English majors and the others were studying economics, horticulture, law, physics and veterinary medicine. The data were collected via a questionnaire. In addition to the varied learning activities learners engaged in, the questionnaire also collected information regarding another three factors: learning motivation, L2 anxiety and L2 proficiency. The ecological perspective employed in this study recognises learners’ mobile learning experience as a result of the interplay between different linguistic, affective and motivational factors, an idea which has been corroborated in Lai et  al. (2018). Since it is impossible to examine all relevant factors in one study, our selection of variables is based on theoretical and empirical evidence in the MALL field (Bergman & Trost, 2006). Previous research on MALL has found that technology mediation is effective in boosting learners’ motivation and alleviating their anxiety (González-Lloret, 2014; Lai et al., 2018; Ma, 2017; Ushioda, 2013). Additionally, learners’ L2 proficiency was also influential in their selective use of mobile technologies in language learning (Lai et al., 2018). All the variables of interest in this study bear strong association with MALL effectiveness (Elgort, 2018; Ma, 2017). We agree that other variables (e.g. cognitive factors; social networks) are also relevant to MALL effectiveness. However, here we only included variables that had undergone wide investigation in the MALL field. The questionnaire for data collection consists of three parts. Part 1 includes items regarding learners’ background information such as gender, educational level and L2 proficiency. L2 proficiency, also an indicator of learners’ linguistics state, was self-assessed by the participants based on a criterion-referenced, self-assessed checklist (Council of

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Europe, 2001). The checklist (DIALANG) was developed for learners who want to know their level of language proficiency and who want to get feedback on the strengths and weaknesses of their language proficiency. In this study, descriptive statements concerning reading, writing and listening ability were explained to the participants prior to their selfevaluation of L2 proficiency. A 6-point Likert scale was used for learners’ self-assessment, with 1 indicating very poor and 6 indicating very good. Part 2 concerns participants’ mobile learning experiences, encompassing all kinds of learning activities that are mediated by mobile technologies. Based on the aforementioned four strands principle, we categorised the activities into MFI (i.e. reading, listening), MFO (i.e. writing, speaking), language feature based (e.g. vocabulary, grammar, pronunciation) and FD (a combination of MFI and MFO). Part 3 includes items that measure learners’ motivational and emotional states. Motivation in the present study was operationalised in line with Dörnyei’s (2009) L2 Motivational Self System. The variables indicative of learner motivation and emotion include ideal L2 self, ought-to L2 self, L2 learning experience, motivated learning behaviour and L2 anxiety. • Ideal L2 Self: Indicating learners’ aspiration and desire for language learning (5 items, α = 0.894). • Ought-to L2 Self: Measuring ‘the attributes that one believes one ought to possess (i.e. various duties, obligations or responsibilities) in order to avoid possible negative outcomes’ (Dörnyei & Ryan, 2015: 106; 6 items, α = 0.856). • L2 Learning Experience: Concerning the attitudes related to the immediate learning environment (here, mobile technologies; 6 items, α = 0.866). • Motivated Learning Behaviour: Examining the regulation of one’s learning behaviour (8 items, α = 0.884). • L2 Anxiety: Measuring learners’ uneasiness and discomfort with using English (8 items, α = 0.889). Items concerning the learning routine were constructed in reference to the current literature on L2 learners’ MALL engagements (e.g. Lai et al., 2018; Ma, 2017; Stockwell & Hubbard, 2013) and fine-tuned in consultation with experienced English teachers in China (e.g. Facebook, Twitter, YouTube, etc. can only be accessed via a VPN connection in Mainland China and hence are sidelined in the questionnaire). Participants were asked to select specific learning activities in relation to reading, listening, writing, speaking and language features (e.g. grammar, pronunciation and vocabulary) and to select the average time per day they engaged in these different aspects of mobile learning outside the classroom. Items indicative of participants’ motivation and emotion were mostly adapted

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from Papi and Teimouri (2014), and some were newly added, taking account of the mediation of mobile technologies (Stockwell & Hubbard, 2013). A 6-point Likert scale was used to measure the items, with 1 indicating strongly disagree or not at all and 6 indicating strongly agree or very much. The questionnaire version was fine-tuned with a pilot study. Data analysis and findings

The data concerning participants’ learning experience were clusteranalysed using R 3.5.0. From an ecological perspective, learners’ learning experience is an outcome of the interaction between learners’ individual attributes (e.g. motivation, emotion, language proficiency) and the spatialtemporal context (Lai et al., 2018). CA is a multivariate exploratory technique used for identifying new groups in a bottom-up manner. It is useful in cases where there is extensive variation among individual cases (e.g. L2 learning processes) (Dörnyei, 2014; Staples & Biber, 2016). Two types of clustering are often employed: hierarchical CA (HCA) and disjoint CA. Disjoint clustering is conceptually simpler in that the researcher determines how many clusters he or she wants. HCA, in contrast, produces a hierarchical structure wherein distinct clusters emerge by themselves. The current study applied the HCA procedure, which led to the emergence of self-similar groups without predetermining the group number. Six clusters emerged from the procedure (descriptive results are presented in Table 4.1). Significant differences between the clustered groups were checked using one-way analyses of variance (ANOVAs). The group differences were further tested on variables indicative of learners’ motivational, emotional and linguistic characteristics (Alexander & Murphy, 1999), as shown in Table 4.2. Additionally, close examination of the specific activities each group engages in also revealed distinctive learning patterns. As a result, it was decided that the six clustered groups exhibited meaningful distinctions and the learners in each group were strongly self-similar. Table 4.1  Descriptive results of the six clustered groups Groups (n)

Group 1 (53) M (SD)

Group 2 (74) M (SD)

Group 3 (18) M (SD)

Group 4 (16) M (SD)

Group 5 (49) M (SD)

Group 6 (28) M (SD)

Reading

1.06 (0.23)

2.69 (0.93)

1.61 (0.77)

4.38 (0.95)

3.45 (0.58)

4.14 (0.80)

Listening

1.53 (0.69)

2.39 (0.77)

4.50 (1.09)

4.31 (0.87)

3.10 (0.62)

4.79 (0.63)

Speaking

1.23 (0.54)

1.72 (0.60)

2.67 (1.13)

1.69 (0.79)

3.04 (0.49)

3.82 (0.72)

Writing

1.15 (0.41)

1.62 (0.59)

2.33 (1.13)

2.31 (0.87)

3.16 (0.62)

3.54 (1.13)

Language features

1.28 (0.53)

2.08 (0.85)

2.11 (1.13)

3.25 (0.93)

3.43 (0.67)

4.32 (0.90)

Note: The value was based on a 6-point Likert scale, with 1 = no time spent; 2 = less than 10 minutes every day; 3 = 10 minutes to half an hour every day; 4 = half an hour to 1 hour every day; 5 = 1 to 2 hours every day; and 6 = more than 2 hours every day.

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Table 4.2  Descriptive results of each group’s linguistic, motivational and emotional states Groups (n)

Group 1 Group 2 Group 3 Group 4 Group 5 Group 6 (53) M (SD) (74) M (SD) (18) M (SD) (16) M (SD) (49) M (SD) (28) M (SD)

L2 proficiency

2.73 (0.79)

2.90 (0.79)

3.10 (0.65)

3.40 (0.96)

3.27 (0.66)

3.56 (0.62)

Ideal L2 self

3.47 (1.26)

3.52 (1.00)

3.72 (1.31)

4.32 (1.19)

3.74 (1.05)

4.14 (0.77)

Ought-to L2 self

2.82 (0.95)

3.02 (0.98)

2.92 (1.06)

3.17 (1.32)

3.00 (0.91)

2.86 (1.08)

Attitude

3.02 (0.90)

3.50 (0.72)

3.63 (1.09)

4.16 (0.67)

4.05 (0.88)

4.28 (0.84)

Motivated behaviour

3.46 (0.96)

3.87 (0.76)

4.02 (1.03)

4.16 (0.62)

4.31 (0.89)

4.20 (0.72)

L2 anxiety

3.97 (1.16)

3.75 (0.91)

3.77 (0.75)

3.42 (0.85)

3.53 (0.87)

3.14 (0.79)

Generally, learners in one of the clusters (Group 1) had the lowest scores in almost all language activities, which means that learners in this group spent little time learning English outside class. According to the four strands principle, to learn a new language well, learners should allocate equal and considerable amounts of time to MFI, MFO, LF and FD activities (Nation & Yamamoto, 2012). Since learners in Group 1 lacked adequate practice in all language aspects, this group was labelled the –MFI, –MFO, –LF and –FD group. This is also the group that presented the lowest levels of language proficiency and learning motivation, but showed the highest level of anxiety. One possible explanation is that learners in this group did not see the relevance of English in their daily life or in their future life, and they did not enjoy English learning but rather regarded it as a school obligation (McCarty et al., 2017). Another cluster (Group 2, henceforth the +MFI, +MFO, +FL and +FD group), though also spending little time practicing speaking and writing, was slightly different in that learners in this group devoted about half an hour every day to reading, listening and vocabulary learning, respectively. Of all the learners surveyed in this study, 31% belonged to this group, representing a large portion of English as a foreign language (EFL) learners in China. They had a relatively large amount of language exposure but limited use of English for communication. This receptive nature of language learning usually leads to a large observed gap between their comprehension and production (Wen, 2016). A similar learning pattern was found in another cluster (Group 4, henceforth the ++MFI, –MFO, +FL and ++FD group), except that learners in Group 4 engaged in MFI activities to a larger extent. That is, though they spent little time on speaking and writing, learners of this group practiced their reading and listening for one and a half hours every day, respectively, and then learned vocabulary, grammar and pronunciation for another half an hour. This learning pattern (i.e. with a particular focus on receptive skills and language features) might be ascribed to Chinese students’ learning style. It is widely acknowledged that students from Confucian heritage

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cultures such as China and Japan are often found compliant and receptive in their language learning (McCarty et al., 2017). Although learners in Groups 2 and 4 had a similarly high level of anxiety, they diverged in their language proficiency and learning motivation. It appears to be case that learners’ engagement with learning activities is positively related to their proficiency and motivational levels, which mirrors Ma’s (2017) findings in her multi-case study. Ma (2017) examined how mobile technologies mediate Hong Kong college students’ L2 learning, and found that students’ selective use of varied e-resources and tools was an outcome of the interaction of an array of factors, such as language proficiency, learner motivation, learning belief, study discipline, personal interests and goals (see also Lai & Zheng, 2018). An ideal learning pattern (i.e. in line with the four strands principle) was found in another cluster (Group 5, henceforth the +MFI, +MFO, +FL and ++FD group). Learners of this group distributed comparable amounts of time (about half an hour every day) to learning each language aspect, which indicates that learners here have equally practiced their reading, listening, writing, speaking and language features, with the help of mobile technologies. Again, a similar pattern was observed in a related cluster (Group 6, henceforth the ++MFI, ++MFO, ++FL and +++FD group). Learners in this group performed all kinds of learning activities to a larger extent; that is, this is the group that committed the largest amount of time to practicing each strand of activities: about two hours every day on MFI (i.e. reading and listening), two hours on MFO (i.e. speaking and writing) and one and a half hours on LF (i.e. vocabulary, grammar and pronunciation). Interestingly, the learners in Groups 5 and 6 were similar not only in their learning pattern, but also in their linguistic, motivational and emotional characteristics. The main difference between the two groups lay in their engagement with specific learning activities. Learners in Group 6 were more traditional and less creative in their selection of specific language learning activities. For instance, they relied very much on watching videos, listening to audio and searching e-news websites as efficient ways to improve their English. Learners in this group were also more goal oriented and conscious of ‘what and how to learn’ (Ma, 2017: 201), and sought out activities that could meet their needs and interests (Wrigglesworth & Harvor, 2018). Diverging from this, learners in Group 5 displayed a higher level of curiosity and awareness of the affordances of mobile technologies as well as the potential resources available (Demouy et al., 2016). In other words, learners in Group 5 showed more dynamism in their choice of learning activities enabled by mobile technologies. For instance, they liked to practice writing via online forum discussion, and were willing to use WeChat Public Platforms to practice their reading, listening and language skills. As mobile technologies advance rapidly, this group might benefit more from the appearance of new resources and mobile activities. Previous

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studies (e.g. Lai & Gu, 2011) revealed a limited use of web 2.0 technologies in language learning. According to our study, it makes sense to empower this group of learners with more meta-cognitive, self-regulating capabilities to embrace web 2.0 technologies. The distinction between Groups 6 and 5 also mirrors different views on language learning (a more conservative view versus a more open and socially integrated one). Although both are forms of language learning outside class, the former seems to reflect more how learners learn in class while the latter is more likely to be a form of social learning. Although it is not necessarily the teacher’s responsibility to organise learners’ mobile learning outside class, teachers may also be able to help learners develop a more integrated view of traditional learning and innovative learning, thus better exploiting the learning potential of emerging mobile technologies (Kashiwa & Benson, 2018). One more cluster emerged in our data, Group 3 (henceforth the ++listening, +MFO, +FL and ++FD group). Learners in this group spent about half an hour every day on the MFO and LF strands. What surprised us was their overemphasis on listening. They had allocated about one and a half hours every day to listening to English materials. Looking closely at their preferred activities, listening to English songs stood out, which corroborated the view that ‘learners have their preferred channels to receive and process learning resources, in the form of online reading (textual), videos (visual) or songs (auditory)’ (Ma, 2017: 198). Students who listened primarily to music also illustrate the potential of popular culture resources for language learning (Dubreil & Thorne, 2017). By adopting a clustering technique, this study revealed six distinct learner types whose learning patterns were mediated differently by their selective use of mobile technologies. It also presented how these differential learning patterns were related to their motivational, emotional and linguistic profiles. In doing so, we were able to extend previous general conclusions that mobile technologies can potentially facilitate learners’ language learning (e.g. Burston, 2015), minimise their fear of embarrassment and raise their motivation for language learning (e.g. Ma, 2017). It further elucidated how learners’ attributes (e.g. motivation, emotion and language proficiency) interact with different mobile technologies to give rise to differential learning patterns that are specific to each learner type. In other words, the application of clustering techniques can help to shed light on the latent learner types that can easily be overshadowed by the average-oriented data obtained at the group level. There are also limitations to this study. The observation of six mobile learner types in the study was based on a sample of college EFL learners in China. More studies that adopt the clustering technique but target other socio-educational contexts are called for. In addition, although large-scale surveys and questionnaires have been considered valuable research tools to generate and test hypothesis, the data obtained are often self-reported and retrospective in nature, which may not accurately

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reflect learners’ attributes. Future research that integrates and triangulates the data from questionnaires with more objective measures of L2 proficiency would yield more robust results. Last but not least, this study adopted the HCA to cluster the participants into different groups. But there are weaknesses inherent in this technique (e.g. it does not work with missing data; it works poorly with mixed data types; it does not work well on very large data sets; and its main output, the dendrogram, is commonly misinterpreted). As such, future research dealing with mixed data types or very large data sets might consider applying better alternatives such as latent class analysis. Implications

This empirical study has several implications for future L2 research and pedagogy. First, L2 learning, from a person-centred approach, should be understood at the individual level as a process of many interrelated components jointly contributing to, and co-evolving throughout, the developmental process. Research describing and explaining individual trajectories of observed sub-system components and the clustering procedure described in this study could also be applied to diachronic developmental processes, with a view to identifying ideal-typical trajectories and factors that account for the change or stability of these trajectories. Second, we suggest that the clustering procedure we discussed above could complement standard variable-centred analysis of experimental data. Prior to an intervention or a treatment, researchers could first issue a series of pre-tests and questionnaires to collect data on IDs and could use clustering techniques to ascertain if the participants/learners can be clustered in meaningful ways (see Staples & Biber [2015] for similar suggestions). Researchers could then examine possible interaction effects between different learner types and the intervention, which could provide valuable findings regarding personalised instruction and the design of more effective learning materials, tools and task types. Third, a person-centred study could also be appropriately viewed as a needs analysis for task-based language teaching (TBLT) and research (González-Lloret, 2014). The design of a TBLT curriculum, as proposed in Norris (2009), begins with an analysis, ideally multi-methodological, of learners’ needs, wants and goals (see also Long, 2005). The clustering technique could potentially reveal learner types and their distribution, all profiled with distinct cognitive, motivational, emotional and linguistic characteristics, which together further lays the foundation for identifying pedagogical tasks L2 learners could perform to amplify their learning potential. Fourth, as learners’ use of mobile technologies in language learning potentially blurs the boundary of formal and informal learning, acknowledging the existence of different learner types with distinct mobile-assisted learning patterns could help L2 teachers design a better

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integration between their in-class guidance and learners’ autonomous learning outside class (Wong et  al., 2015), which mirrors Thorne and Reinhardt’s (2008) call for bridging activities that incorporate learners’ digital expertise, experience and curiosity with instructor guidance and hence helps educators to engineer optimal conditions for language learning (see also Reinhardt & Thorne, 2019). Collectively, a teacher’s job is no longer to teach but to create environments that maximise learners’ agentive role in language learning and which ecologically align with their personal interests and present as well as future needs (see Kassenberg et al., this volume, for details on practice). Future Directions and Conclusion Theoretical implications of the ‘person-centred’ approach

To clarify the definition of person-centred, a clear distinction should be made between the theoretical and methodological aspects of the person-centred approach. Terms such as ‘cluster analysis’ (e.g. Papi & Teimouri, 2014) or ‘clustering technique’ (e.g. Lee et  al., 2018) only imply the person-centred approach by the method it uses, ignoring the theoretical dimension. The person-centred approach, as proposed in this chapter, is grounded in the ecological dynamic paradigm (de Bot et al., 2007; Larsen-Freeman & Cameron, 2008), which recognises L2 learning as an individual learner’s use of language in a spatial-temporal context (Larsen-Freeman, 2017). This recent focus on individuals in context has been described as the era of ‘person-centredness’ by Benson (2019), which he contrasts with earlier eras such as ‘the invisible learner’ and ‘learner-centredness’. A person-centred approach understands L2 learning, use and development at the individual level by regarding each learner as a functioning whole with its components (e.g. cognitive, affective, motivational and linguistic) jointly contributing to what happens in the developmental process. Given that the number of interacting components and the way they interact are usually different for different learners, L2 learning trajectories often differ across individuals (Lowie & Verspoor, 2019; Verspoor et al., 2017). Reconsidering issues of data aggregation

Conventional research on L2 learning is often based on group studies with an assumption that results obtained at the group level can be generalised to each individual. However, the person-centred perspective eschews the practice of overdetermined generalisation, as learning patterns are often found to differ across individuals and contexts. The proposed invalidity of generalising group findings to the individual is elaborated in Lowie and Verspoor’s (2019) discussion on the ergodicity problem. Lowie and Verspoor (2019) argued that the generalisation of group observations across individuals can only be made under two

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conditions: that the learner group is homogeneous and each individual’s learning process remains stable. In view of the individualised nature of L2 learning, both conditions are likely to be violated, as ‘a randomized group is most probably not homogenous and the data are not stable’ (Lowie & Verspoor, 2019: 192). Rather than using aggregated data with the whole group, our suggestion is to identify distinct and arguably self-similar subgroups. Molenaar and Campbell (2009: 116) similarly suggest that generalisation to the wider population can possibly be achieved ‘through the identification of subsets of similar individuals’. This type of generalisation begins with identfiying different learner types, with similar individuals in each type. As such, the findings of each identified subgroup could possibly be proximally generalised to the individual within it. However, this is not to say that a standard variable-centred study at the group level is inferior to the person-centred approach. While research efforts are still needed to identify new variables influential for successful L2 learning with group studies, research focus should also include examining the individual in context by taking a person-centred approach. The need for intensive studies of individual development

When individual development is the focus, it is not evident that the conventional longitudinal approach, which is often characterised as group based and with relatively few measurement points, is adequate. To better illuminate details of individual development, it is necessary to study the dynamics of change in the developmental process. To achieve this, Lowie (2017) proposes longitudinal case studies with intensive (frequent) and temporally arrayed sampling. We acknowledge that intensive data collection with many measurement points is logistically difficult to obtain, which further restricts the learners who can be included in such research. A good compromise, as exemplified in Lowie and Verspoor (2019), would be to embed a small sample of intensively studied persons within a conventional group study. The group study could provide valuable information about the relative weight of individual variables that are influential for L2 development, while the longitudinal case studies shed light on the process of individual development, and potentially, can visibilise relatively homogeneous ideal-typical subgroups. The application of an ecological and person-centred approach means not rejecting but rather complementing the L2 frameworks developed in recent decades so as to optimally respond to the realities of our highly mobile, globalised and digitalised world, in which millions of people endeavour to learn new languages in different instructional settings and for different reasons. Ultimately, we hope to draw from descriptively oriented longitudinal case studies and cluster analyses in order to better engineer conditions for language learning, both within and outside of instructional settings.

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5 Creativity and Routinisation in L2 English: Two Usage-Based Case Studies Søren W. Eskildsen

This chapter investigates usage-driven creativity and routinisation over time in second language (L2) English (for a recent overview of usagebased L2 research, see Cadierno & Eskildsen [2015]). The chapter adopts the traceback methodology from child language studies (Lieven et al., 2009; Vogt & Lieven, 2010), a method which allows researchers to tease out and explore the constructional fabric and thereby emergent creativity and routinisation in language users’ linguistic repertoires. This research has shown that children’s emergent repertoires consisted of formulas and utterance schemas, and that only a few basic syntactic operations accounted for early syntactic creativity. Applying the traceback procedure to the L2 data revealed that the syntactic operations identified by Lieven and colleagues, especially substitution of semantically similar items in open slots in recurring constructions, also apply to beginning adult L2 learning (Eskildsen, 2014, 2017). Recycled routinised formulas and novel utterances based on utterance schemas and the substitution operation accounted for more than 85% of my focal student’s production, indicating that recycling is important in L2 learning and that emergent creativity is exemplar based and heavily dependent on routinisation. This chapter summarises these previous traceback studies in L2 learning and brings the findings to bear on a new focal student. Moreover, through local analyses of the usage-based learning of specific constructions, the chapter demonstrates that situated activities have an impact on the dynamic development of creativity and routinisation in L2 learning. The data come from the Multimedia Adult English Learner Corpus at Portland State University and span several years. Introduction

Drawing on a construction-based view of language and a view of language learning as an exemplar-based process of inferring schematic 107

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similarities among encountered formulas and utterance schemas (i.e. formulaic frames), this chapter reports and expands on a series of ongoing investigations into emergent creativity in second language (L2) English (Eskildsen, 2014, 2017). In these previous publications, I have investigated emergent creativity in terms of L2 speakers’ expansions of their L2 repertoires in and through talk in an English as a second language (ESL) classroom. The interest has grown from usage-based studies that investigated specific constructions in L2 development and documented and discussed L2 learning over time in terms of an exemplarbased process where the L2 user is constantly developing a repertoire of interrelated constructions on the basis of recurring exemplars (Ellis & Ferreira-Junior, 2009a; Eskildsen, 2009, 2011, 2012, 2014, 2015, 2017, 2018b; Eskildsen & Cadierno, 2007; Eskildsen et al., 2015; Li et al., 2014; Kassenberg et  al., this volume; Larsen-Freeman, 2015; Mellow, 2006; Roehr-Brackin, 2014; Yuldashev et al., 2013). The objective has been to put these substantiated usage-based assumptions about L2 learning under further empirical scrutiny – to discover the empirical fabric of the claim that entire L2 repertoires emerge out of countless occasions of experiencing and using the L2. By entire L2 repertoire, I do not mean to imply that I have empirical access to all linguistic experiences of the L2 users in my data; rather, what I wish to convey is that I look at the entirety of L2 users’ production as it has been captured on recordings and trace the natural history of the emergence of all linguistic patterns in their production at distributed points in time rather than a priori choosing to look at one or a few specific linguistic constructions and their ontogenesis. The key issue, then, is to investigate how a creative linguistic repertoire comes into being on the basis of concrete recurring linguistic material in use, following a trajectory from specific recurring multi-word expressions (MWEs) to partially fixed, partially schematic utterance schemas to increasingly schematic constructions based on systematic commonalities among patterns (e.g. Ellis, 2002; Tomasello, 2003). This bears with it a rejection of the compartmentalisation of language into (i) something that is listed in the mental lexicon, swiftly processed and stable; and (ii) something that is rule governed, cognitively demanding and flexible (Eskildsen & Cadierno, 2007). Instead, language knowledge is shown to be a structured inventory of symbolic units, i.e. form-meaning pairings (Langacker, 1987) of varying complexity and abstraction. The units vary in size from morphemes to full expressions and range from the totally specific to the maximally general, allowing for the co-habitation in the grammar of abstract schematised representations and their concrete instantiations (e.g. Achard, 2007; Langacker, 2000). The ontological status of constructions as form-meaning pairings in L2 learning has been empirically supported (e.g. Bartning & Hammarberg, 2007; Collins & Ellis, 2009; Ellis & Ferreira-Junior, 2009a, 2009b; Ellis et  al., 2013; Goldberg & Casenhiser, 2008; Gries & Wulff, 2005, 2009; Robinson &

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Ellis, 2008; Waara, 2004) and usage-based perspectives have been gaining rapid attention within second language acquisition (SLA) research (Cadierno & Eskildsen, 2015; Douglas Fir Group, 2016; Ortega, 2014). More recently, initiatives have been taken to go beyond the concept of formmeaning pairings to understand the more fundamental relation between linguistic expressions and the actions that the expressions can be used to accomplish. This enterprise is rooted in the notions that function shapes language and its learning and that language is primarily used for social action. This is in full alignment with usage-based endeavours – but it has necessitated the complementation of usage-based approaches with a theory of social action, namely conversation analysis (Eskildsen, 2018a, 2018b, 2020; Eskildsen & Kasper, 2019; Pekarek Doehler, 2018). This chapter expands on the body of longitudinal usage-based L2 research by exploring the specific ways in which linguistic creativity emerges in L2 learning. To achieve this, I draw heavily on Eskildsen (2014, 2017) in which I adopted the traceback methodology from child language studies (Dabrowska & Lieven, 2005; Lieven et al., 2003, 2009; Vogt & Lieven, 2010; cf. also Yuldashev et  al., 2013), a method which allows researchers to tease out and explore the constructional fabric of emergent grammars in terms of the ways in which constructions put to use are related to other constructions in the inventory across time. The method reveals the ways in which constructions in particular speakers’ language use are related to other constructions in the same L2 speakers’ repertoires at particular points in time and across time by way of tracing actual utterances backwards in longitudinal developmental data. This method thus presents a window onto the anatomy of the linguistic inventory across time and investigates the relationship between creative and routinised aspects of it. As will be shown, emergent creativity is rooted in experience, it grows slowly from affordances and from the speakerʼs amassed repertoire of constructions through use. One of the central dogmatic tenets of linguistics in the 20th century, namely that language is creative to such an extent that every time we encounter an utterance or sentence it will be something we have never encountered before is simply wrong; instead, speakers reuse what is around them, and every time they speak, they say something that has been said in exactly the same or a slightly different way before (Hopper, 1998). In addition to this mapping of the emergence of linguistic repertoires, Eskildsen (2017) took a closer look at how the process of constructing a linguistic inventory is something learners actively do as they are figuring out the language (Ellis, 2002). In this part of the exploration, I drew on conversation analysis and showed how the L2 speaker’s learning and diversification of usage of a construction, centred on the verb need, was dependent on a range of moments of ‘noticing’ in ‘language-related episodes’ (Swain & Lapkin, 1998) and private speech instances (Lantolf, 1997; Ohta, 2001). In this chapter, I also take a further look at some

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interactional detail, but here the focus is on the specifics of (1) how a linguistic expression grows iteratively from context (de Bot et al., 2007) and (2) how another linguistic expression is routinised as a tool for performing social action (Eskildsen & Kasper, 2019). Before launching into the study, a word on the relationship between creativity and routinisation is in order. This is a discussion I have undertaken before – e.g. Eskildsen (2009, 2017) and Eskildsen and Cadierno (2007) – so there will be some repetition here. In SLA, the discussion also goes back a long way – a much longer way, of course! – often in terms of the antagonistic pair ‘formulaic expressions’ and ‘creative grammar’ (e.g. Ellis, 2012; Myles et al., 1998, 1999; Nattinger & De Carrico, 1992; Pawley & Syder, 1983; Weinert, 1995). As I have argued previously, because usage-based approaches do not compartmentalise language into what is ‘formulaic’ and what is ‘creative’, what is formulaic and what is not should be seen as a matter of degree of abstraction and creativity rather than a question of either-or. Empirically, usage-based L2 research has accounted for the ways in which reused material in the form of recurring MWEs feed into the rest of the emergent L2 on the basis of frequency and form the backbone of schematisation (e.g. Ellis, 2002; Ellis & FerreiraJunior, 2009a, 2009b; Eskildsen, 2012, 2014, 2017; Eskildsen & Cadierno, 2007). One issue that remains unsettled, I think both theoretically and empirically, is the role played by the emergent L2 as a system. There is certainly a systemic notion to Langacker’s cognitive grammar and his ‘structured inventory’ or ‘assembly’ (Langacker, this volume) of symbolic units – arguably, the primordial root of usage-based linguistics. But Langacker’s is not a theory of learning or development and so it is questionable whether ‘structured inventory’ is the most apt way of talking about an emergent language. It is generally agreed across usage-based approaches, including emergentism and dynamic systems theory, that language learning is a moving target, and development is dynamic, nonlinear, fluid, environmentally dependent and iterative (e.g. de Bot et al., 2007; Eskildsen, 2009; Eskildsen & Wagner, 2018; Larsen-Freeman, 2006, 2007, 2015; MacWhinney, 2006; Murakami, this volume; Sulis et al., this volume; Wind & Harding, this volume). I sympathise with the notion of piecemeal learning of constructions and the ensuing system as something that is abstracted from these through experience (Ellis, 2002). However, investigating these things empirically, my focus remains with the learning of linguistic patterns that I can actually observe. And in this light, the ensuing system becomes less interesting because it is less visible – if visible at all. One might take this to be in agreement with Hopper’s (1998) view of grammar as epiphenomenal, a view with which I am very comfortable. My perspective, then, is that a ‘language system’ may emerge – but as Larsen-Freeman and Cameron (2008: 116) put it, ‘it is not a single homogenous construct to be acquired’. Keeping that in mind, in addition

Creativity and Routinisation in L2 English  111

to the point that language learning is too complex to allow for brief definitions (Eskildsen, 2014, 2017), my interest lies in how people build their L2 capacities in and through use, primarily social interaction because that is the bedrock of human sociality and the preeminent environment of language use. I use the term ‘L2 repertoire’ (Eskildsen, 2018a; Hall, 2019) to denote that it is something people use for specific purposes, to foreground the experiential nature of its emergence and to imply that it consists of resources that are more or less loosely connected and that its sum may conspire to form an entity with some degree of systematicity. The chapter is organised as follows: After an introduction to the database, the traceback method is outlined. Then, the results from the traceback procedure are presented in order to show what emergent L2 creativity looks like from a usage-based perspective. Subsequently, a closer look at some instances from the data allows for tracing the specifics of how a linguistic expression grows as a tool for performing social action. Data

The data source for this study is the Multimedia Adult English Learner Corpus, which consists of audio-visual recordings of classroom interaction in an ESL context. The classrooms in which the recordings were made were equipped with ceiling-mounted video cameras and microphones, and students wore wireless microphones on a rotational basis; the teacher also wore a microphone (Reder, 2005; Reder et  al., 2003). All students signed consent forms before participating in the recordings. The present research is based on two students, Valerio and Carlos (pseudonyms), who were adult Mexican Spanish-speaking learners of English. Carlos had been in the United States for 21 months and Valerio for 9 months before joining the ESL programme, and both students progressed successfully through the levels assigned to their classes by Portland Community College (PCC), referred to locally as Levels A, B, C and D. According to PCC, the levels span from beginner to high intermediate (see Reder [2005] for more details). The final database of the present inquiry consists of transcripts from the sessions in which Valerio and Carlos were either wearing a microphone or sitting next to someone wearing a microphone. In addition, the sessions in which the focal students took part but were not assigned to wear microphones were viewed for any interactions involving Carlos or Valerio that might have been picked up by the generic microphones (Eskildsen, 2014, 2015, 2017). The full database was divided into four recording periods (henceforth RPs) for each student, as outlined in Table 5.1 (note that both Carlos and Valerio took time off from school, e.g. due to paternity leave, hence the gaps).1 The division into RPs reflects that in Eskildsen (2017). In the interest of space, this chapter focuses on the early emergence of creativity and

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Table 5.1  Overview of focal students’ time in class RP

Valerio Dates

Level

Carlos Dates

Level

1

June 24–Aug. 15, 2003

B

Sept. 27–Nov. 29, 2001

A

2

Sept. 23–Nov. 25, 2003

B

Jan. 7–June 7, 2002

B

3

Jan. 13–Aug. 10, 2004

C

Sept. 23, 2003–March 12, 2004

D

4

June 21–Aug. 11, 2005

D

Sept. 30, 2004–March 3, 2005

D

Note. RP = recording period; level refers to Portland Community College’s programme levels.

routinisation. In terms of the levels assigned to the students by PCC, the focus is on Levels A and B – RP 1 and 2 for the two students. The more advanced levels that are not covered here are marked bold in Table 5.1. For a discussion of how the traceback methodology can be applied to data at more advanced levels of learning, see Eskildsen (2017). Method Traceback procedure in child language studies

Methodologically, as outlined in Eskildsen (2014, 2017), the modus operandi is inspired by Dabrowska and Lieven (2005), Lieven et al. (2003, 2009) and Vogt and Lieven (2010) in which the researchers reported on usage-based investigations of syntactic creativity in early child language. Referring to their method as ‘traceback’, the researchers used densely sampled longitudinal data sets of recordings of four two-year-olds to investigate how closely related the children’s utterances at the end of the RP were to their previous utterances. Their basic finding for the four children was that 78%–92% of their target utterances (utterances at the end of the RP) were either verbatim repetitions or traceable to previous utterances by recourse to one specific syntactic operation, called ‘substitution’. If, for example, a target utterance was I got the butter and the closest match was recognised as I got the door, the syntactic operation identified to be required for producing the novel utterance was substitution (of the object). The underlying construction sanctioning this operation was thought to consist of a fixed part and a flexible part: I got the + an open slot for the insertion of lexically apt material. The authors thus found a high degree of linguistic routinisation in their focal children, thereby confirming the results from MacWhinney (1975), the primordial empirical work showing that children’s evolving grammars are item-based. Traceback in the present study

The methodology has been modified to fit the present data because these data were collected over a longer time span (Eskildsen, 2014, 2017). I divided my focal students’ participation in the ESL classroom into RPs

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Table 5.2  Data collection periods, main corpora and test corpora, RP1 and RP2, Carlos Period

Main corpus

Test corpus

Number of utterances

RP1

Sept. 27–Nov. 8, 2001

Nov. 19, 26 and 29, 2001

274

RP2

Jan. 8–June 7, 2002

May 17, 21, 24, 28 and June 7, 2002

295

Table 5.3  Data collection periods, main corpora and test corpora, RP1 and RP2, Valerio Period

Main corpus

Test corpus

Number of utterances

RP1

June 24–Aug. 15, 2003 Aug. 12 and 15, 2003

361

RP2

Sept. 23–Nov. 25, 2003 Nov. 18, 21 and 25, 2003

374

that constitute the traceable databases, the main corpora. At the end of each period, I made a baseline point consisting of two to six classroom sessions from which I drew the target utterances (i.e. those to be traced), the test corpora. The reason for the difference in amounts of sessions (dates) for collecting the test corpora is that I aimed for roughly the same number of target multi-word utterances (MWUs) to be traced. The data collection periods with main and test corpora and the number of traced utterances are shown in Table 5.2 (Carlos) and Table 5.3 (Valerio). MWUs were defined either interactionally or prosodically, i.e. with respect to points of speaker-transition where the next speaker takes the floor, or with respect to intonation patterns and pauses in Carlos’ and Valerio’s talk. For example, I get up at 7 o’clock and I take a shower followed by a response, for example mhm, would be counted as one MWU, and turns at talk such as I’m gonna go back. go back where there are two distinct intonation patterns and a pause between I’m gonna go back and go back would be counted as two MWUs. Utterances with embodied completions were also included (Olsher, 2004).2 Having identified the MWUs at each baseline point, I then traced them backwards in development in order to discern the interplay between routines and creativity in L2 development.3 Tracing was always done in a lexically specific manner. All MWUs in the test corpora were thus traced to identify their closest matching utterances. A closest match was either the exact same string – a fixed MWE (cf. the Introduction) – or a string that differed from the target utterance in one or more slots in the construction, which was then labelled an utterance schema; a mixed construction, consisting of a fixed and a variable part. The variable part is an open slot for the insertion of semantically relevant material and can be established if slots are filled by semantically similar slots in the schema over time (Lieven et al., 2009). The identified slots are outlined and categorised in Table 5.5. The more slots that need filling to arrive at a target utterance from the closest match, the more creative the construction can be said to be. Once the MWUs to be traced had been identified in the test corpora,

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the first step in the tracing process, following Lieven et al. (2009), was to identify recurring chunks, i.e. fixed MWEs, in the data and then to identify and count the utterances that varied in one or more pattern slots from their closest matches and to categorise the slots semantically. Summary of Results: Carlos (Eskildsen, 2017)4

This section summarises the results of the traceback procedure as applied to Carlos’ data and will be used as a template to perform the same analysis of Valerio’s data in the following section. The first step in the tracing procedure was to match the target utterances with previous utterances. In this process, it became necessary to make an initial distinction between simple and complex traces. Simple traces applied when utterances could be traced to one previously occurring singular utterance, either a fixed string, i.e. an MWE, or an utterance schema with one or more open slots, and complex traces applied when the tracing had to be carried out a number of times corresponding to the number of utterance schemas to which the target utterance was traced. As Table 5.4 indicates, one-to-one traces and simple traces far outnumber complex traces; in RP1, 243 out of 274 target utterances (88.7%) could be traced to either an MWE, an affordance or an utterance schema, whereas 31 utterances (11.3%) could not be traced to one specific previous occurrence but needed to be traced to more than one match. For RP2, the numbers are slightly different with 86.7% constituting simple traces and 13.3% complex traces. This preliminary count also concerns the ratio of repetitions to novel constructions. For RP1 and RP2, respectively, 51.5% and 48.1% of Carlos’ utterances were full verbatim repetitions. These are the MWEs and the affordances in Table  5.4. Whereas MWEs have been said by Carlos in their entirety before, affordances are expressions uttered by someone else in the immediate interaction leading up to Carlos’ own use and produced by either a peer or a student, or introduced by the teacher as part of the current task and/or written on the classroom whiteboard. These are referred to here as examples of affordances with a term borrowed from van Lier (2000). Afforded uses may range from short expressions like hot tea to longer ones such as do you like ice cream, where did you go and but not this time. Another kind of affordance comes about as private speech. These are utterances that derive from the environment but which Carlos repeats to himself in a lowered voice. Such private speech, it has been argued in sociocultural theory, is crucial in internalisation processes in L2 development (e.g. Lantolf, 2006; Ohta, 2001). The remaining portion of the utterances in the test corpora, that is just over 50%, could not be traced to exactly identical utterances, i.e. they were novel and thus creative. These are the utterances traced to one utterance schema and all the complex traces. The lion’s share of these novel,

87 (31.8%)

54 (19.7%)

141 (51.5%)

102 (37.2%)

243 (88.7%)

Affordances

Full verbatim repetitions, total:

One utterance schema

Total:

Adapted from Eskildsen (2017).

RP2

256 (86.7%)

114 (38.6%)

142 (48.1%)

33 (11.2%)

109 (36.9%)

Absolute/relative no.

RP1

MWEs

Type

Simple trace (trace to an utterance schema, MWE or affordance)

Table 5.4  Simple and complex traces, RP1–RP2, Carlos

10 (3.6%) 0

Untraceable

31 (11.3%)

14 (5.1%)

7 (2.6%)

Three or more utterance schemas + MWE(s)

Total:

RP2

39 (13.3%)

1 (0.3%)

15 (5.1%)

9 (3.1%)

14 (4.8%)

Absolute/relative no.

RP1

Two utterance schemas

One utterance schema + MWE(s)/recycled items

Type

Complex trace (trace to several sources, either multiple schemas, multiple MWEs, a schema(s) and a MWE(s) in combination, or a schema(s) or a MWE(s) in combination with recycled single items)

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116  Usage-Based Dynamics in Second Language Development

Table 5.5  Types of slots in the recurring constructions in the data Semantic type of slot

Example utterances

Schema with slot(s)

Referent (REF)

I have only 26 We have only one class

REF have only REF

Process (PRO)

You no have address? You no like ice cream?

You no PRO REF?

Attribute (ATTadj)

Are you sick? Are you sure?

Are you ATTadj

Attribute (ATTadv)

You think so much I worked too much

REF PRO ATTadv

Location (LOC)

It’s on the 36 picture It’s in the first avenue

It’s LOC

Progressive (PROing)

I’m writing I was dancing

I am/was PRO-ing

Utterance (UTT)

More difficult More time/more + gesture

More UTT

Determiner (DET)

The picture My picture

DET picture.

Copula (COP)

How is your son? How are you?

How COP REF

creative utterances consisted of one utterance schema, i.e. utterances that were traceable to previous uses by way of one simple syntactic operation, substitution, or in some cases, two or three substitutions. In the case of the former, the target utterances differed from previous uses in only one open slot (e.g. are you sick? → are you sure?), and in the case of the latter, in two or three open slots (e.g. I no cook nothing → I no remember my zip code). For further discussion of this, see Eskildsen (2017). The high percentage of utterances traceable to a particular utterance schema tallies well with previous usage-based findings that indicated the importance of utterance schemas in L2 development (Eskildsen, 2009); MWEs, affordances and utterance schemas constitute the basic constructional material of Carlos’ utterances during his first year in class. This portrays language learning as a highly iterative process in which linguistic expressions become routinised – and form the backbone of emergent creativity at the same time: MWEs and affordances can, over time, be disassembled and new material can be put into the appearing open slots. Creativity in this sense, then, is not a matter of producing something entirely novel, but about producing something that differs slightly from something in one’s previous experience as a language user. This, in essence, is the key to understanding usage-based emergence of a creative linguistic repertoire. The next step was to investigate the nature of the open slots in the creative utterances. The slots identified in RP1 and RP2 are displayed in Table 5.5 and exemplified. The slots are the same as in Lieven et al. (2009) with four additional slots: adverbs as verbal attributes (ATTadv),

Creativity and Routinisation in L2 English  117

the progressive verb form (PROing), a determiner slot (DET) and copula (COP). Apart from UTT, all slots must have shared semantic features in their instantiations. This also means that the UTT category applies in cases where Carlos seems to be working on an item-based pattern (e.g. more UTT) but where the open slot may be occupied by material that does not necessarily share semantic features. In the case of more UTT, the utterance more difficult? could be traced to more time and more  +  embodied completion which indicates that the open slot is, in fact, of a quite versatile nature, making it reasonable to assume that for Carlos it is so, too. The reasoning behind positing a UTT slot is thus very much data driven; the empirical data simply lead me to suggest that Carlos is working on a more UTT-schema. Another such example is the schema you no like UTT as the utterance you no like play football could be traced to you no like ice cream. Returning to Table 5.4, I now take a closer look at the cases where multiple schemas had to be invoked to arrive at the target utterances. In total, there are 31 such utterances in Carlos’ RP1 and 39 in his RP2. A basic distinction was made between utterances that consisted of one utterance schema in combination with a variety of recycled material and utterances that consisted of multiple utterance schemas. Examples of the former share the feature of being a partial or full repetition of something Carlos has said before with the addition of other material in a way that has not been done by Carlos before. So, although the utterances themselves consist of recycled and thus traceable material, they are novel and creative uses. There were 7 and 14 such uses in RP1 and RP2  +  RP3, respectively. Table 5.6 gives one example from RP1. The example is an MWE and an utterance schema in combination: in the night for the dance. The two components were not intertwined in this use; instead they seemed to be produced sequentially as separate units: in the night + for the X (dance). The remaining complex traces consist of two or more utterance schemas; there were 24 examples in each period. The use of two or more schemas in one utterance implies the necessity of introducing additional kinds of operations; the simple and otherwise frequent substitution operation no longer suffices, although it is also being used for the production of these utterances. Instead, it was hypothesised that Carlos constructs novel utterances by embedding utterance schemas in each other. The operation of embedding is similar to what Vogt and Lieven (2010) called a two-step substitution and will now be explained in detail using the Table 5.6  Partial or full repetitions of something Carlos has said before with the ­addition of other material in a way that has not been done by Carlos before Utterance

Closest matches

In the night In the night for the dance For the write

Type 1 MWE + 1 utterance schema

MWE/schema In the night For REF

Operations Repetition + 1 substitution (write–dance)

118  Usage-Based Dynamics in Second Language Development

Table 5.7  Utterance based on two utterance schemas Utterance I don’t know write snore

Closest matches I don’t know how to say I write yesterday

Schemas I don’t know UTT Write REF

Operations Two substitutions (write snore, snore) + EMBEDDING

example in Table 5.7, which displays 1 of 23 utterances consisting of two utterance schemas found in RP1 and RP2. The example, I don’t know write snore, is the result of two substitutions and embedding. When it is traced, two matches appear, I don’t know how to say and I write yesterday. The schema write REF allows for the substitution of yesterday with snore and is embedded into the I don’t know UTT-schema in the UTT slot. The notion of embedding is to be thought of as a metaphor for the process that allows Carlos to combine his way to it’s an action right now on the basis of the two previously used patterns identified as the closest matches. Schematically it looks like this: I don't know write snore I don't know UTT write REF snore

Using that template it is possible to derive the same process for other examples of the same kind (Eskildsen, 2017). The complex traces accounted for so far have been found to consist of a variety of combinations of MWEs or affordances or other repeated items and a singular utterance schema or two utterance schemas. The nature of the operations needed to produce the utterances when compared with closest matches in the tracing procedure was most profitably analysed in terms of embedding and substitution operations. Even in the case of these more complex traces, the constructional lineage of the utterances can be found in the data by way of the tracing methodology, showing an astounding degree of recycling and routinisation in L2 learning and accounting for creativity – i.e. the ability to construct novel utterances – in terms of operations on the basis of open slots in constructions. This was also the case for utterances that required tracing to three or more utterance schemas (see Eskildsen, 2017, for more detail). The application of the traceback methodology from child language studies to longitudinal adult L2 data has shown a case of early L2 learning as rooted in recurring MWEs and utterance schemas with creativity evolving in a slow and piecemeal fashion that in many ways resembles the processes involved in child language learning. The substitution operation, as was the case in the child language data, was found to be the most frequently employed operation to produce new, creative

Creativity and Routinisation in L2 English  119

utterances. However, it was also necessary to introduce the embed operation for utterances that consisted of more than one utterance schema. Development was thus described and analysed as the emergence of new MWEs and utterance schemas, some of which may be combined in different ways, with a slight tendency for the number of schematically sanctioned lexical options and intra-turn schematic operations to be on the increase. Results: Valerio

For Valerio, the results of the traceback are remarkably similar to Carlos’. The simple and complex traces, respectively, roughly account for the same portions of data in both students, as displayed in Table 5.8. The biggest difference is that the developmental picture seems slightly different – for Carlos, the tendency was for the complex traces to make up a slightly bigger portion of the data in RP2 and, as shown in Eskildsen (2017), this tendency was more pronounced in later RPs, whereas for Valerio the opposite seems to be happening. One reason could be that whereas Carlos progressed from Level A to Level B across the RPs reported on here, Valerio was attending classes at the same level in both RPs, so perhaps he was not encountering a sufficiently large amount of new linguistic material, or perhaps the interactional environments across this timespan were too alike for any development to happen in terms of emergent creativity. Future research will reveal what the tracing looks like when applied to data further down Valerio’s developmental path and compared to Carlos’ more advanced data. The remainder of this chapter is concerned with a brief discussion of the dynamics of locally contextualised aspects of emergent creativity and routinisation. Emergent Routinisation and Creativity

In a recent chapter in an introductory textbook to SLA, LarsenFreeman (2015) accounted for some of the empirical findings in Eskildsen (2012) through the lens of complexity theory. One of Larsen-Freeman’s points is that the developmental data showed a high degree of fluctuation and that this fluctuation could, to a large extent, be explained by recourse to contextual factors. The original study went beyond mere counts of instances of the construction under investigation, as it applied a twopronged methodology; ‘it did not stop with the UBL evidence. Instead, based on the argument that language is not only emergent but emergence itself is locally contingent and situated, a move toward a locally contextualized view of L2 learning was implemented analytically by exploring the evolution of two negation patterns in ongoing discourse with the aid of CA’ (Eskildsen, 2012: 366). This section briefly describes the environmentally coupled emergence in Valerio’s data of (1) a routinised pattern

RP2

108 (29.9%)

77 (21.3%)

185 (50.2%)

120 (33.2%)

305 (84.5%)

MWEs

Full verbatim repetitions, total:

One utterance schema

Total:

341 (91.2%)

155 (41.4%)

186 (49.7%)

42 (11.2%)

144 (38.5%)

Absolute/relative no.

RP1

Affordances

Type

Simple trace (trace to an utterance schema, MWE or affordance)

Table 5.8  Simple and complex traces, RP1–RP2, Valerio

RP1

56 (15.5%)

10 (2.8%) 9 (2.5%)

Three or more utterance schemas + MWE(s) Untraceable

3 (0.8%)

34 (9.4%)

Total:

RP2

33 (8.8%)

1 (0.3%)

9 (2.4%)

18 (4.8%)

5 (1.3%)

Absolute/relative no.

Two utterance schemas

One utterance schema + MWE(s)/recycled items

Type

Complex trace (trace to several sources, either multiple schemas, multiple MWEs, a schema(s) and a MWE(s) in combination, or a schema(s) or a MWE(s) in combination with recycled single items)

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for social action, you no verb; and (2) a syntactically creative auxiliary do-negation-pattern. This is to exemplify how usage and biographical encounters of specific expressions are crucial to the developmental overview presented in the previous sections. You no write

The most frequent purposes for which Valerio used the two varieties, you no verb- and you don’t verb-constructions were to make assertions (Pomerantz, 1984) or to ask confirmatory questions (Turk, 1999). However, the you no verb-construction was also used to achieve a specific purpose for which Valerio used no other construction and for which he did not appear to possess more relevant L2 resources, namely to instruct his fellow students on the task at hand. As reported in Eskildsen (2012), one activity on one day in class seemed especially pivotal to the development of this aspect of Valerio’s negation repertoire (cf. Extract 1) where the students were doing free movement interactions, a common praxis in this classroom in which the students walk around, freely engaging relatively briefly in cued serial dyadic interactions (Hellermann & Cole, 2009). In this exercise, the students had been instructed by the teacher to write down the names of the students who answered their are you going to + verb questions affirmatively. Extract 1 (Eskildsen 2012: 356, Extract 1, 13 February 2004)5

In Lines  1–3, a classmate asks Valerio a task-question and Valerio answers. The student then starts writing, and Valerio instructs her not to write at this point, using you no write as the main resource to achieve this (Lines  4–8). Valerio ends his turn with you no: accompanied by a vertical open palm gesture (Lines 8 and 9). The gesture seemingly works as an embodied completion of the turn (Olsher, 2004), thus projecting a relevant point for speaker transition. In response, the co-participant

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delivers a nothing (Line 10) which displays understanding and thus helps maintain intersubjectivity, and Valerio immediately incorporates the item into his next turn, a repetition of the instruction, you no write nothing. The sequence is finally closed down as Valerio’s partner, in Line 12, thanks him following a change of state-token o:h (Heritage, 1984) which indicates that she has now understood something new. On this day, Valerio uses the expression you no write eight times to instruct his classmates in the same way as above. As previously mentioned, Valerio used you no/you don’t verb-constructions to accomplish other actions, but the action of instructing somebody on how to do something is for Valerio strictly coupled with the you no-variety. In Valerio’s experience, it emerges as a resource for accomplishing this specific action – it is, in other words, derived from interactional practices in which the act of instructing is relevant. The deployment of this particular pattern at this particular time, then, is a matter of using the available resources allowing Valerio to achieve his interactional goals. In February 2004, where Extract  1 is from, Valerio does not master any other linguistic repertoire that would satisfactorily fulfil his purpose. You don’t verb is yet to emerge (although, arguably, even though structurally it would be standard English, its function as instructing would be pragmatically odd), and expressions like you’re not supposed to verb are not among his L2 resources. On the other hand, Valerio had used the you no verbpattern before this occasion and thus it was already part of his linguistic experience, making for the resource that got him closest to his interactional purpose at the time. With the emergence of you no write in recurring interactions, the non-standard negation becomes a statistical preference in Valerio’s linguistic repertoire, and its use in later interactions a matter of the frequency-biased build of his linguistic inventory. It becomes an established, routinised resource with a clear relation between the expression and the action it is used to accomplish (Eskildsen & Kasper, 2019). Given the highly contextualised nature of you no write, it is likely that different interactional environments (e.g. different or differently structured language learning tasks in the classroom) would have yielded a different trajectory of emergence for this particular feature of Valerio’s negation repertoire. Larsen-Freeman (2015) made the point that Valerio’s changing repertoire in response to situational changes is, indeed, what would be expected of changes in a dynamic system. The development of the standard variety, you don’t verb, can also be traced to changes in linguistic behaviour in response to the environment, albeit in a different way. This is the focus of the next section. You don’t verb

This section starts with Extract  2, in which Valerio is engaged in a classroom task with a classmate, Sal. The lines of interest are Lines 1 to 3.

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Extract 2 (Eskildsen, 2012: 361, Extract 2e, 25 May 2004)

In Lines  1 and 2, Sal claims non-understanding of something – but at this point it is not clear what. This is evident in Valerio’s response which is a request for further information in which he recycles Sal’s turn with a change in speaker perspective. After a pause during which Sal is looking in his papers, he states that nail file is causing him trouble (Line 5). Extract  3 happens 15  minutes later, the class still working on the same theme. The focal lines are 2, 6, 7 and 9, in which Valerio, respectively, recycles parts of Sal’s prior turn and makes a self-repair of a negation structure, from you no useh to you don’t useh (the ‘h’ marks Valerio’s pronunciation of use as /jusə/). Extract 3 (Eskildsen, 2012: 361–362, Extract 2f, 25 May 2004)

Prior to the interaction in the extract, the teacher has introduced the students to the item plastic valve for medical use. In Line 1, Sal makes a claim of no knowledge (of plastic valve) in response to which Valerio immediately orients physically to Sal (he turns around to face him), and, again recycling his words with a change in speaker perspective (Line 2), asks a confirmatory question. After a pause during which there is parallel talk in the class (denoted by the omitted lines in the transcript), Sal answers no, which closes down the sequence (Line 3). Whether Valerio in fact knows the item remains uncertain, because at the moment where he could have explained it to Sal, the next item, contact lenses, is introduced by the

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teacher (Lines  4 and 5). The teacher asks the class about contact lenses and Valerio embarks on an embodied response using a non-standard variety of the negation pattern, you no useh glasses (Line 6 and 7; note again the off-target pronunciation of ‘use’). In overlap (Line  8), the teacher then acknowledges his response (a:h yeah). Next, the teacher and Valerio speak at the same time (Lines 7–10); the teacher is rephrasing Valerio (they replaced glasses they were new) in overlap with which Valerio does a selfrepair (you don’t useh glasses) and elaborates on his response (it’s lit- very small). At the end of the overlap, in Line 11, Valerio displays understanding of and confirms the teacher’s reformulation (yeah). Valerio’s and Sal’s exchanges in the examples can be seen as instances of iteration and co-adaptation – key processes at work in the emergence of language as seen from a complexity theory perspective (de Bot et al., 2007; Larsen-Freeman, 2015). Through affordances of interaction, the speakers experience and, especially in Valerio’s case, imitate encountered linguistic patterns. Chronologically, these two instances mark a point in development just before Valerio begins using a varied repertoire of you don’t verb-patterns. Before this, Valerio’s instances included other afforded uses, that is, uses that he picked up from the environment and imitated and the MWE you don’t know. In addition to displaying exemplar-based characteristics in development, this part of his linguistic repertoire was found to be dependent on affordances and self-repairs (Eskildsen, 2012). Concluding Remarks

The tracing of the emergence of MWEs and utterance schemas has shed new light on how L2 learning takes place along a usage-based path of routinisation and increased creativity (Eskildsen, 2017). The traceback studies have suggested that MWEs and utterance schemas constitute the bulk of constructional material in emergent L2 repertoires. Such a view of the emergent L2 capacities – and the notion that language use is their necessary prerequisite – makes for a very concrete and usage-rooted concept of our linguistic abilities: language is learnable as an experiential interplay of abstracted utterance schemas, based on exemplar MWEs and single lexical items encountered in local environments, and their ascription to the achievement of specific social actions (Eskildsen & Kasper, 2019). Creativity in itself is not only a matter of de-routinising routines, i.e. breaking up fixed chunks into semi-fixed utterance schemas, but it is also a matter of combining utterance schemas into coherent strings of talk in discourse to enable the accomplishment of social actions that require extended talk, for example accounting for something or telling stories (Eskildsen, 2018a, 2018b; Pekarek Doehler & Pochon-Berger, 2015). The data examples also showed the importance of situated language use for L2 learning: everything speakers do is inherently and

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fundamentally contextual. As de Bot et al. (2007: 11) put it, ‘language acquisition emerges through interaction with other human beings within a social context’. This is by now agreed on by usage-based approaches, broadly conceived (Cadierno & Eskildsen, 2015; Douglas Fir Group, 2016). The data reviewed here have presented considerable evidence that Carlos and Valerio were, in fact, drawing on portable resources that can be called their own; if not, the very notion of biographical tracing in the data would be obsolete. However, how something became their own is a different matter; what they do derives from their experience and ultimately what we see as their constructional inventories, frozen in time, are particularised-individualised renditions of what is essentially a socially shared resource – language. In fact, precisely this relationship between the speakers and the contexts in which they navigate needs more attention in the future as we tackle the question of what other interactional resources – doing co-constructions, carrying out repair, initiating turns, initiating and closing down storytelling, employing gestures, making playful comments, etc. – Carlos, Valerio and others are learning as part of their developing interactional competence (Eskildsen, 2018a, 2018b; Eskildsen & Kasper, 2019; Pekarek Doehler, 2018; Pekarek Doehler & Pochon-Berger, 2015). Getting to the core of the relationship between interactional contexts, social actions and the emergent linguistic repertoire is crucial to an understanding of language learning as a dynamic, biographical and experiential process. Notes (1) Carlos’ RP2 was RP2–3 in Eskildsen (2017) and Valerio’s RP3 was RP3–4 in Eskildsen (2015). (2) An embodied completion is a turn-at-talk ending in a bodily action, e.g. he went to the [deictic gesture]. (3) Single word utterances (yes, no, exactly, alright, etc.), summons of teachers or classmates and tokens of recipiency and change-of-state (Heritage, 1984) (uhuh, mhm, oh, etc.) have been left out here because the focus of the investigation is on MWUs. (4) In the process of writing this chapter, I discovered some minor inconsistencies between the tables and the text in Eskildsen (2017). These have been corrected in this chapter. (5) Transcription conventions: 01,02,03. . .: line numbers; Va, Sa. . .: speakers (Un = unknown student); -> = target utterance; (1)/(.) = pause, length indicated in seconds/ pause shorter than one second; ((. . .)): transcriber’s comments; : = stretched vowel; [] = overlap; ↓, ↑ = falling / rising intonation; “-” = cut-off. “ = ” = continued lines.

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6 Attractor States in the Development of Linguistic Complexity in Second Language Writing and the Role of Self-Regulation: A Longitudinal Case Study Attila M. Wind and Luke Harding

From a Complex Dynamic Systems Theory (CDST) perspective, complex phenomena such as the language learner’s linguistic system, are considered to be nonlinear, completely interconnected, iterative and co-adaptive (Larsen-Freeman, 1997). Although these systems show a certain degree of variability over time, they might also settle into specific states: so-called ‘attractor states’ (de Bot et al., 2007). Previous studies on second language (L2) writing development have explained the lack of variability in language learners’ trajectories as possibly related to ‘attractor states’. However, these studies did not investigate the emergence of attractor states further (Spoelman & Verspoor, 2010; Verspoor et al., 2008). This study adopted a mixed-methods research design to investigate how L2 writing development is facilitated by the use of selfregulatory processes. Data were collected from one Hungarian English as a foreign language (EFL) university student over nine months. The participant composed 23 argumentative essays and was interviewed periodically on his self-regulation. The essays were analysed for lexical and syntactic complexity indices, while the interviews were coded for three key self-regulatory processes: self-observation, self-evaluation and goal-setting. Findings show that the trajectories of linguistic complexity indices were nonlinear over time. Statistically significant developmental peaks were not detected in the participant’s linguistic system, which indicated the emergence of salient attractor states. Qualitative analysis of the interview data revealed that the participant made limited use of selfregulation, which was reflected in the lack of change in the complexity of his L2 writing. Furthermore, the qualitative analysis demonstrated that 130

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the student’s motivational system resided in an attractor state related to boredom, frustration and low self-efficacy belief, which may have influenced the stability of his linguistic system. This study contributes to a theoretical understanding of the emergence of attractor states in the linguistic and motivational systems. Introduction

Since the introduction of tuition fees at Hungarian universities, a growing number of secondary school and university students have sought to study abroad. This trend might be because there are countries in the European Union where university education is free, such as Denmark, or because students wish to study at an institution with a high international ranking (currently the highest-ranked Hungarian university, the University of Szeged, is ranked between 501 and 510 [QS World University Rankings, 2019]). In order to study at universities where English is a medium of instruction, Hungarian students are required to take a standardised international test of English language proficiency such as the International English Language Testing System (IELTS). The vast majority of universities require students to obtain a minimum overall score of 6.5 on the academic module of the IELTS for admission to degree programmes. Although academic writing makes up 25% of the overall IELTS score, writing does not regularly receive dedicated attention in secondary and tertiary education in Hungary. For example, only one university in Hungary, the Central European University, has a separate centre for academic writing. The relative lack of attention to academic writing is reflected in the results of the IELTS test taker performance (2016) in which writing was the lowest-scored skill for Hungarian test takers. Improving writing performance, however, is a complex task. Successful academic writing requires development both in a writer’s linguistic system and in non-linguistic systems such as self-regulation (Kormos, 2012). For example, writers need to control their thoughts (e.g. competency beliefs), emotions (e.g. anxiety experienced during writing), behaviours (e.g. how they manage a writing task) and the learning environment (Pintrich & De Groot, 1990; Zimmerman, 1998). A study on the use of self-regulatory strategies among Hungarian university students found that only a third of the participants, from a sample of 222 English as a foreign language (EFL) university students, possessed the ability and willingness to control their writing processes (Csizér & Tankó, 2017). Consequently, there is an urgent need to investigate the simultaneous development of second language (L2) writing and self-regulation. The majority of previous studies on L2 writing development have typically adopted a two-wave research design, with samples collected at two points in time to investigate changes in linguistic complexity indices

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(Barkaoui, 2016; Knoch et al., 2015; Storch, 2009). These previous twowave studies have yielded three types of findings: (1) an increase, (2) a stagnation or (3) a decrease in a specific index. Although two-wave longitudinal studies are important in revealing tendencies in L2 writing development, they have limitations. First, they cannot easily capture the dynamic nature of L2 development (Norris & Ortega, 2009). Second, according to the ergodic principle, group statistics cannot be generalised to the individual, and vice versa, unless it can be demonstrated that groups form an ‘ergodic ensemble’ (Lowie & Verspoor, 2019: 185). For this reason, longitudinal single-case studies have come to be viewed as vital in complementing group studies of L2 development. Since the beginning of the 2000s, there has been a rapid increase in the number of studies adopting a multi-wave research design where performance samples are collected from individual learners at multiple points over time (Larsen-Freeman, 2006; Verspoor et  al., 2004, 2008). In line with Complex Dynamic Systems Theory (CDST), multi-wave research designs have been found to be fruitful in capturing the dynamicity and nonlinearity of the constructs of linguistic complexity. In previous CDST studies, one of the most extensively used techniques to detect changes in linguistic complexity measures is ‘variability analysis’, developed by van Geert and van Dijk (2002), which employs data resam­pling techniques and Monte Carlo analyses. Several previous CDST studies have employed variability analyses to detect changes in linguistic indices (Rosmawati, 2016; Verspoor et  al., 2019) and explain the lack of developmental peaks by pointing to possible ‘attractor states’: periods of system stability. However, these studies did not investigate further the reason why such possible attractor states might emerge. The case study presented in this chapter addresses this gap by adopting a longitudinal, multi-wave, mixed-methods research design to trace changes and periods of stability in linguistic complexity indices and their connection with selfregulatory processes in the writing of one Hungarian university student. The Development of Linguistic Complexity in L2 Writing and Self-Regulation

Linguistic complexity in L2 writing is generally measured by tracing changes in the constructs of lexical and syntactic complexity. Bulté and Housen (2012: 25) defined complexity generally as ‘the degree of elaboration, the size, the breadth, the width, or richness of the learners’ L2 system’. Similarly, Verspoor et al. (2017: 1) defined linguistic complexity as a ‘quantitative property of language units’ that is ‘the greater the number of components a construction has and the more levels of embedding it contains, the more complex it is’. However, lexical and syntactic complexity represent quite distinct dimensions of complexity, and their measurement in L2 writing requires consideration of a range of techniques.

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Lexical complexity

Lexical complexity is a multidimensional construct generally involving lexical diversity, lexical density and lexical sophistication (Bulté & Housen, 2014). A range of measures of lexical complexity have been used in the research literature including the type-token ratio (Johnson, 1939), the Guiraud (1954) index, and the measure of textual lexical diversity (McCarthy, 2005). Verspoor et al. (2017), however, argue that the average word length (AveWL) index is a reliable indicator of general lexical complexity. The AveWL index is a fairly simple measure in which the total number of characters in a piece of writing is divided by the number of words in a script. Previous studies adopting a multi-wave research design have found that the AveWL index increases over time. By applying a polynomial trend line, Verspoor et al. (2008) found that the AveWL index displayed an upward trend in the written data of an advanced learner of English over three years. By applying a min-max graph to the AveWL index, Verspoor et  al. (2008) identified three stages in the bandwidth of variability: (1) a relatively stable period, (2) a highly variable part and (3) a stable period again. Although Verspoor et al. (2008) visually detected a developmental peak in the AveWL index, it was not tested against chance by using data resampling and Monte Carlo analysis. Verspoor et al. (2017) also found upward trends by applying locally estimated scatterplot smoothing (LOESS) in the AveWL index in three Dutch female university students’ written data over four years. Similarly, Penris and Verspoor (2017) found that the AveWL index showed an upward trend across 49 written samples collected from a Dutch EFL learner over a 13-year period. Syntactic complexity

Similar to lexical complexity, syntactic complexity is also a multidimensional construct consisting of at least three main dimensions: (1) subordination, (2) coordination and (3) phrasal complexity (Norris & Ortega, 2009). One of the most common methods for exploring syntactic complexity is the words per T-unit method (e.g. Storch, 2009; Verspoor et  al., 2012); however, Verspoor et  al. (2017) argue that the finite verb ratio (FVR) index can be considered as a useful general syntactic complexity index. Previous CDST studies adopting a multi-wave longitudinal research design found that the FVR index increases as a learner progresses from B2 to C1 on the Common European Framework of Reference (CEFR). For example, Verspoor et al. (2008) found the FVR index increased in a Dutch EFL learner’s written data over three years. However, Verspoor et al. (2008) did not apply any smoothing techniques to the FVR index but rather focused on the interaction between the FVR index and sentence length over time. Verspoor et  al. (2017) also found upward trends in the FVR index by applying LOESS, in three

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female Dutch EFL students’ writing over four years. Likewise, Penris and Verspoor (2017) found that the FVR index displayed an upward trend, employing polynomial trend lines, in a Dutch EFL student’s written data over 13 years. (See Bulté & Housen [this volume] on how lexical and syntactic complexity interact over time.) It is clear that multi-wave longitudinal research designs have helped to capture change in linguistic complexity over time, providing more finegrained perspectives on developmental peaks and troughs than would be possible with two-wave designs. However, there is less understanding of the influencing factors which might drive such variations in developmental trajectories. Kormos (2012) pointed out that self-regulation might play an important role in general L2 writing development. The construct of self-regulation is addressed in the next section. Self-regulation

Research on L2 motivation has been dominated by Dörnyei’s (2005, 2009a) influential model, the L2 Motivational Self System which is composed of the ‘ideal L2 self’, the ‘ought-to L2 self’ and the ‘L2 learning experience’. Self-regulation plays an important role within the L2 Motivational Self System as Nitta and Baba (2015: 368) claim that selfregulation can be adopted ‘as a construct for characterising L2 learning experience’. Although a multitude of factors might contribute to development in L2 writing more generally, high levels of self-regulation have been found to be one of the most important elements. Kormos (2012) defined self-regulation as a process in which learners organise and manage their learning. Zimmerman (1998) pointed out that self-regulation includes learners’ control over their thoughts (e.g. competency beliefs), emotions (e.g. anxiety experienced during the learning process), behaviours (e.g. how they deal with a specific learning task) and the learning environment. Numerous self-regulatory processes or strategies have been identified in the literature on self-regulation, such as self-efficacy, self-observation, causal attribution, self-evaluation, text analysis and goal-setting. Zimmerman (2000) categorised these self-regulatory processes in a cyclical model consisting of three phases: (1) forethought, (2) performance control and (3) self-reflection. Zimmerman’s (2000) model, in line with CDST, includes sources of motivation and cognitive processes ‘in a cyclical feedback loop wherein writing outcomes are used to modify and guide subsequent efforts to write’ (Zimmerman & Kitsantas, 2007: 54). L2 motivation has come to be seen as a dynamic construct since the introduction of the CDST into the field of L2 motivation research (Dörnyei et  al., 2015). A CDST approach recognises that a language learner’s motivation might change during a 45-minute class (Sulis et al., this volume) or over extended periods of learning (Waninge et al., 2014). Although there have been some studies of self-regulation from a CDST

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perspective, these studies have mainly focused on the evolution of selfregulatory processes rather than drawing connections with patterns of linguistic development (Han & Hiver, 2018; Sasaki et al., 2018). To date, however, there have been few studies specifically focused on the simultaneous development of self-regulation and linguistic complexity (Nitta & Baba, 2015, 2018). Nitta and Baba (2015) explored how the ideal L2 selves of two Japanese female learners of English emerged and evolved over one academic year during which participants composed essays for 10 minutes on a weekly basis. One participant employed self-evaluation processes and set a wide range of goals, refining her future goals and internalising them as her ideal L2 self through repetition of the writing tasks. The second participant’s self-regulatory processes displayed marked differences in the first and the second halves of the academic year, and this matched changes in lexical and syntactic complexity and fluency. Nitta and Baba attributed this marked contrast to the second participant’s experiences studying abroad since her ideal L2 self emerged and developed simultaneously with these changes. It was found that the relationship between the ideal L2 self and L2 learning experience was coadaptive within the context of the EFL classroom and that learners’ selfregulatory processes played an important role in helping the development both of the ideal L2 self and of linguistic complexity and fluency. Nitta and Baba (2015) concluded that it might be instructive to investigate cases with limited self-regulatory capacity and explore what factors might contribute to make individual learners unmotivated. In another CDST study, Nitta and Baba (2018) explored the benefits of task repetition over one academic year. The authors collected data from 26 Japanese EFL students to investigate how learners’ use of selfregulation related to changes in linguistic complexity. The participants’ texts were analysed using lexical and syntactic complexity and fluency indices, while their self-reflections were coded for three key self-regulatory processes: self-observation, self-evaluation and goal-setting. The L2 writing of the first focal participant, labelled a ‘skilful self-regulator’, improved over time as evidenced by her more elaborated engagement with the writing tasks, her use of self-evaluation processes and her setting of a wide range of goals. Conversely, there was little change in the L2 writing development of the second participant, the ‘naïve self-regulator’, since he showed more limited engagement and employed a less elaborate self-regulatory process. The authors concluded that self-regulatory processes influence learners’ L2 writing development to a decisive extent when a writing task is repeated over a long period. Attractor states

According to de Bot et al. (2005), complex systems are constantly changing and self-organising and all elements are directly or indirectly connected to each other. Sometimes, complex systems show a great

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deal of variability and change over time. However, there are certain periods of inherent stability when only stronger external forces might cause a change in the system. A great deal of variability might be the harbinger of change in a complex system, while little intra-variability can be a sign of system stability. States of less variability are called ‘attractor states’. Hiver (2015) defined attractor states as stable patterns, tendencies, solutions or outcomes in human behaviour. De Bot and Larsen-Freeman (2011) exemplified attractor states with the phenomenon of fossilisation, which refers to stagnation in L2 development. Note, however, that Larsen-Freeman (2014) has also critiqued the notion of fossilisation, which assumes orientation towards specific norms and end points. Hiver (2015) illustrated attractor states with the stabilisation of a first-year class of high school L2 learners into a cohesive group. According to Dörnyei (2009b), the combination of specific learner characteristics might create salient attractor states that function as integrated wholes causing system stability. For example, the ideal L2 self, or personality characteristics (extroversion or introversion), might form attractor states on the longer-term timescale, whereas level of interest can create attractor states on shorter timescales (Dörnyei, 2009b). However, disrupting forces, called perturbations, can push the system out of one attractor state into a different direction. Hiver (2015) exemplified perturbations as the announcement of a test in the L2 language classroom which could shift students into a level of high-intensity preparation. To date, no studies have investigated attractor states in the development of linguistic complexity in L2 writing. However, some studies have looked at attractor states in language learning motivation. For example, Waninge (2015) identified the main attractor states that make up the learning experiences in a language classroom of 56 second-year students of English at a British university. The data were collected through short semi-structured interviews in which participants were asked to list as many states as they experience in their classroom. Frequently mentioned attractor states included interest, boredom, neutral attention and anxiety. Some learners were found to switch from one state to the other within a single lesson indicating variability on a short-term timescale. However, certain states were found to be more stable such as interest. Research questions

This study forms part of a larger project which adopted a CDST perspective to investigate the development of lexical and syntactic complexity among a group of Hungarian EFL university students over a nine-month period (Wind, 2018). By applying a mixed-method, longitudinal, multiple case study research design, the project explored the coadaptation between the linguistic and the self-regulatory systems. Data in the current study focus on one specific learner – Hunor. This study is framed by the following research questions:

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(1) How do lexical and syntactic complexity indices change in the participant’s argumentative essays over the nine-month investigation? (2) Where do developmental peaks emerge in the lexical and syntactic complexity indices in the participant’s argumentative essays over the nine-month investigation? (3) How do the participant’s self-regulatory processes change over the nine-month investigation? (4) What (if any) is the connection between lexical and syntactic complexity and self-regulatory processes over the nine-month investigation? (5) Where do attractor states emerge over the nine-month investigation? Methodology Research context

The data for this study were collected during an English for academic purposes (EAP) programme at a university in Budapest. The programme was aimed at developing the use of English in an academic context, the analytical and critical thinking skills required for academic study and an awareness of relevant learning skills and strategies. The target population of the programme were students with IELTS scores of 5.5–6.5 (B2 on the CEFR, Council of Europe, 2001). The EAP programme provided three hours of in-class teaching per week and adopted a task-based approach. The programme was composed of two modules: academic reading and writing, and academic listening and speaking. IELTS-type language tests and vocabulary tasks were typically completed during each class and students received feedback in the form of an overall IELTS score. Furthermore, the students were required to take four vocabulary tests over the nine months. The participant

The participant of this study, Hunor (pseudonym), was a 22-year-old EFL Hungarian student. At the time of the study, Hunor was studying for a bachelor’s degree in engineering at a university in Budapest. His first language was Hungarian and he had been learning English for 10 years at the beginning of the EAP course. Hunor’s English language education started at the age of 12 at a renowned secondary school in Budapest where he attended three English classes per week over a six-year period. He took the European Language Certificates (TELC) language test at B2 CEFR level in Grade 10, and on these grounds he was not obliged to attend English classes for the remainder of his time at secondary school. At the end of secondary school, Hunor decided to take the final exam (Matura) in English language at ‘medium’ level (approximately at B1 CEFR level). During his bachelor studies at university, Hunor did not engage in formal language education apart from occasional private English language classes. However, Hunor was planning to apply for an

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MSc in engineering in Hungary, one of the prerequisites for which was an English language certification at the C1 level. Hunor, therefore, enrolled in the EAP programme to prepare to take an IELTS exam. Data collection

This study adopted a longitudinal, mixed-methods research design. According to Johnson and Onwuegbuzie (2004), a key feature of mixedmethods research designs is methodological pluralism, drawing on both quantitative and qualitative data and analytic approaches. In the current study, data included samples of written work collected over a ninemonth period as well as transcripts of interviews. Linguistic complexity phenomena within the written samples were quantified and analysed using statistical methods, whereas the interview transcripts were mostly analysed qualitatively through thematic coding. A total of 23 IELTS-style argumentative essays were collected from Hunor over a nine-month period. Sixteen essays were written as home assignments (i.e. in the participant’s natural setting), in line with the data collection protocols of previous CDST studies (Verspoor et  al., 2004), while seven essays were composed in controlled settings. During the composition of the 16 home essays, Hunor had unlimited access to resources. For instance, he could use dictionaries, auto-correction tools, the internet and electronic editor tools. The home assignments were sent to the teacher of the EAP class electronically: the teacher then provided feedback in the form of a predicted IELTS score. In order to achieve a balance between the naturalistic and experimental research designs, more controlled or experimental data were also collected. This took the form of seven argumentative essays which were embedded within the longitudinal multi-wave design. To make these tasks as comparable as possible, all the writing prompts for the seven argumentative essays were related to the topic of ‘foreign language learning’, a topic considered relevant and familiar to the participant. The seven IELTS-style argumentative essays, written at monthly intervals, were composed by the participant from October to March. Hunor wrote the essays by hand in his classroom; the use of word-processing software, dictionaries and reference materials was not allowed. Hunor was asked to work individually and to produce a written sample (at least 250 words) in approximately 40 minutes. The researcher did not give feedback on Hunor’s written samples during the data collection procedure. The two types of data collection settings required the utilisation of different aspects of self-regulation. For example, during the writing of the 16 argumentative essays, Hunor needed to control his behaviour and environment, whereas composing the seven argumentative essays under controlled settings he needed to manage his time as well. In addition to providing the 23 writing samples, Hunor took part in nine interviews. In an initial interview, Hunor was asked about his

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Data points 1

2

1

2

3

4

5

3

4

6

7

8

5

6

9

10

11

12

13

14

15

16

17

11

12

18

19

20

13

14

21

22

23

15

16

Uncontrolled writing prompts 7

8

9

10

Controlled writing prompts 1

2

3

1

2

3

4

5

6

7

5

6

7

Retrospective interviews

Initial interview 1

4

Final interview 2

Figure 6.1  Multi-wave research design

general writing goals. The aim of this initial interview (approximately 5 minutes) was principally to become acquainted with the participant and to create a motivational profile. Then, Hunor took part in seven retrospective interviews immediately following his production of each of the seven controlled written samples. These retrospective interviews (approximately 10 minutes) focused on Hunor’s self-regulatory processes: he was asked to comment on the essay he had just written, to compare the essay with previous essays he had written for the study and to talk about his future writing goals. Finally, Hunor was interviewed (approximately 30 minutes) at the end of the data collection period to explore further any external factors that might have contributed to his L2 writing development. Figure 6.1 displays the multi-wave research design. Quantitative data analyses

In calculating linguistic complexity indices, the analytic choices in this study followed Verspoor et al. (2017), who claimed that the AveWL index is a reliable indicator of general lexical complexity, while the FVR reliably measures general syntactic complexity. The AveWL index was computed by Coh-Metrix 3.0 (Graesser et  al., 2004, 2011). The FVR index was calculated through a manual procedure. First, the texts were coded for finite verbs, ‘the verb form that is limited in tense, person, and number’ (Verspoor & Sauter, 2000: 49) and then the total number of words was divided by the total number of finite verbs in a specific text. Changes in the linguistic complexity indices were visualised by trajectory plots. In order to explore the developmental trend over time, a

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smoothing algorithm (simple moving average [SMA]) was applied. The SMA is the unweighted mean of the preceding n data. In this study, a window of five data points was used. Nonetheless, linear regression lines were added to the trajectory plots when the SMA displayed a sideways trend. The degree of variability in the linguistic complexity indices was visualised using min-max graphs (van Geert & van Dijk, 2002). The minmax graph shows the bandwidth of the observed data over time. The wider the bandwidth, the greater the amount of variation in a specific index. Observations were tested against chance by data resampling and running a Monte Carlo analyses using MS Excel Poptools (Hood, 2010). The observations can be tested against chance by data resampling, developed by van Geert and van Dijk (2002), since the min-max graph is only a descriptive technique. In the data resampling method (Efron & Tibshirani, 1993; Good, 1999), a large number of subsamples are randomly drawn from the original sample in order to detect developmental peaks in the data set. First, an SMA over two data points was calculated in the original data set and repeated until the last data point in the original data set. Second, the difference between data points was calculated in the averaged data set. Data point 2 was subtracted from data point 1 in the twostep difference values, while data point 3 was subtracted from data point 1 in the three-step difference values. The same calculation was repeated until the six-step difference. Third, the maximal distances between the data points were calculated for each step (from Step 2 to Step 6) and the maximal positive distance of every step was used as the testing criterion in the resampling model. Fourth, the original data were reshuffled with replacements using MS Excel Poptools. Finally, two separate Monte Carlo analyses (one for the AveWL and one for the FVR indices) were run with 5000 simulation steps by selecting the resampled criterion for the dependent range, and by selecting the original criterion for the test values. Qualitative data analyses

The qualitative data exploration consisted of three stages. First, the interview data (initial interview, retrospective interviews and final interview) were coded by the researcher of this study and an English teacher for three key self-regulatory processes: (1) self-observation, (2) self-evaluation and (3) goal-setting. The coding scheme was adopted from Nitta and Baba’s (2015) study. Self-observation concerned the participant’s impressionistic descriptions of his thoughts and actions, usually containing superficial descriptions of his own writing. In contrast, selfevaluation related to evaluative comments that involved several cognitive processes such as specifying, reasoning, analysing or comparing essays. For example, the participant sometimes specified and gave reasons for his actions concerning writing, or in other cases analysed his own writing and compared the argumentative essays written for this study. The third

Attractor States in the Development of Linguistic Complexity  141

category, goal-setting, included comments in connection with future specific actions concerning improving the participant’s own writing. Table 6.1 provides examples for the three key self-regulatory processes. The second stage of qualitative data exploration included the identification of attractor states in the participant’s interview data. This second stage was part of an iterative coding process which was employed after it was discovered during the first stage of the qualitative analysis that the participant did not develop his self-regulatory processes (c.f., Nitta & Baba, 2015, 2018). In the second stage, the interview data were re-analysed to identify potential attractor states. The coding scheme for attractor states was adopted from Waninge’s (2015) study (see above). Intra- and inter-coder reliability

In this study, both intra- and inter-coder reliability was calculated. Coder 1 was the first author, while Coder 2 was an English teacher with 30 years’ experience who was also studying for a PhD degree in applied linguistics. Both coders coded the 23 argumentative essays for finite verbs, as well as the interview data using the coding scheme for self-regulatory processes presented in Table 6.1. In addition, the coding for finite verbs and for self-regulatory processes was repeated by Coder 1 three months after the first coding procedure to establish intra-coder reliability. In this study, the positive overlap ratio (POR) was calculated to measure intra- and inter-coder reliability (van Geert & van Dijk, 2003). The POR shows the percentage of overlapping positive cases confirmed by the two coders. There were two steps in the calculation of the POR index: (1) the identification of the cases confirmed by the two coders and (2) the identification of the number of overlapping cases. The calculation of the POR index is shown in Equation 6.1: POR =



2Y X1 + X 2

In Equation 6.1, X1 refers to the number of cases confirmed by Coder 1, while X2 denotes the number of cases confirmed by Coder 2; Y refers to the number of mutually confirmed cases. Table 6.1  Self-regulatory processes Self-regulatory process

Example

Self-observation

‘Maybe I tried some new (words and phrases)’.

Self-evaluation

‘I am happy with it (the level of vocabulary) because there were only one words, word what I couldn’t write’.

Goal-setting

‘I want to read more in English and just improve my language and my grammar so just deal with English’.

Note: Since goal-setting was not identified in this study, the example was taken from Wind (2018).

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The POR value of the intra-coder reliability reached 98% for the finite verbs and 82% for the coding of the interview data, whereas the POR value of the inter-coder reliability was 95% for the finite verbs and 84% for the interview data. In this study, disagreement between the coders was resolved through discussion. Results Developmental trends

Figure 6.2 shows the developmental trend of the general lexical complexity (AveWL) index across the 23 data points. The AveWL slightly fluctuated between four and five characters between data points 1 and 23, except for data point 22 (5.35). The AveWL index reached its nadir at data point 3 (AveWL = 4.01), while the highest AveWL value (AveWL = 5.35) was measured at data point 22. The smoothing algorithm (the simple moving average, SMA) displays a slightly upward trend over the nine months indicating a slight improvement in the general lexical complexity index. The developmental trend of the general syntactic complexity (FVR) index is shown in Figure 6.3. The lowest FVR value (FVR = 6.55) was measured at data point 18, while the highest value (FVR = 9.11) was recorded at data point 13. The SMA displays a sideways trend and the linear regression line shows a downward trend over the nine months, indicating that Hunor’s syntax did not become more elaborate over time. The following examples, taken from Hunor’s Essay 18 and Essay 13, illustrate the difference in the general syntactic complexity (FVR) index. Essay Excerpt 1 was extracted from Essay 18 where the FVR was at its lowest value (6.55). In contrast, Essay Excerpt 2 was taken from Essay 13 where the FVR index was at its peak (9.11). In the excerpts, the finite verbs are underlined and numbered and the example sentences are left uncorrected. 6.00 5.00 4.00 3.00 2.00 AveWL

1.00 0.00

SMA 1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Figure 6.2  General lexical complexity (AveWL)

Attractor States in the Development of Linguistic Complexity  143

10.00 9.00 8.00 7.00 6.00 5.00 4.00 3.00

FVR

2.00

SMA

1.00

Linear

0.00

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Figure 6.3  General syntactic complexity (FVR)

Essay Excerpt 1 (Essay 18) Learning a language 1is not just depending on that where you 2live. (Errors are uncorrected; finite verb is underlined and numbered in superscript) (Word count = 12; finite verb count = 2; FVR = 6) Essay Excerpt 2 (Essay 13) However, it 1is a completely great idea because students 2can earn a lot of experiences during a year of travel or work. (Errors are uncorrected; finite verb is underlined and numbered in superscript) (Word count = 22; finite verb count = 2; FVR = 11) According to FVR, the two sentences exhibit different levels of syntactic complexity, even though they are both ‘complex’ sentences in the sense that they each contain an independent clause and a dependent clause. Degree of variability

Apart from plotting the developmental trends of the lexical and syntactic complexity indices, this study also looked at the degree of variability over the nine months. Figure 6.4 shows the bandwidth of variability in the general lexical complexity (AveWL) index. There are no clear differences in the bandwidth of variability in the AveWL index over the nine months. However, the bandwidth slightly narrows at data point 6 and then slightly widens at data point 9. The most notable change in the bandwidth of the AveWL index was detected at data point 20, when the bandwidth widens again. These ranges of variability can be interpreted as Hunor using lexical items with similar length in a regular pattern over the entire period of investigation.

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6.00 5.00 4.00 3.00 AveWL

2.00

MIN 1.00 0.00

MAX 1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Figure 6.4  General lexical complexity (min-max)

10.00 9.00 8.00 7.00 6.00 5.00 4.00

FVR

3.00

MIN

2.00

MAX

1.00 0.00

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Figure 6.5  General syntactic complexity (min-max)

The bandwidth of variability in the general syntactic complexity (FVR) index is displayed in Figure 6.5. There are larger differences in the bandwidth of the FVR index than in the bandwidth of the AveWL index. The bandwidth of the FVR index is narrow (range: 7.63–8.24) between data points 1 and 3, but then it widens and remains relatively wide until data point 10. The bandwidth widens (range: 6.94–9.11) even further at data point 11, before narrowing again (range: 6.54–8.20) at data point 16 and shifting to a slightly lower level. The data of the lexical and syntactic complexity indices were resampled and two separate Monte Carlo analyses were run. The p-value of the AveWL index was 0.31, while the p-value of the FVR index was 0.65, suggesting that statistically significant developmental peaks were

Attractor States in the Development of Linguistic Complexity  145

not detected in the linguistic complexity indices. The quantitative data exploration of the development of linguistic indices thus indicated a more stable period. It might be speculated that Hunor’s linguistic systems resided in an attractor state throughout the nine-month study. Self-regulatory processes

The evolution of Hunor’s self-regulatory processes, as evidenced in the interview data, is depicted in Figure 6.6, which shows the number of thematic units identified at each data point when an interview was conducted. Hunor focused predominantly on self-observation processes between data points 3 and 9. However, a shift can be observed from self-observation to self-evaluation processes from data point 12. For instance, there were four self-evaluation thematic units and only one self-observation thematic unit at data point 12, and the prevalence of selfevaluation thematic units continues through to data point 21. Figure 6.6 also demonstrates that Hunor did not set any goals over the nine months. A detailed breakdown of the range of Hunor’s self-regulatory processes over the nine months is displayed in Table 6.2. The number of self-observation thematic units was evenly distributed (ranging between 1 and 2 thematic units) over time. Nonetheless, the types of selfobservation thematic units were not equally dispersed as Hunor shifted between concentrating on language, content and his composing processes (while never focusing on the quality of his essays). By contrast, the number of self-evaluation thematic units was more focused, from data point 12, on language, with some evaluation of content and quality (but not composing processes). The nature of Hunor’s comments is also revealing. Early selfobservations were typically brief responses to the interview questions, 6 Self-observation

5

Self-evaluation Goal-setting

4 3 2 1 0

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Figure 6.6  Self-regulatory processes

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Table 6.2  Self-regulatory processes Data point

Self-observation

Self-evaluation

Goal-setting

Language

Total

3

6

9

12

15

18

21

1

0

0

1

1

0

0

Composing processes

1

1

1

0

1

1

1

Content

0

1

1

0

0

0

0

Quality

0

0

0

0

0

0

0

Total

2

2

2

1

2

1

1

Language

0

1

2

2

1

2

3

Composing processes

0

0

0

0

0

0

0

Content

0

0

0

1

1

1

1

Quality

0

0

0

1

1

1

0

Total

0

1

2

4

3

4

4

Language

0

0

0

0

0

0

0

Composing processes

0

0

0

0

0

0

0

Content

0

0

0

0

0

0

0

Quality

0

0

0

0

0

0

0

Total

0

0

0

0

0

0

0

11

18

0

showing a relatively cursory level of introspection. Interview Excerpts 1 and 2 are cases in point, illustrating Hunor’s reticence to engage deeply with describing his writing process. Interview Excerpt 1 (Self-observation: language, data point 12) Interviewer: Are there any words in your essays that you have used for the first time? Hunor: No, I didn’t use any. Interview Excerpt 2 (Self-observation: language, data point 6) Interviewer: Did you use any new lexical items you learned during the course? Hunor: No, not really. As noted above, Hunor began to focus more on self-evaluation from data point 12 onwards. These comments, however, also showed little elaboration beyond a sense of satisfaction or dissatisfaction with the use of appropriate vocabulary. Interview Excerpt 3 (Self-evaluation: language, data point 18) Interviewer: Are you happy with the level of vocabulary that you were using in this writing? Hunor: Yes, I am happy with it because there were only one words, word what I couldn’t write.

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Interview Excerpt 4 (Self-evaluation: language, data point 21) Interviewer: Why didn’t you include those words in the essay? It’s not a question that you should include. I’m just asking. Why not? Is there a reason? Hunor: Maybe because these words is not so automatically useable for me now. I don’t know. Maybe this is the reason. Ultimately, Hunor’s description of his L2 learning experience did not contain more specific explanations over time, which suggests that his self-regulatory processes did not evolve substantially, despite a small shift from self-observation to self-evaluation. Consequently, Hunor’s interview data were re-read to identify potential attractor states that made up his L2 learning experience to try to explain the lack of evolution in his self-regulatory processes. Attractor states

The first dominant state which emerged in Hunor’s interview data was boredom. He repeatedly stated that he was uninterested in the writing task (see Interview Excerpt 5). Interview Excerpt 5 (data point 9) Interviewer: Do you think that this piece of writing is a good representation of how well you can write? Hunor: Well… it can be but the topic wasn’t my… best… I’m not very interested in this topic. The general lexical complexity (AveWL) index value reflects Hunor’s disinterest in the topic of ‘language learning’. The AveWL index, shown in Figure 6.2, increases between data points 1 and 2. However, the AveWL index drops at data point 3 when the first essay was written on the topic of ‘language learning’. The difference between the controlled and the uncontrolled essay prompts becomes even clearer in the second half of the data collection. The AveWL index drops at data points 12, 15, 18 and 21 when Hunor composed essays on different topics related to ‘language learning’. At data point 12, during the retrospective interview, Hunor expressly connected his lack of interest in the topic of ‘language learning’ with his writing performance (Interview Excerpt 6). Interview Excerpt 6 (data point 12) Interviewer: Do you think that this piece of writing is a good representation of how well you can write? Hunor: Well, it isn’t because I am better when I have to write about my own ideas so there is no topic. Interviewer: So you think that this topic is really precise or there is no freedom in it? Hunor: Yes… kötött (restricted or controlled).

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The second dominant state which emerged in Hunor’s data was frustration. In his initial interview at data point 3, Hunor described how irritated he feels when he does not know a lexical item during writing (see Interview Excerpt 7). Interview Excerpt 7 (data point 3) Interviewer: How do you feel when you write in English? Hunor: When I don’t know a word I will be angry… and then I always open a next dictionary. Interviewer: So you are frustrated… or stressed a little bit? Hunor: Yeah. This general frustration with writing can also be found later during the nine-month period when Hunor states (see Interview Excerpt 8): Interview Excerpt 8 (data point 6) Interviewer: How did you feel during the composition of this essays? Hunor: I don’t know I become angry because I don’t remember a word. Finally, low self-efficacy beliefs appear to have contributed to the stagnation of Hunor’s self-regulation. At data points 18 and 21 (Interview Excerpts 9 and 10), Hunor revealed that he perceives himself as a ‘bad writer’ even in his mother tongue. It might be speculated that Hunor constructed a negative identity of being a ‘bad writer’ throughout his language learning education which may have resulted in little investment (see Norton Peirce, 1995) in his writing tasks. Interview Excerpt 9 (data point 18) Interviewer: How do you see yourself as a writer? So, what kind of problems do you have? Hunor:  I don’t know maybe I’m not the best writer in Hungarian, too. Interviewer: Did you have problems, for example in Hungarian literature or grammar? Hunor: Not really but it is hard to express myself in a topic what I don’t really understand. Interview Excerpt 10 (data point 21) Interviewer: Do you like writing argumentative essays? Hunor: No, I don’t like these topics, these types of essays. Interviewer: Why? Hunor: I don’t know because when I learned in Hungarian… I was a bit bad in it… I don’t know, I got bad marks… for every essay.

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Interview Excerpts 5–10 show that boredom, frustration and low selfefficacy belief might have contributed to the stagnation of Hunor’s motivational system and, consequently, this may have constrained his engagement with the writing tasks more generally, a situation which is reflected in the stability of his linguistic complexity across the nine-month period. The finding for Hunor here aligns with Nitta and Baba (2018), who found that their participant with limited engagement employed less elaborate self-regulatory processes, which was reflected in little change in the learner’s linguistic development in L2 writing. Discussion

This case study demonstrated that lexical and syntactic complexity indices developed nonlinearly, showing ebbs and flows over the nine-month investigation in line with previous CDST studies on L2 writing development (Penris & Verspoor, 2017; Verspoor et  al., 2008, 2017). Although the smoothing algorithm of the general lexical complexity (AveWL) index displayed a slightly upward trend over the nine months, statistically significant developmental peaks were not detected in Hunor’s argumentative essays during this time. While the smoother of the general syntactic complexity (FVR) index showed a sideways trend over the nine months, the linear trend line displayed a downward trend suggesting that Hunor did not improve in general syntactic complexity. Moreover, the variability analyses did not detect a statistically significant developmental peak in the FVR index. These results show that Hunor’s trajectory is not consistent with other studies of advanced EFL students’ linguistic complexity development in L2 writing (Penris & Verspoor, 2017; Verspoor et  al., 2017). Hunor’s trajectory is also not consistent with the case presented in Wind (2018) in which a statistically significant developmental peak was detected in the academic word list (AWL) index and with the case in Wind (2018) in which a statistically significant developmental peak was revealed in the accuracy (EFC/C) index. The findings of this study are, however, noteworthy in their exceptionality as Hunor attended the same EAP course as the participants in Wind’s (2018) study. These findings underscore the usefulness of the case-study method in identifying developmental trajectories (or periods of stability) among individuals within the same cohort. A connection can be drawn, however, between the observation of stability in Hunor’s lexical and syntactic complexity and the notion that his self-regulatory processes appeared to be in an attractor state. Hunor’s self-regulatory processes developed nonlinearly over the nine-month investigation in line with previous longitudinal studies on self-regulation (Nitta & Baba, 2015, 2018). Although his focus shifted slightly between the performance phase (self-observation) and the self-reflection phase (self-evaluation), Hunor’s focus did not shift from the self-reflection

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phase to the forethought (goal-setting) phase over the nine-month investigation. The absence of goal-setting and the lack of critical and elaborate self-evaluation processes indicated that Hunor might be a ‘naïve selfregulator’ (Nitta & Baba, 2018). Zimmerman (2002) has suggested that naïve self-regulators are either oblivious to the need to self-evaluate their learning efforts or actively avoid these opportunities. The limited number of shifts between performance and self-reflection phases in the evolution of Hunor’s self-regulatory processes indicated that an attractor state might have dominated his L2 learning experience. Hunor reported that he frequently experienced boredom during the writing sessions of the EAP course. Waninge (2015) similarly found that boredom was one of the four attractor states in students’ L2 learning experience. However, Hunor’s boredom was also combined with frustration with his inability to access appropriate lexis, and with his sense of low self-efficacy as a writer (whether in English or in Hungarian). This complex interplay between boredom, frustration and low selfefficacy belief appears to have formed a powerful, deep attractor state in Hunor’s motivational system, which led to no noticeable gains in lexical or syntactic complexity over time. Despite the overriding goal to achieve a C1 level result on the IELTS, Hunor was not able to self-regulate to the extent that he could overcome a more immediate lack of interest and negative emotional response to the writing tasks. In a follow-up interview with Hunor conducted one year after the study had finished, it was interesting to note that by that time he had received an overall band score of 6.5 on the IELTS, which indicates that he had moved to the borderline of B2/C11 in his overall proficiency. Conclusion

The findings of this case study have important theoretical and methodological implications. First, the study provides further empirical support for the theory that self-regulation and motivation are likely to play a crucial role in L2 writing development, in line with Kormos’s (2012) projections. However, this study also shows that linguistic and self-regulatory systems may interact over time, and that motivational constructs might combine to affect the efficient use of self-regulatory processes, and constrain the development of linguistic complexity. In dynamic parlance, the linguistic and self-regulatory systems develop co-adaptively and sometimes these systems settle into attractor states. The study also provides insight into the nature of these attractor states, providing further evidence in addition to Waninge (2015) of the negative influence of boredom, frustration and low self-efficacy on development. Second, adopting a longitudinal multi-wave research design, in line with the CDST approach, allowed for the investigation of dynamicity and nonlinearity in linguistic complexity and self-regulatory processes. The

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fluidity of linguistic complexity and the nuanced nature of self-regulation as it varies over time could not have been captured by a two-wave longitudinal research design. There are several limitations to this study. First, the interviews were relatively short and the interviewer avoided leading questions when asking about the future goals of the participant in order to avoid influencing the participant’s goal-setting. Consequently, it can be speculated that the participant might not have fully verbalised his goals during the interviews. Second, the findings of this case study cannot be generalised due to the ergodic principle (Lowie & Verspoor, 2019); however, the study may contribute effectively to theory-building. The study has two important pedagogical implications for language teachers. First, the topic of the writing prompts might have a substantial effect on the writing outcome. As this study shows, writing on a boring topic, such as language learning, might provoke a negative emotional response, which in turn spirals over time into a lack of engagement with the writing process itself. However, when controlled writing prompts are combined with naturalistic writing prompts, as in this study, a more reliable picture can be gained. Therefore, language teachers should carefully select motivating writing prompts for the language learners. Second, self-regulatory processes are likely to play an important role in L2 writing development. Therefore, teachers should facilitate the evolution of the students’ self-regulatory strategies in the L2 classroom as part of a holistic approach to writing pedagogy. Since self-evaluation processes seem to play a more important part in L2 writing development (Nitta & Baba, 2015), teachers might encourage students to engage in self-assessment practices. For example, educators might teach criteria for rating (Andrade & Valtcheva, 2009). Note (1) According to https​://ww​w.iel​ts.or​g/iel​ts-fo​r-org​anisa​tions​/comm​on-eu​ropea​n-fra​ mewor​k.

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Verspoor, M., de Bot, K. and Lowie, W. (2004) Dynamic systems theory and variation: A case study in L2-writing. In M. Hannay, H. Aertsen and R. Lyall (eds) Words in Their Places. A Festschrift for J. Lachlan (pp. 407–421). Amsterdam: Free University Press. Verspoor, M., Lowie, W. and van Dijk, M. (2008) Variability in L2 development from a dynamic systems perspective. The Modern Language Journal 92 (2), 214–231. doi: 10.1111/j.1540-4781.2008.00715.x Verspoor, M., Schmid, M.S. and Xu, X. (2012) A dynamic usage based perspective on L2 writing. Journal of Second Language Writing 21 (3), 239–263. doi: 10.1016/j. jslw.2012.03.007 Verspoor, M., Lowie, W., Chan, H. and Vahtrick, L. (2017) Linguistic complexity in second language development: Variability and variation at advanced stages. Recherches en didactique des langues et des culture. Les cahiers de l’Acedle 14 (1), 1–27. Verspoor, M., Lowie, W. and Wieling, M. (2019) L2 developmental measures from a dynamic perspective. In M. Paquot and B. LeBruyn (eds) Learner Corpora and Second Language Acquisition. Cambridge: Cambridge University Press. Waninge, F. (2015) Motivation, emotion and cognition: Attractor states in the classroom. In Z. Dörnyei, P.D. MacIntyre and A. Henry (eds) Motivational Dynamics in Language Learning (pp. 195–213). Bristol: Multilingual Matters. Waninge, F., de Bot, K. and Dörnyei, Z. (2014) Motivational dynamics in language learning: Change, stability, and context. The Modern Language Journal 98 (3), 704–723. doi: 10.1111/modl.12118 Wind, A.M. (2018) Second language writing development from a Complex Dynamic Systems Theory perspective: A multiple case-study of Hungarian learners of English. Unpublished doctoral dissertation, Lancaster University. doi: 10.17635/lancaster/ thesis/519 Zimmerman, B.J. (1998) Developing self-fulfilling cycles of academic regulation: An analysis of exemplary instructional models. In D.H. Schunk and B.J. Zimmerman (eds) Self-Regulated Learning: From Teaching to Self-Reflective Practice (pp. 1–19). New York: Guilford Press. Zimmerman, B.J. (2000) Attainment of self-regulation: A social cognitive perspective. In M. Boekaerts, P. Pintrich and M. Zeidner (eds) Self-Regulation: Theory, Research, and Applications (pp. 13–39). Orlando, FL: Academic Press. Zimmerman, B. (2002) Becoming a self-regulated learner: An overview. Theory and Practice 41 (2), 64–70. doi: 10.1207/s15430421tip4102_2 Zimmerman, B.J. and Kitsantas, A. (2007) A writer’s discipline: The development of selfregulatory skill. In P. Boscolo and S. Hidi (eds) Writing and Motivation (pp. 51–69). Oxford: Elsevier.

7 Competence Appraisals: Dynamic Judgements of Communication Competence in Real Time Peter D. MacIntyre and Samantha Ayers-Glassey

This chapter introduces the concept of competence appraisals, defined as ongoing assessments of competence along multiple dimensions that are made by actors and observers. Even as a speaker assembles and delivers her or his message, a self-evaluation of competence occurs continuously, which is integrated with the process of deciding what to say and how to say it. This concept of competence appraisals draws on Complex Dynamic Systems Theory (CDST), Action-Assembly Theory and Stimulus-Appraisal Theory.

There are significant benefits to looking at the ways in which language use creates intra-individual variability, a major theme of Verspoor and colleagues’ dynamic usage-based research (DUB; Verspoor et al., 2008). Verspoor et al. (2012) specifically noted that variability within a person, along with variation across persons at the same general level, creates considerable difficulty in clearly describing or estimating an individual’s level of language competence. The research literature on human communication often parallels concerns raised by taking a communicative approach to second language (L2) development. Communication scholars have also struggled with questions about conceptualising competence; Phillips (1983: 25) noted that defining communication competence ‘is like trying to climb a greased pole; every time you think you have it, it slips’. Over time, there have been a number of approaches to refining the definition and measurement of communication competence in the communication literature (Cupach & Spitzberg, 1981; Duran & Spitzberg, 1995; Larson et  al., 1978; McCroskey, 1982; Parks, 1994; Phillips et  al., 1991; Wiemann, 1977) with a resulting effect that can be likened to adding a little more grease to that slippery pole. However, Verspoor’s efforts over the years involved exploring alternative approaches to defining languagerelated concepts such as competence with a creative approach from which the field has greatly benefited. 155

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Inspired by Verspoor’s thinking, the present chapter takes an approach based on CDST (Larsen-Freeman & Cameron, 2008; Thelen & Smith, 1994). CDST provides a meta-theoretical perspective from which to examine ongoing assessments of competence, recognising the complexity within the ebbs and flows of communication processes. Exploring the ideas generated by a dynamic perspective reflects an attempt at climbing the greased pole from a different starting point – perhaps it will provide some traction for new directions in competence research even as it opens new challenges for scholars in focusing on both communication and L2 development. One of the significant challenges for conceptualising communication competence dynamically is to address the multiple dimensions on which competence can be assessed, including the role and relevance of the language dimension whether it is a person’s first, second, third, foreign or other language. Within the dynamics of an ongoing communication event, the language being used might be a major consideration but not necessarily the one prioritised over all other dimensions, and in some conversations between individuals the specific language used might be almost irrelevant. To be as generally applicable to communication processes involving language use as possible, the present chapter examines competencies using the communication literature as a base rather than the applied linguistics literature. Part of the reason we are directing the theoretical focus toward communication theory lies in the traditional notion in the L2 development literature that language competence refers to the internalisation of vocabulary and grammar knowledge (see Savignon, 2018). Canagarajah (2018) provided an analysis of L2 communication showing how limiting it can be to focus exclusively on the verbal account of authentic speech. The illustrative example comes from Tan, an international scholar teaching mathematics in English in the United States. Tan’s speech was described by Canagarajah as hesitant, incomplete, repetitious and with pronunciation difficulties that made transcription difficult. However, Tan’s teaching continuously integrated verbal (spoken words, inscriptions on the board) with non-verbal (visuals, gestures, movement, affective expression, etc.) communication, along with other resources including the classroom space and the board itself; students were focused and responsive to the lecture. A senior, native English-speaking teaching assistant, Adam, watched a recording of the classroom and commented that Tan’s teaching was excellent due to the quality of his board work which integrated verbal, non-verbal and contextual resources in meaning-making. In this chapter, we consider key processes that allowed Adam to make such a positive evaluation of Tan’s competence as he watched the video and to theorise how Tan might also have been continuously assessing his own competence as he did the board work.

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Defining Communication Competence

A tension exists in the communication literature between defining competence in relatively objective terms – based on observation or coding of behaviour – versus conceptualising competence as a person’s latent capability, a perspective in which competence is taken to be a communication trait that may or may not be evident during any particular communication event. The solution that has been used for many years has involved researchers separating competence from skill (Greene, 2016; Spitzberg, 2013; Verspoor et al., 2008). McCroskey (1982) noted that a representative definition was provided by Larson et al. (1978: 16), who wrote that competence reflects ‘the ability of an individual to demonstrate knowledge of the appropriate communicative behavior in a given situation’. If competence is tied to the immediate context, communication skill is treated as ‘the ability of an individual to perform appropriate communicative behavior in a given situation’ (McCroskey, 1982: 5). Spitzberg (1983) argued that communication competence is a function of knowledge, skill and motivation that ‘… can now be formally defined as the degree to which meaningful behavior is perceived as appropriate and effective in a given context’ (Spitzberg, 2013: 130). Within Spitzberg’s (2013) framework, ‘appropriate’ refers to the degree of how fitting, legitimate or acceptable a person’s behaviour is in a certain situation and ‘effective’ refers to accomplishing communicative goals. Further, a distinction exists between ‘communicative competence’ discussed in applied linguistics and ‘communication competence’ from the communication literature. The former is understood as a three-part construct involving strategic, grammatical and sociolinguistic competences (Canale & Swain, 1980; Savignon, 2018) and the latter is seen as a broader, overarching term described by Spitzberg (1983). For clarity, the present chapter will discuss competence from a communication perspective. The L2 competence literature provides a variety of ways to assess competence, including scores on standardised tests, course grades and other feedback from instructors. More generally, competence criteria have become coded in categories of competence such as those from the influential Common European Framework of References (CEFR) for Languages (Council of Europe, 2001). The CEFR is a multifaceted approach to competence, but here we draw attention to its broad categorical classifications such as ‘basic user’ (Levels  A1–A2), ‘independent user’ (Levels B1–B2) and ‘proficient user’ (Levels C1–C2) based on the individual’s ease of completing productive and receptive communicative tasks. The CEFR uses communication performance to indicate underlying skill, with a focus on what a person is capable of doing. The CEFR formally defines competence as the ‘sum of knowledge, skills and characteristics that allow a person to perform actions’ (Council of Europe, 2001: 9) accumulated over time, reflecting a person’s potential for successful language use.

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Although a distinction between competence and skill has persisted in both the native language (L1) and L2 communication literatures for quite some time, key issues arising from these definitions are yet to be addressed. In almost any life domain that one could imagine, specific communication behaviour judged to be appropriate in one context will not necessarily be perceived as appropriate in another, and even small changes in context can have a dramatic effect on what is considered appropriate or competent communication. Questions of appropriateness strongly implicate contextual factors in the assessment of competence, yet it can be difficult to specify in advance all the possibly relevant dimensions on which appropriateness and competence might be evaluated. In particular, the Spitzberg (1983) definition of competence in terms of appropriateness and effectiveness begs the question: what do ‘appropriate’ and ‘effective’ mean in practice? Refining the question further, we might ask: appropriate or effective for what purpose, within what context, as judged by whom and using what criteria? Different individuals judging competence may have somewhat different perspectives on communication behaviour that is acceptable or preferred within a given context. For example, a political speech will generate different reactions among supporters than opponents, a comedian’s raunchy jokes may be enjoyed by some in the audience but not others, a technical talk may be informative for experts but not for novices. The notion that competence criteria change from person to person is further complicated by the observation that the criteria also might change within a person over time, even as an event unfolds. In a teaching context, a learner’s classroom presentation might be articulate, informative, grammatical and well planned, but his classmates might lose interest in the topic and begin to talk incessantly among themselves during the presentation. Has the learner demonstrated communicative competence? By adopting a highly contextual approach, such as that required by the CDST, and by allowing for multiple criteria of competence judgements, the best answer to the question seems to be ‘yes’ and ‘no’ depending on the appraisals made by various persons in the situation and how those appraisals change during the communication event. Therefore, the criteria on which competence judgements are made and how they change from person to person over time become the critically important factors for understanding the reasons for judging higher or lower levels of competence. There is a subjective component to competence judgements. Alongside conceptualising communicative competence in relatively objective terms is the need to consider the perception of competence because that perception may be especially relevant to the way the communicative event unfolds. ‘Since the choice of whether to communicate is a cognitive one, it is likely to be more influenced by one’s perceptions of competence (of which one is usually aware) than one’s actual competence (of which

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one may be totally unaware)’ (McCroskey & Richmond, 1991: 27). Several terms related to the perception of one’s competence have been used in the literature, including self-efficacy (Hsieh & Schallert, 2008), self-perceived oral proficiency (Dewaele, 2007) and self-perceived communication competence (McCroskey & McCroskey, 1988). Concepts such as self-efficacy, self-perceived oral proficiency and self-perceived communication competence refer to long-term timescales evaluated over months or years, much like the competence levels assessed by the CEFR. However, if subjective judgements become the focal point of competence judgements, the timescale can be narrowed to momentto-moment fluctuations during communication and then a wide range of internal and external factors come into play. According to Horwitz et al. (1986), positive self-perceptions of communication competence are: rarely challenged when communicating in a native language as it is usually not difficult to understand others or to make one understood… [however]… because complex and non-spontaneous mental operations are required in order to communicate at all, any performance in the L2 is likely to challenge an individual’s self-concept as a competent communicator and lead to reticence, self-consciousness, fear, or even panic. (Horwitz et al., 1986: 128)

The ability of an individual to continuously evaluate the proceedings of a communicative event in which they are participating, as the event unfolds in real time, is necessary to effectively repair or compensate for mistakes, clarify meaning and deal with any misunderstandings that may occur. This continuous assessment process is necessary to effectively enact the strategic (Dewaele, 2010) and pragmatic (Cohen, 1997) dimensions of competence, both of which involve continuous testing of the quality of communication. To facilitate theorising the process of assessing competence on the fly, we turn to CDST. Complex Dynamic Systems Theory

A CDST approach reflects a burgeoning perspective in studies of language acquisition (de Bot et al., 2007; Larsen-Freeman, 2007), developmental psychology (Lavelli & Fogel, 2002; Lichtwarck-Aschoff & van Geert, 2004; Thelen & Smith, 1994), communication (Fogel, 2006) and other scholarly areas. Examining interpersonal communication competence from a dynamic perspective seems to be a potentially productive approach due to the constant interactions existing among elements of the communication system. For example, in addition to their own perspective, a communicator must also take into account their observer’s point of view as co-constructed with the other actors (Fogel, 2006). As such, communication is a process that constantly changes the context in

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which it is located. As defined by Thelen and Smith (1994: 258), ‘the term dynamic systems, in its most generic form, means systems of elements that change over time’. Therefore, CDST is an appropriate perspective from which to examine how communication competence develops as a broadly applicable skill, and how it is both enacted and understood within a given situation by the people involved. Similarly, in L2 studies, the DUB approach recognises dynamic variability within and between individuals during language acquisition and usage: Within a DUB perspective, one would expect differences among L2 learners, resulting in diverse individual trajectories and plenty of trials and errors along the way. The assumption is that many predictor variables such as L2, age, intelligence, verbal aptitude, motivation, type of exposure, or context, will interact in complex ways to determine L2 acquisition. The term ‘dynamic’ implies that the current level of development depends critically on the previous one. (Verspoor et al., 2012: 241)

Thus, the use of a dynamic approach (i.e. CDST, DUB) to examining communication competence and appraisals could aid in recognising factors contributing to fluctuations within and between individuals throughout communicative events. CDST emphasises an understanding of the process of change but avoids ascribing linear cause–effect explanations. Rather, change is reflective of the state of the system being altered by interactions that occur among multiple subsystems and variables, impinging on the system in the present context. Communication as a system cannot be exactly the same at two different times (Fogel, 2006). The timescale in which a dynamic system can be examined varies from studies of moment-to-moment fluctuations, measured in seconds or fractions thereof (MacIntyre & Legatto, 2011), to studies of development that take place over days, months, years or longer (Verspoor et al., 2011). Furthermore, dynamic processes such as communication take place over interacting timescales. In other words, as de Bot (2012: 11) explained, ‘Development on one scale is influenced by what happens on smaller and larger scales, and development at these levels will have an impact on what happens on the timescale in focus’. CDST also recognises elements of uncertainty and randomness that affect systems over time. Within each system are a number of moving parts assembled to coordinate action. For example, in physical development, the act of walking involves muscles, bones, blood circulation, neural connections and other physical systems which coordinate in a slightly different way when dancing, climbing a tree or driving a car. The specific bits and pieces assembled in the action of a system can change as various systems interact with each other over time. This variability makes it impossible to be able to completely predict the future patterns

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of a fluctuation even in a simple dynamic system, let alone in a system as complex as human communication. Yet, systems tend to be governed by principles of self-organisation and emergence: an emergent quality that is more than the sum of its parts helps make the system itself both coherent and comprehensible, even if it is not always perfectly predictable. Dynamic systems may settle into periods of relative stability called attractor states, which are similar to the stable states of chemical reactions that follow a period of volatility, and instability called repeller states in which change is imminent (see Chapter 6 of this issue). CDST principles apply to communication behaviours and can be used in the study of communication competence. As a person engages in communication, the context itself is changed by what is said or not said, non-verbal actions or reactions, the reactions of an interlocutor, the external context and many more contextual factors. Given the fluctuations within a communicative episode, we are likely to observe peaks and valleys in perceptions of communicator competence made by the actor and observer, as their assessments of competence fluctuate over a short time. To illustrate, within a classroom presentation an L2 speaker might tell an engaging opening story but then awkwardly shift topics. That same story could not be received in the same way by the same listeners a second time, even within the same speech. In judging competence, ‘appropriate’ does not mean flawless; adding and subtracting mistakes from a checklist or aggregate test score can lead to a potential misunderstanding of a speaker’s overall effect on a listener’s sense of appropriate, meaningful communication. In practical applications, it can be difficult to predict the effect of a mistake or attempted recovery on an audience in advance, yet such effects can be described after the fact – albeit likely with some degree of variance among the persons in the audience who are individually judging the speaker’s competence. It is possible for a highly competent speaker to recover from a gaffe with self-deprecating humour, which actually increases the audience’s perception of that speaker’s competence. When considering any phenomenon from a CDST perspective, the timescale under study is a critically important consideration. It is easy to imagine why summative ratings of a specific speech or conversation at the microlevel (a timescale of minutes) might differ from those made over a semester-long course (a timescale of months) or over a person’s career as a speaker at the macrolevel (a timescale of years). Broad patterns of stability at one level can obscure considerable amounts of variability at another level (Fogel, 2011). Specifically, measures of competence considered on a per-second timescale, made continuously in the moment, can show considerable variability during the ebb and flow of a single speech segment as it unfolds, even as the speaker remains at the same broad level of competence (e.g. Level B1 in the CEFR). Viewed in this way, the bifurcation of competence-as-performance and competence-as-skill is

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not particularly informative because the timescales are different. Performance considerations tend to have a brief timescale, whereas questions of skill take a longer view. There are several examples of shorter- and longer-term summary measures of competence already in the communication literature (e.g. Shen et al., 2012; Spitzberg, 2011). However, ways of making dynamic assessments on a very brief timescale, rising and falling second by second, have not yet appeared. Perhaps one reason why competence ratings tend to take the long view is that L2 researchers and teachers often think of the language development process from an educational viewpoint rather than a communication one. Education is a long-term process, but communication is assembled in the here and now. Communication competence from an education perspective emphasises long-term patterns of development, as in the levels defined by the CEFR. Competence from a communication perspective can address more directly the variability in momentto-moment interactions and the dynamics of language use (Verspoor et  al., 2012). In order to describe what is happening with competence assessments on a brief timescale, measured in seconds, it is necessary to consider two key processes: putting words together to create a communication episode and how a communication episode is assessed on a continuous basis. To deal with these two processes, we appeal to ActionAssembly Theory and Appraisal Theory, both of which focus on the necessary timescale although they both predate the introduction of CDST in the field of L2 development. Action-Assembly Theory

Adopting a dynamic perspective requires that the concept of competence be drawn closer to the cognitive processes underlying communication: choosing what to say and how to say it. Greene (1984, 2013, 2016; Greene et  al., 2000) proposed Action-Assembly Theory as an explanation for how individuals create and produce both verbal and non-verbal behaviours. Two key processes underlie the process of choosing what to say: activation and assembly. The activation system is the initial stage when a person sorts through procedural records in their memory. These records are stored in long-term memory and offer a wealth of information about what to expect in specific situational contexts such as information regarding certain actions, outcomes and situations (Greene, 1984). For example, eating an excessive amount of ice cream (action) in a short amount of time (situation) might result in a short-lived but intense headache (outcome). After experiencing this specific situational context for the first time, this information will be stored in memory. However, procedural records can have different levels of strength in which ‘some are mere scratches that barely leave a trace in our minds, while others are well-worn paths in long-term memory’ (Janis, 1994: 116). Some word

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pathways are used more appropriately in conversation than others. The phrase ‘ice cream headache’ is fairly common in speech and can be easily understood by an audience; therefore, it is more likely to be judged as appropriate in multiple contexts than the technical term for the same condition, sphenopalatine ganglioneuralgia, which might only be judged appropriate among medical professionals or possibly in a trivia game. Following activation, the assembly process begins. This process organises the activated procedural records into what Greene (1997) calls a larger behavioural complex, where the specifications for action are created. Features are activated and assembled into a complex form or output representation, that is, procedural records matching the relevant goal and situational context of the individual (Greene, 1995). Procedural records are enacted if they are appropriate in context. The process of assembly usually runs smoothly in the background. However, problems can and do arise when action features do not fit together well, that is when an individual can become aware of difficulties in the action-assembly process. For example, there can be an occasional trade-off between answering a question honestly and avoiding hurting another person’s feelings, as when a friend asks, ‘do you like my haircut?’ but you do not like it at all. The question demands a rapid response because hesitating to answer can be taken as a negative response. Very quickly after the question is asked, several different procedural records are activated that can be enacted, such as to respond honestly, to obfuscate or to change the subject. Other examples of becoming aware of action-assembly problems include the ‘tip of the tongue’ phenomenon (Greene et al., 2000) and hesitation in L2 speech (MacIntyre & Doucette, 2010). Greene (2006) recognised that the process of deciding what to say and when to say it may not be as rigid as originally proposed in his ActionAssembly Theory, leading to the development of ‘second-generation’ Action-Assembly Theory. The revised theory ‘is an attempt to specify the mechanisms by which the output, so conceived, is produced, momentby-moment, during ongoing interactions’ (Greene, 2013: 152), indicating that the process of planning and deciding what to say may be more dynamic than originally proposed. Second-generation Action-Assembly Theory introduced the concept of ‘coalition formation’ (Greene, 1997), a term given to the process whereby appropriate features are joined together to produce action, essentially replacing the more sequential, linear assembly process in the original theory (Greene, 1997; Greene et al., 2000). The processes of activation and coalition formation run in parallel: several features are activated while a number of coalitions may be operating at the same time. It takes only a fraction of a second for action features to be activated and to decay back to their resting level (Greene, 1997; Greene et al., 2000). Joining the action-assembly process with an ongoing assessment of competence allows examination of the links between communicative behaviour on the one hand, and dynamic

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(rising and falling) perceptions of competence on the other hand in real time. Given the complexity of communication and its implications for relationships, identity, self-presentation and so on, it would be a mistake to think of action assembly in terms of ‘cold cognition’, devoid of influences from the emotions. Comparatively, Appraisal Theory is designed to address the ongoing emotional ties to cognition. Appraisal Theory

Action-Assembly Theory links competence assessment to the cognitive process of deciding what to say and how to say it; however, we also need to implicate emotions and processes related to the self. Appraisal Theory is an umbrella term used to describe a set of theories that address how a person’s interpretation or evaluation of an event, as well as the event’s potential impact on one’s well-being, both influences and is influenced by the continuous emotions that accompany it (Ellsworth, 2013). Appraisal theories can describe the continuous intersection of cognition and emotion. One of the influential early theories of appraisals was Lazarus and Folkman’s (1984) model of stress reactions, which popularised the idea that events themselves are not necessarily stressful, rather the appraisals of events guide whether a situation is perceived as stressful by any specific person. Kappas (2006: 957) outlined the qualities of appraisals as follows: (1) Appraisals are typically automatic evaluative processes: they are direct, immediate and intuitive. (2) Immediate appraisals can be sufficient to elicit action tendencies/ behaviours/emotions. (3) Appraisals can also be reflective and can modify ongoing emotions indirectly by changing the intuitive estimate. Lazarus’s (1991a, 1991b) well-known Cognitive-Appraisal Theory originally focused mostly on coping with stress and the emotions that accompany the coping process. Cognitive-Appraisal Theory originally specified two key processes that were thought to occur simultaneously: the primary appraisal of a situation as an assessment of whether there was something personally relevant, and a secondary appraisal as assessing whether one possessed the resources necessary to cope with the situation. Later, Lazarus and colleagues defined a three-part theory of appraisal that incorporated the functional relations among cognition, motivation and emotion (Lazarus, 1991a). According to Lazarus (1991b: 819), ‘An emotion theory should be a systems theory, encompassing a number of interdependent cause-and-effect variables and processes, which follow the fluid principle of reciprocal determinism (Bandura, 1978, 1983)’. The idea of reciprocal determinism brings forth the complex interactions

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among the many attributes of the person, the relevant aspects of the environment and the person’s actions or behaviour, any of which might cause changes in the other elements whose effects feed back into the ongoing, functioning system. Thus, the inclusion of multiple, interacting factors that influence ongoing behaviour, cognition and emotion provides a combined molarand-molecular perspective on the processes occurring during emotional appraisals (Smith & Lazarus, 1993). That is, appraisals contribute to a general ‘core relational theme’ for emotional experiences that describe the thought and action tendency typically generated by specific emotions (e.g. threats lead to anxiety-themed emotions, loss leads to an emotional theme of sadness, and so on with other emotions). However, appraisals that occur in situ are more molecular and provide the instantiated reasons why a situation is perceived to be personally relevant and the specific personal resources that can be used to cope with the situational demands. There will be a number of detailed, specific considerations in any given communication event, suggesting that appraisals are multidimensional, always somewhat idiosyncratic, tied to the local context and being made and re-made continuously as time goes on. It is important to note that appraisals are not one-time or occasional occurrences, rather they are always running in the background, continuously influencing one’s ongoing experience. Smith and Lazarus (1993) stated: …there is a danger that we will be interpreted as implying that appraisal is a conscious, volitional, verbally accessible process that requires deliberation and considerable time. On the contrary, we have been consistent in maintaining that appraisal can be automatic (even primitive) and instantaneous and can occur outside of consciousness. (Smith & Lazarus, 1993: 629)

As with other theories of appraisal, there are several dynamic functional relations occurring as an appraisal is made. In other words, there are ever-present interactions occurring among relevant factors. According to Lazarus (1991b), these interactions include: (1) a bi-directional relationship between cognition and emotion, as emotions can be seen as both responses to and influences on thoughts and interpretations; (2) cognitions – including general knowledge of how things work in the world and an evaluation/appraisal of the event – acting to both provoke and re-evaluate behavioural responses; and (3) motivations (i.e. goals, values, personal interests) contributing to the understanding of why an event might be personally relevant, how it fits with goals, beliefs, interests and experiences contributing to the mild or strong intensity of the emotional response.

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Action-Assembly + Appraisals

If appraisals are ongoing processes within a communication event, the process of modifying action-assembly coalitions as communication unfolds must be linked to a self-assessment process in which persons are constantly evaluating how well they are doing as events take place. Such a process potentially allows a communicator to know immediately when something has gone wrong during communication, possibly as a result of audience feedback or a self-assessment. Gray and McNaughton (2000) examined the septo-hippocampal circuit of the brain which checks on whether events unfold as expected (‘okay mode’) or not as expected (‘not-okay mode’). If events are being evaluated as ‘okay’, a person will proceed with the communication smoothly and competently; if events are ‘not-okay’, then an arousal reaction can be triggered. With increasing arousal, coping mechanisms may be activated to deal with this ‘not-okay’ event to restore the ‘okay’ state. The decision-making process associated with the coping response will occur rapidly and unconsciously. McNaughton and Corr (2004: 299) stated, ‘(t)he time course for decision making will be very swift, of the order of tens of milliseconds, while that for arousal is necessarily slow with autonomic and hormonal actions having latencies of the order of seconds’. Thus, the ongoing unconscious evaluation of whether events are ‘okay’ or ‘not-okay’ occurs in real time along with the action-assembly process. Therefore, they can be conceptualised as two interacting dynamic systems. When communication is perceived to take an unexpected negative turn, a speaker’s focus can rapidly shift to coping efforts and the assembly of new messages. Within a period of a few seconds, if the communication has not been repaired in a manner that returns the speaker to an ‘okay’ state, emotional arousal might intensify. A rapidly declining sense of competence can be linked to a rising anxiety response, activation of the fight-flight-or-freeze response and the potential for distracting, selfrelated cognition (Eysenck, 1979). Thoughts associated with increasing anxiety tend to focus on assessing the consequences of ongoing events and possibly planning for a face-saving escape from the situation. Within the potential escape planning process will be the activation of potential coalitions that include speech acts that apologise for errors, offer explanations or excuses for difficulties, avoid or change topics and so on. In essence, these coalitions compete with task-related cognition for the chance to be enacted. Consider how the repair phrase ‘what I meant to say’ is used in conversation. The phrase reflects awareness of inappropriate communication and the formation of a new, possibly more appropriate coalition. By using the phrase ‘what I meant to say’, a speaker might be revising or repairing not only the form, function, meaning or content of what he or she said, but also the relationship with the interlocutor in an attempt

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to cope with having said or not said, done or not done, something that triggered the ‘not-okay’ self-assessment circuit. The success itself of the action-assembly process in coping with miscommunication reflects higher communicative competence, even as the misstep that generated the need to do so seems to reflect lower competence. The numerous interactions among systems at play including the individual’s physical, emotional, memory and cognitive systems, the various dimensions of verbal and non-verbal communication, the active perception of self and others and other factors make changes in the integrated perception of competence at moments of uncertainty or conflict that are difficult to predict a priori. When the appraisal process is directed towards assessing communication competence, we can identify multi-level assessments (both rapid/ intuitive checking and a more reflective process) closely tied to how a person’s sense of self relates to the immediate context. Generally, appraisals are tied with both emotion and coping efforts (Ellsworth, 2013; Lazarus, 2001). Competence appraisals produce holistic, grossly or finely graded assessments based on the criteria relevant to a person’s sense of wellbeing and appropriate action, at a specific moment in a specific situation, and can take into consideration both performance skill and potential. It is important to note that the criteria for competence appraisals can change within-person even as communication unfolds moment by moment and as multiple goals within a communicative context are being successfully achieved and/or threatened. Appraisals can be jeopardised by misunderstandings of meaning, misinterpretations of words and phrases, unexpected or embarrassing self-disclosure, violations of cultural or group norms, unusual timing of utterances, inconsistencies between verbal and non-verbal behaviour and many other factors (Kappas, 2006). Within the L2 domain, Schumann (1997) identified five categories of stimulus appraisal that are relevant to competence appraisals: novelty of the situation, pleasantness of the situation, the situation’s contribution to one’s goals or needs, coping potential to handle the situation and how the situation may be compatible with one’s self-image. The sources of information that an individual might use to evaluate competence are extensive and difficult to list exhaustively, but would include ease of retrieval from memory, non-verbal feedback from an interlocutor, reaction of others involved in the conversation, comparison of present and goal states, expectations for one’s capabilities along with surprising successes or missteps, felt emotions, meaningful understanding of discourse and exchange of information that is either consistent with or divergent from conversational expectancies, and other sources of information. Appraisals of competence are made along multiple dimensions and integrate information from multiple sources both internal and external to the person, including self-perceptions, emotional reactions, ongoing cognition and verbal and non-verbal feedback from other persons.

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If an ongoing assessment of communication competence overlays the action-assembly process, then we have a novel basis on which to approach defining communication competence which requires conceptualising a rapid, continuous assessment process. Appraisal Theory provides the basis on which to propose such continuous, personally relevant assessments. Competence appraisals can be defined as an individual’s ongoing process of evaluating the effectiveness and/or appropriateness of communication using salient criteria that may change over time and which are partially established in situ. Consistent with CDST, the competence appraisal made at any given moment is partially a function of prior appraisals, helps set the context for future appraisals and may potentially influence the communication process itself via changes in the cognitive and emotion systems. Figure  7.1 presents a graph of a hypothetical example of competence appraisals. It shows five dimensions of appraisals based on Schumann (1997), although other dimensions of communication competence appraisal could be relevant. In this hypothetical example, a student is giving a presentation in her psychology class on the topic of flow theory (e.g. Csikszentmihalyi, 2013). The speaker is well prepared and is generally feeling competent while explaining the topic to the class. However, despite practicing in advance, she fumbles over the name of the theory’s author, Csikszentmihalyi, noticeably mispronouncing it (see Figure 7.1, Time 1). Imagine that everyone in the room laughs, including the professor. At this moment, the ‘not-okay’ mode is activated for the speaker and arousal increases rapidly even as she begins to cope with her mistake. At that moment, the activity in several systems changes in a coordinated set of actions: physically, the speaker’s face feels flushed and she begins to perspire; cognitively, she loses her train of thought as the action-assembly process activates several possible options including ignoring the mistake, 10 8 6

#1: New topic-Word pronounciation error

#2: Similar topic -better coping

4 2 0 -2 -4

Competence Appraisal

-6

Novelty

-8

Coping Potential Word Choice

-10

pleasantness

Figure 7.1   Hypothetical changes in five dimensions of appraisals

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apologising, trying again to pronounce the name and possibly other verbal responses; emotionally, she feels increasing anxiety and the perceived pleasantness of the situation quickly drops; non-verbally, her hands move up, palms toward the audience in a ‘wait’ gesture, she stops speaking for a moment and appraisals of her perceived coping ability are activated. The topic of flow theory is perceived as more novel than it had been just moments before. Imagine that the speaker responded by simply allowing the mistake to lie, waiting a few seconds for the room to calm down and then continuing the presentation as if nothing happened. Moments later, at Time  2 (see Figure  7.1), the name Csikszentmihalyi occurs again but this time practice pays off and the theorist’s name is pronounced correctly. At this next salient moment, the hypothetical speaker feels a surge in her coping potential, higher communicative competence and the pleasantness of the situation increases again. Perhaps she notices a few reflected appraisals from the audience whose non-verbally supportive expressions (smiles, head nods) suggest that at least some of them empathise with the presenter. Among audience members, different trajectories of competence appraisal ratings likely would be seen. Following the mistake, an empathetic listener might assess the speaker as highly competent and resilient in the face of adversity, followed by enhanced ratings based on successful recovery in a difficult situation. A more critical listener might have assessed competence at Time  1 as low given that the speaker flubbed a key name in the presentation, holding that mistake in focus as the speaker later recovered to where she should be. As such, even in a simple example covering only a few moments of time, appraisals of competence can change dramatically both within and across persons; appraisal is a dynamic process for both the speaker and the listener. Competence Appraisals from Actor and Observer Perspectives

If competence appraisals vary with the perspective from which the assessment is made, framing the issue in terms of the actor–observer differences can help illustrate some of the ways in which perspectives might systematically differ. In social psychology, the well-known actor– observer bias has been described as a tendency for actors to ascribe successes to their own stable attributes (such as skill) and failures to external elements of the situation; the reverse tendency has been reported among observers (Jones & Nisbett, 1972; Malle, 2006). Prior research indicates that people tend to perceive themselves to be more competent communicators than others might perceive them to be (Malle et al., 2007; Spitzberg, 2013). Actor–observer differences are based on differences in access to information: only actors have introspective knowledge and comprehensive access to self-related memory of prior experiences, against which

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present performance can be evaluated (Malle et al., 2007). In the example presented in Figure 7.1, the actor and observers might experience different motives for impression management during communication. The presenter (actor) is likely motivated to appear informed and competent to her peers and professor, but the observers might have very different goals with which to evaluate the communication event. Friends in the audience might sympathise with the speaker and judge her communication to be effective, while others might have competitive motives, seeing the speaker as a rival for top grades in the class and thus harshly judge her for any mistake. Finally, the professor might be focused primarily on the speaker’s effective presentation of theory, using appropriate terminology. Different motives are part of each individual’s appraisal process and can influence the perceptions of competence held by different people, which influences the trajectory of reactions to the events. Figure 7.1 shows the hypothetical ratings of the actor; observers might show a variety of very different patterns. The literature shows a complex relationship between competence judgments of actors and observers, and under some conditions the correlation between them can be near zero (Carrell & Willmington, 1996). Other research has shown systematic bias in the correlation between actor and observer; McCroskey and McCroskey (1988) proposed that self-report is most likely positively biased, based on such factors as the respondent’s self-esteem. That is, a general bias towards self-enhancement in self-reports might exacerbate the tendency for positive selfrelated bias: ‘…normal human thought and perception, is marked not by accuracy but positive self-enhancing illusions about the self, the world, and the future’ (Taylor, 1989: 7). The opposite tendency, self-deprecating cognition, might be observed in other situations. For example, from a person who is anxious or depressed (Noles et  al., 1985) or low in self-esteem (Campbell & Fehr, 1990). Finally, it is possible that actors and observers agree on their appraisals. John and Robbins (1994: 217) concluded that ‘self-perceptions generally correspond with perceptions by others’, justifying the construct validity of self-report and its use in a large body of research (for an example, see MacIntyre & Serroul, 2015). From a dynamic perspective, the question is not necessarily best phrased in terms of what the comparative biases in appraisals are, but rather, when do competence appraisals reflect positive versus negative biases, and when do the processes reasonably converge on similar assessments of competence? Further, we might consider in more detail why competence ratings vary in any particular example. It should be possible to allow that all three outcomes (positive, negative and near-zero bias) take place, even in the same communication event as presented in the foregoing hypothetical scenario. Therefore, a different set of research questions can be generated to examine convergence and divergence in competence appraisals, along with a method of addressing competence

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on a second-by-second basis, allowing for the examination of both actor and observer perspectives. Given the idiosyncrasies of each specific communication event and the concern for the unique rationale underlying competence appraisals, it is informative to study competence appraisals as an intra-individual phenomenon rather than aggregated scores across persons. Summing and averaging over persons breaks the tight bond between competence appraisals and the reasons for them. If the goal is to interpret actors’ understanding of their own competence appraisals, the tricky issue of conscious reporting comes into play. Appraisals typically run continuously in the background of conscious experience; they are often an unconscious process. Reporting directly and completely on competence appraisals will not be possible all of the time. Operationalising the issue in terms that are familiar to learners/speakers is necessary for research into competence appraisals. Future research into competence appraisals might begin with a more familiar construct such as self-confidence, which reflects an individual’s integrated perception of how well they are doing in a communication episode, on an ongoing basis, based on combining multiple sources of information into a coherent whole. Clément (1980, 1986) defined self-confidence as a secondary motivational process reflecting low anxiety and high ratings of competence, reflecting an integration of cognition and emotion processes in evaluating competence (Dewaele, 2010). If self-confidence can be considered an emergent state of the system of which one can be fully aware and report more or less continuously (if asked), then the competence appraisal process can be said to be the major influence on dynamic self-confidence.1 Dynamic self-confidence operates in real time, meaning that it can serve as a research catalyst to highlight additional psychological processes relevant to language use that can affect language development over time. On a brief timescale, the idiodynamic method (MacIntyre, 2012) could be used to track fluctuations in self-confidence in real time. Idiodynamics asks a speaker to rate a video recording of a speech sample at a pre-determined rate, such as once per second, which would allow researchers to connect changes in self-confidence to the use of various elements of language such as novel or difficult grammatical structures, new idioms being learned, specific word choices or non-verbal strategies being employed. On a longer timescale, self-confidence ratings could be added to a longitudinal case-study design such as the one used by Spoelman and Verspoor (2010), who described in detail the development of word and sentence complexity in the writing of a Dutch speaker learning Finnish over a three-year period. Adding regular measures of self-confidence that capture the self-related cognitive and emotional reactions accompanying language development would offer an even richer account of intraindividual variation. It is easy to imagine that a learner’s self-perceptions such as pride in one’s success, embarrassment over failures or anxiety about making mistakes will change with experience. Changes likely

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occur in a complex fashion as self-perception interacts with the expectancies of self and others. For example, the errors of novice learners are often evaluated very differently from those of experienced learners who ‘ought to’ know what to say (see MacIntyre & Serroul, 2015). Conclusion

The concept of competence appraisals suggests that people engaging in conversation are continuously making evaluations about their own competence, as well as the competence of the other person(s) involved, as communication unfolds in real time. The evaluation process continues even as speakers unconsciously plan and execute the communication process. This is a novel application of Appraisal Theory integrated with Action-Assembly Theory, updated with CDST. The combined theoretical perspective suggests that the complexity of communication extends beyond the processes described exclusively by Action-Assembly Theory. A speaker is not only thinking about what to say and how to say it, but dimensions of competence appraisals are integrated into and affect cognition, emotion, motivation and, in particular, dynamic feelings of self-confidence that are all tightly integrated within the communication system. Note (1) Such a state was implicated in the pyramid model of willingness to communicate (WTC) where the two most immediate influences on WTC were state self-confidence and having a desire to talk to somebody (see Sulis et al., Chapter 8, this volume).

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8 Dynamic Changes in Motivation and Willingness to Communicate in the Second Language Classroom: A Multiple Case Study Giulia Sulis, Joanna Davidson and Marije Michel

Recent years have seen extensive research exploring changes in second language (L2) motivation and willingness to communicate (WTC) across different timescales (see Dörnyei et al., 2015; Mystkowska-Wiertelak & Pawlak, 2017). However, only a handful of studies to date have investigated their fluctuations in an authentic L2 classroom context, and even fewer have explored the relationship between these two constructs from a dynamic, situated perspective (e.g. Peng, 2014). This chapter seeks to address these gaps by investigating the dynamic development and interrelationship of WTC and motivation over the course of two 45-minute lessons. This chapter begins by reviewing earlier theoretical and empirical work into L2 motivation and WTC, specifically from a dynamic perspective. We then provide details of the method, design, data coding and analysis of the study before presenting and discussing the results. The chapter concludes by discussing directions for future research and formulating implications for the L2 classroom. Introduction

Over the years, individual differences such as age, anxiety, motivation and willingness to communicate (WTC) have received ample attention in second language (L2) research (Pawlak, 2012). Traditionally, while acknowledging the role of context on variations in motivation and WTC among learners, research on the two constructs has focused on the 176

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enduring traits of learners. More recently, however, research targeting the two constructs has seen a dynamic shift that acknowledges motivation and WTC as likely to fluctuate over time depending on complex combinations of individual, social and contextual factors (Pawlak et al., 2016; Poupore, 2013; Waninge et  al., 2014; Yashima et  al., 2016). This shift has resulted in a growing set of empirical investigations taking a dynamic and situated perspective focusing on each of the two constructs on its own. Although MacIntyre and Serroul (2015) have looked at both motivation and WTC and the dynamic interrelationship between these two constructs in laboratory conditions, to the best of our knowledge no study to date has examined this relationship in an authentic classroom context. The current study aims to fill this gap as it takes a closer look at fluctuations in L2 motivation and WTC and their interrelationship in a group of eight students over the course of two intact L2 lessons. In the following, we first review earlier theoretical and empirical work into L2 motivation and WTC with specific emphasis on the dynamic shift. We then provide details of our innovative study where we triangulate data from different sources (stimulated recall, observations, interviews) drawing on a combination of Waninge et al.’s (2014) Motometer, Pawlak’s (2012) motivation grid and MacIntyre and Legatto’s (2011) idiodynamic method. The discussion highlights the multifaceted and dynamic nature of motivation and WTC. Both were found to show alternating periods of change and stability across the two lessons. We conclude by suggesting that teachers could use more classroom tasks that require extensive and constant involvement (e.g. discussion activities in small groups) as these seem to be highly beneficial to both WTC and motivation. L2 Motivation and WTC: A Shift in Perspective

Research into L2 motivation dates back to the mid-1900s when the socio-psychological work of Gardner and Lambert (1959) investigated linear cause–effect relationships between motivation and learning, drawing on surveys with large samples of L2 learners. Since then, Gardner (2010) has conducted further research into this area, and over the years, L2 motivation research has gradually shifted its focus from a macro-perspective to a more situated and classroom-based perspective; this has allowed fluctuations in motivation over time to be identified and the role of contextual factors on students’ motivational dispositions to be investigated (Dörnyei, 2000). Motivation was not only seen as a stable trait of a learner but also as a ‘a fluid play […] that emerges from the process of interaction of many agents […] in the ever-changing complex world of the learner’ (Ellis & Larsen-Freeman, 2006: 563). In the present study, we adopt this perspective on motivation as a dynamic and multifaceted construct which is ‘responsible for the choice of a

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particular action, the effort expended on it and the persistence with it’ (Dörnyei, 2001: 7). Investigations into WTC have undergone a similar shift, from viewing it as a stable trait to also regarding the construct as a context-embedded dynamic state in which L2 learners find themselves (McCroskey & Richmond, 1991). WTC is defined as ‘a readiness to enter into discourse at a particular time with a specific person or persons, using a L2’ (MacIntyre et  al., 1998: 547). MacIntyre et  al. (1998) conceptualise L2 WTC as a pyramid that integrates socio-cognitive and context-situated variables. At the top of the pyramid is the communicative behaviour of L2 use. The latter rests on two situated antecedents: the desire to communicate with a specific person and state self-confidence. These are influenced by the bottom layers of motivational propensities, of the affective-cognitive context and of the social and individual context. For a long time, L2 research has aimed to identify individual variables that have a more enduring influence on both state and trait WTC, and more recent work taps into dynamic changes in situational WTC (e.g. Kang, 2005; MacIntyre & Legatto, 2011; Pawlak & Mystkowska-Wiertelak, 2015). The findings of these studies support MacIntyre et al.’s (1998) pyramid model and they provide evidence that WTC may be best regarded as a dynamic construct. Before reviewing these empirical studies, the next section introduces Complex Dynamic Systems Theory (CDST) which provides the conceptual framework of the present study. CDST Approaches to Individual Differences

The basic tenet of CDST is that any construct – and thus also individual differences – is part of a complex system of interacting variables characterised by non-linear relationships and alternated periods of change and stability over time (de Bot et al., 2007; Larsen-Freeman & Cameron, 2008). Periods of change within a dynamic system are not due to the effect of a single variable, but rather to the complex interaction between different factors, each also subject to dynamic variability, at a specific point in time. Furthermore, as highlighted by Verspoor (2015), periods of change are dependent on initial conditions, namely the conditions of the system when one starts measuring. Initial conditions appear crucial when it comes to investigating constructs such as motivation or WTC as they can determine how a learner reacts, for instance, to negative experiences. As highlighted by Verspoor (2015), a very motivated learner in the initial stages of L2 learning might be more severely affected by a negative event, compared to a learner who has been highly motivated for years. Within CDST, change occurs not only on a temporal axis but also within the relationships established by the different components of the system and in their interaction with the context. For instance, when a learner experiences a motivation drop, this is likely to affect other related constructs

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such as WTC, anxiety and perceived competence; four constructs have been identified by MacIntyre and Serroul (2015) as the ‘four horsemen’ of avoidance motivation. Therefore, these components should not be investigated separately because it is their reciprocal interaction and interconnectedness that accounts for the system’s complexity and dynamic variability. A crucial factor contributing to variability in dynamic systems is context. Ushioda (2015) highlights that the specific context plays a major role within a dynamic system since it not only shapes learners’ affective and cognitive subsystems but it is also shaped by learners. Consequently, the context, the learners and their own subsystems are components of a larger dynamic system whereby the factors influence each other in a bi-directional relationship and through a process of co-adaptation. The investigation of dynamic changes in motivation and WTC as well as in language acquisition more generally is highly dependent on the timescale used to observe this phenomenon (de Bot, 2015). The adoption of larger or smaller timescales as part of the research methodology can lead to different results and interpretations of the dynamic nature of motivation or WTC. Based on the timescale chosen, the degree to which motivation and WTC fluctuate over time varies significantly (de Bot, 2015). Given that the present study focuses on dynamic changes in motivation and WTC every 2.5 minutes within two L2 lessons, the following section reviews earlier empirical work that adopted a CDST perspective using similarly short timescales. Researching Motivation and WTC: A Dynamic Perspective

In recent years, an increasing number of empirical studies have investigated dynamic variability in L2 motivation. So far, a few studies have focused on changes in motivation across longer periods of time, such as the academic year (Nitta & Asano, 2010), a 10-month period (Kim, 2009), a 4-week period (Pawlak, 2012) or a 2-month period (Lasagabaster, 2017). Only a handful of studies have looked at changes in motivation on short timescales; these aimed at investigating fluctuations every 5 minutes during the lesson (Pawlak, 2012; Pawlak et  al., 2014; Waninge et  al., 2014), pre-, during and post-task (Poupore, 2013) and on a moment-by-moment basis during task completion (MacIntyre & Serroul, 2015). Table 8.1 summarises the earlier work. The first three studies made use of tailor-made charts where learners indicated their level of motivation every 5 minutes during the lesson; these data were complemented by interviews where learners provided a rationale for outstanding variations in their motivation. Results revealed that changes in motivation at the lesson level were dependent upon combinations of situation-specific factors such as topic, task type, task duration and change of activity. Poupore (2013) used questionnaires to study changes in motivation before, during and after task completion,

Polish secondary school learners of English.

Dutch secondary school learners of Spanish and German.

Korean learners of English in a conversation course as part of a teaching English to speakers of other languages (TESOL) certificate programme.

Pawlak et al. (2014)

Waninge et al. (2014)

Poupore (2013)

MacIntyre and Serroul University learners of French (2015) as L2.

Polish secondary school learners of English.

Participants

Pawlak (2012)

Author(s)

Pre-task, main task and post-task.

5-minute intervals during the lesson.

5-minute intervals during the lesson.

5-minute intervals during the lesson.

Timescale

Idiodynamic method: Moment-by(1) Communicative task is moment during recorded for immediate playback. task completion (2) Participant views recording and rates WTC on a moment-bymoment timescale. (3) A graph of the motivation rating is produced and reasons for fluctuations are discussed in an interview.

Motivation questionnaires administered pre-, during and post-task completion.

Motometer (motivation grid to be filled every 5 minutes during the lesson); classroom observations.

Motivational questionnaire, classroom observations, interviews, lesson evaluation questionnaires, motivation grid to be filled every 5 minutes during the lesson.

Motivational questionnaire, classroom observations, interviews, lesson evaluation questionnaires, motivation grid to be filled every 5 minutes during the lesson.

Research methods

Table 8.1  Empirical research into changes in L2 motivation over short timescales

Variability in approach/avoidance motivation was highly dependent on task demands. Approach motivation increased when communication was continuous and learners felt self-competent. Avoidance motivation arose due to language anxiety or feeling of low self-competence.

Stabilising factors for motivation: Task attraction, enjoyment, relevancy, interest; intended/reported effort. Decreasing factors for motivation: success expectancy; high perceived difficulty; low group dynamics.

Alternation of periods of high variability and attractor states due to the influence of various contextual factors (e.g. change of task, task interest, events prior to the lesson).

Factors creating dynamic fluctuations in motivation: task topic, type, duration; change of activity; opportunities for involvement in group work; perceived usefulness of the activity for future assessments.

Students’ motivation showed limited variability within the single lesson.

Findings

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and showed that different personal and contextual variables accounted for periods of relative stability or variability in motivation. Finally, using the idiodynamic method originally developed to investigate fluctuations in WTC (see below), MacIntyre and Serroul (2015) found the lexical and grammatical demands of a task and a learner’s perceived competence to be the main factors accounting for variability in approach/avoidance motivation. Recent work on L2 WTC has also adopted a dynamic perspective, investigating fluctuations in WTC over one (Cao & Philp, 2006), three (de Saint-Léger & Storch, 2009), five (Cao, 2011, 2014) or seven (Peng, 2012) months or a semester (Yashima et al., 2016). Given the scope of the present study, we review in more detail earlier work on WTC, holding the microscopic lens on changes over the course of a single lesson, task or conversation. A growing body of recent work adopting a dynamic perspective looked at fluctuations in L2 WTC. The studies summarised in Table 8.2 explored changes in WTC every 30 seconds or every 5 minutes. MacIntyre and Legatto (2011) developed the idiodynamic method for their lab-based study of six participants who were asked to complete eight oral communicative tasks. After task completion, the participants watched a videoreplay of their performances and rated their moment-to-moment WTC during task performance. Finally, they were interviewed about their ratings of WTC. The key factors identified in this study that affected WTC were task difficulty, task familiarity and ease of task-related vocabulary retrieval. Mulvaney’s (2015) study, which also used the idiodynamic method, highlighted complex interconnections between different factors affecting WTC given that next to task factors (e.g. communicative ease) interpersonal relationships and self-confidence had an influence on participant ratings. Both Kang (2005) and Pawlak and Mystkowska-Wiertelak (2015) investigated changes in WTC every 30 seconds. While Kang’s (2005) participants attributed fluctuations in WTC to excitement, responsibility and security, which were in turn co-constructed by interactive situational variables, Pawlak and Mystkowska-Wiertelak (2015) found that the degree of direct involvement in the task was key to changes in WTC. Most recently, Mystkowska-Wiertelak (and colleagues) attempted to capture dynamic fluctuations in WTC within the language classroom every 5 minutes. Findings revealed that change of task during the lesson and topic (Pawlak et al., 2016) as well as class-arrangement modes, interlocutor, topic, task features and stage of the class (MystkowskaWiertelak, 2016; Mystkowska-Wiertelak & Pawlak, 2017) all influenced the variability of WTC. This brief review of earlier work shows that both L2 motivation and WTC can be viewed as complex constructs that are subject to variability over time. Earlier work also revealed that the specific classroom context

Korean learners of English at university level

Learners of English at a Polish university

Learners of English at a Polish university

Learners of English at a Polish university

Kang (2005)

Pawlak and Mystkowska-Wiertelak (2015)

Pawlak et al. (2016)

Mystkowska-Wiertelak and Pawlak (2017)

Moment by moment during an oral task.

Moment by moment during an oral task.

Timescale

Factors affecting fluctuations in WTC: complex relationships between different situation-specific factors. Increase: task/topic interest; decrease: communicative difficulty, uncertainty.

Key factors affecting WTC: task difficulty, familiarity; ease of taskrelated vocabulary retrieval.

Findings

WTC grid; lesson plans; questionnaire.

5-minute intervals over the course of the language lesson.

Variations due to a combination of factors: topic of discussion, preference for small-group interaction, interlocutor involvement in the task (focus on three speaking tasks).

Large contextual and individual variation within and across groups; consistent patterns: increase in WTC at beginning of each new task, when discussing interesting/familiar topics, when interacting in smaller groups.

Every 30 seconds over the course Large individual variations in of a communicative task. dynamic WTC due to topic, planning time, interlocutor familiarity, selfcompetence and other individual variables.

Classroom observations, 5-minute intervals over the dynamic self-reports; stimulated course of the language lesson recall interviews.

Participants rated WTC in real-time from –10 to +10 on a tailor-made grid in response to a buzzer, then explained fluctuations in these ratings in a follow-up interview.

Interviews, video-taped Every 30 seconds over a series of Three key psychological variables: conversations, stimulated recall. conversations. excitement, responsibility and security.

Idiodynamic method

Thai university students of English

Mulvaney (2015)

Research methods

Canadian learners of French Idiodynamic method at university level

Participants

MacIntyre and Legatto (2011)

Author(s)

Table 8.2  Empirical research into changes in L2 WTC over short timescales

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with its complex combinations of individual, social and contextual variables impacted on the two constructs. Some of these factors also mediated the relationship between motivation and WTC, as we highlight in the following section. The Relationship between Motivation and WTC

According to MacIntyre et  al. (1998: 553) ‘the motivation for language learning may take the form of WTC, but not necessarily so’. That is, a highly motivated learner does not necessarily present a high degree of WTC, because intensive silent study may also be a sign of high motivation. As mentioned above, MacIntyre et  al.’s (1998) pyramid model sees motivational propensities as a stable trait that creates the conditions for L2 communication. Later, MacIntyre (2007: 567) acknowledged that WTC ‘integrates motivational processes with communication competencies and perceived self-confidence’. In conformity with CDST, this perspective sees motivation as a series of processes that influence L2 communication at a particular moment in time in combination with other factors (MacIntyre, 2007). Among the earliest studies examining the relationship between motivation and WTC, MacIntyre and Charos (1996) administered a questionnaire to L2 learners of French, tapping into self-reported measures of the Big-Five personality traits (i.e. extraversion, agreeableness, conscientiousness, emotional stability and intellect; Goldberg, 1992) as well as WTC, motivation and other constructs. The results revealed a non-significant relationship between WTC and motivation. Yet, a replication of this study with Japanese English as a foreign language (EFL) students using structural equation modelling (SEM) showed a significant link between WTC and motivation (Hashimoto, 2002). Similar studies in Japan (Yashima, 2002; Yashima et al., 2004), Turkey (Cetinkaya, 2005) and Iran (Ghonsooly et  al., 2012) did not yield a direct link between WTC and motivation; yet, motivation seemed to affect self-confidence in L2 communication, which in turn influenced WTC. In Yashima’s (2009) study, self-determined forms of extrinsic motivation strongly correlated with WTC and other factors such as international posture, frequency of communication and learners’ Ideal L2 Self. Similarly, data from MacIntyre et al. (2002, 2003) showed that high school pupils in a French immersion programme as well as Anglophone university students displaying high motivation were also more willing to communicate, presented higher perceived competence, communicated more frequently in French and had lower communication anxiety. Also in Peng’s (2007) data, integrative motivation was the strongest predictor of WTC. In contrast, the WTC model by Mystkowska-Wiertelak and Pawlak (2017) based on a two-round factor analysis excluded motivation in the form of Ideal Self and integrativeness.

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Table 8.3  Empirical research on the relationship between motivation and WTC at specific moments in time Author(s)

Participants

Research methods

Findings

Dörnyei and Kormos (2000)

Hungarian learners Self-report questionnaire; Situation-specific motivational of English at oral argumentative task. variables significantly affect secondary school. engagement and positive attitudes towards task; linguistic self-confidence, WTC, need for achievement and social status are positive determinants of student behaviour.

Dörnyei (2002)

Hungarian learners Self-report questionnaire; Interlocutor’s motivation of English at oral argumentative task. affects output. WTC not secondary school. affected by task partner.

Eddy-U (2015)

Learners of English Semi-structured focus at a university and group interviews. hospitality training institute in Macau.

Key factor influencing motivation: WTC; motivation is co-constructed by participants.

Peng (2014)

Learners of English Questionnaire on at a Chinese WTC, learner beliefs, university. communication confidence and classroom environment; journals; semi-structured interviews.

Relationship motivation and WTC is mediated by communication confidence. Changes in WTC affected by classroom environment.

Finally, a few studies have looked at the interplay between motivation and WTC at a particular moment in time (see Table 8.3 for a summary). Dörnyei and Kormos (2000) investigated motivation, looking at different affective and social variables (e.g. group cohesiveness and intermember relations) and their effect on task engagement (i.e. number of words and turns produced) during argumentative tasks. The results confirmed that situation-specific motivational variables had a significant effect on engagement; furthermore, positive attitudes towards the task, linguistic self-confidence, WTC, need for achievement and social status appeared as positive determinants of student behaviour. The follow-up analysis by Dörnyei (2002) found a relationship between the interlocutor’s output and motivation but not between the interlocutor’s output and WTC. Eddy-U’s (2015) data confirmed that social factors have a strong impact on motivation, as it seemed to mutually increase or decrease within the same group of learners. In addition, WTC was identified as one of the key factors influencing task motivation. Finally, taking a dynamic perspective on WTC, Peng (2014) targeted the relationship between individual and contextual factors within different classroom settings. Data revealed that motivation influenced WTC only indirectly mediated by a learner’s communication confidence. In sum, these studies showed indirect connections between the two constructs. That is, motivation appears to influence communication behaviour, including social relations and self-confidence, which in turn plays a role in shaping WTC.

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Purpose of the Study and Research Questions

Although a number of studies have investigated the dynamic fluctuations in both motivation and WTC, none has specifically examined the interrelationship between the two constructs from a dynamic perspective in the authentic classroom context and during intact lessons. Through our situated perspective on the investigation of the two constructs, we attempt to shed light on how the learner and the classroom context change and shape one another as part of the same complex dynamic system (see Ushioda, 2015), and on how this process contributes to shape, in turn, motivation, WTC and their interrelationship. Furthermore, through collecting dense data about each individual learner and thus taking a person-centred approach (see Peng et al., this volume), we attempt to determine how different factors can impact the two constructs and their interrelationship in different learners, depending on the quality of each learner’s interaction with the context. Previous studies on the relationship between the two constructs, with the exception of MacIntyre and Serroul (2015), have examined this link at a specific moment in time, focusing on linear cause–effect relationships. Our study uses a micro-lens to identify ‘the convergence of psychological processes underlying communication’ (MacIntyre, 2007: 564) every 2.5 minutes during two lessons, in order to uncover the multitude of interrelated factors influencing motivation and WTC and contributing to changes in their relationship over time. While acknowledging the contribution of earlier classroom-based studies where learners tracked their motivation in real-time during the lesson (e.g. Pawlak, 2012; Poupore, 2013; Waninge et al., 2014), we also aim to address a methodological shortcoming. That is, the fact that students had to indicate motivation or WTC during task performance or during a class is likely to have required cognitive effort. Accordingly, it might well be that the dual task of focusing on the class/task and on rating motivation/WTC simultaneously influenced those tasks. This is particularly pertinent from a CDST perspective, where one small change in one part of the system is thought to have repercussions elsewhere in the system (Larsen-Freeman & Cameron, 2008; Larsen-Freeman, this volume). In other words, it is likely that the regular interruptions to indicate motivation or WTC influenced the dynamic relationships between different factors and affected task performance. In order to overcome these methodological issues, the present study combines the strengths of this earlier work by employing a combination of classroom observations, stimulated recall procedures based on videorecordings of the lesson and cued retrospective interviews, pursuing the following research questions: (1) (a) To what extent does motivation fluctuate over the course of two L2 lessons?

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(b) What do students identify as sustaining or impeding motivation during two L2 lessons? (2) (a) To what extent does WTC fluctuate over the course of two L2 lessons? (b) What do students identify as sustaining or impeding their WTC during two L2 lessons? (3) What characterises the interrelationship of motivation and WTC throughout two L2 lessons? Method Participants

Eight advanced learners of L2 French from two first-year classes at a British university voluntarily participated in the study (see Table 8.4 for their characteristics). The classes observed were compulsory as part of the students’ French language degree. We purposely decided to work with a small sample of participants to allow for a more in-depth study of motivation and WTC. Table 8.4  Participants’ characteristics Activity

Duration

Task 1

In groups, two to three students discussed two assigned topics previously addressed during the academic year. They should focus on the most important concepts and key vocabulary and come up with ‘questions de conversation’ (conversation questions), one for each topic, to be discussed in the following activities.

20 minutes

Task 2

Each group presented the key vocabulary and concepts while the teacher would write these on the board and would provide clarifications where necessary.

15–20 minutes

Task 3

In groups covering each topic, students presented their ‘question de conversation’ and led the discussion.

10 minutes

The classroom context

The same teacher, a native speaker of French with more than 10 years of teaching experience in higher education, taught two lessons according to the same structure comprising three communicative tasks (see Table 8.5). Given that it was almost the end of term, the lessons aimed to revise the different topics addressed over the academic year. Instruments and procedures Classroom observations and video-audio recording

The two lessons of two different first-year advanced French classes were audio-/video-recorded. Detailed handwritten notes of classroom activities and students’ and teachers’ behaviour and interactions in the

Dynamic Changes in Motivation  187

Table 8.5  Lesson plan Participant

Gender

Age

Years studying French

Degree programme

Group

Focus of investigation

Lucy

Female

19

 5

French studies and history

1

Motivation

Kate

Female

19

 8

French studies and history

1

Motivation

Max

Male

19

 7

French studies and maths

2

Motivation

Hailey

Female

19

11

French and Spanish studies

2

Motivation

Bryce

Male

19

 7

French studies and linguistics

1

WTC

James

Male

19

 7

International business management

1

WTC

Sylvia

Female

20

13

Linguistics, French and English language

2

WTC

Claire

Female

19

 8

French studies and history

2

WTC

classroom were taken by the first and second author. Before the observations took place, the students and teachers in each class signed for informed consent to be included in the study. Stimulated charting of motivation/WTC

Directly following the class, dynamic fluctuations in learners’ motivation and WTC over the course of each lesson were tracked using a chart developed on the basis of Waninge et al.’s (2014) Motometer and Pawlak’s (2012) motivation grid. The x-axis of the chart constituted the time (minute 2.5–45 of the lesson) in 2.5 intervals, while the y-axis showed a scale from 0 (low) to 10 (high) to rate levels of motivation/WTC. The stimulated recall procedure based on the video-replay of the lesson was inspired by the idiodynamic method (MacIntyre & Legatto, 2011) and adapted to suit the current investigation. The video-replay of the lesson was broadcast on a large screen to each group of participants. They were prompted to rate their level of motivation or WTC on the chart every 2.5 minutes in response to a buzzer. Four students were asked to track their level of motivation, explained to them as their willingness to put effort into learning at that specific moment during the lesson. The operationalisation of the construct of motivation draws on the construct of ‘intended effort’, defined by Papi (2010: 470) as ‘the amount of effort learners intend to put into learning’. The other four students charted their WTC, explained as their willingness to initiate communication at that specific point during the lesson

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45 min lesson

45 min charting

1. Classroom observation & audio-/video-recording

2. Motivation/WTC chart during video replay

15 min interviews

3. Individual semi-structured cued interviews

Figure 8.1  Study design

(MacIntyre et al., 1998). Separating the two constructs allowed not only for in-depth investigations into each of them, but also to determine whether students who were interviewed about their motivation would mention changes in their WTC and vice versa. This procedure secured an uncontrived investigation of the relationship between the two constructs. Interviews

Following the charting procedure, students took part in individual semi-structured cued interviews where they were asked to provide a rationale for the charted changes in motivation and WTC. Figure 8.1 summarises the design of the study. Coding and analysis

A logbook was created combining the classroom observation notes and data from the audio-/video-recording of each lesson. The numeric data from students’ motivation and WTC charts for each lesson were entered into Excel and transformed into line graphs, in order to obtain a visual representation of students’ motivation trajectory during each lesson. Interview data were analysed thematically, first, because thematic analysis is not grounded in a specific epistemological perspective and it can be employed with a variety of theoretical frameworks (Braun & Clarke, 2006). Therefore, a thematic analysis can be adopted to investigate not only how individuals make sense of their experiences, but also how the broader social context affects their interpretation of these experiences (Braun & Clarke, 2006: 5). This is of great relevance to the present study, where students’ personal and social experiences are examined in light of the specific classroom contexts where they occur. Second, thematic analysis allows for both an inductive bottom-up and a deductive top-down coding approach (Braun & Clarke, 2006). In this study, a combination of both was adopted: the data-driven approach was employed to investigate factors emerging from students’ accounts which were not bound to a pre-existing coding frame, whereas the theory-driven approach was used to label specific phenomena previously outlined in the CDST literature. The analysis procedures were based on Braun and Clarke’s (2006) six steps of thematic analysis adapted for the present

Dynamic Changes in Motivation  189

study. The first step of analysis began with the verbatim transcription of all interviews with the aid of a research assistant. Once transcribed, each interview was entered into the computer software Atlas.ti 8 and read multiple times. Both literature-based and emergent codes were then generated to label pieces of the raw data in a systematic way across the data set. Codes were then grouped together to create overarching themes (e.g. fluctuations in motivation at the lesson level) and subthemes (e.g. self-confidence and sense of efficacy). All data extracts for each theme were then re-read multiple times and examined in close detail. The first and second author carried out multiple rounds of coding on the whole data set and discrepancies were discussed until agreement. In the final interpretive step based on the CDST literature, the interconnections between themes were established and findings across the different data sources were triangulated. Findings and Discussion

This section, in which we examine and discuss the findings of this study, is divided into three subsections. We examine fluctuations in (1) motivation and (2) WTC throughout the lesson, where each subsection provides the data from the motivation charts and interviews, followed by an examination of the main themes in relation to changes in motivation and WTC at the lesson level. We then (3) focus on the interconnections between motivation and WTC. Fluctuations in motivation at the lesson level

Addressing the first research question, this section examines fluctuations in motivation over the course of the L2 lesson. Figures 8.2 and 8.3 show the level of students’ motivation measured at 2.5-minute intervals and plotted on the chart together with salient extracts from the interviews with reference to specific time points during the lesson. Next, we examine the four main factors that, based on the thematic analysis, appeared crucial to changes in motivation during the lesson, namely (a) self-confidence and sense of efficacy, (b) active involvement and participation in the learning activities, (c) topic of interest and relatedness and (d) group dynamics and classroom atmosphere. Self-confidence and sense of efficacy

Based on learners’ self-reports, the continuous judgement of their own capabilities to achieve a given task had a substantial impact on fluctuations in motivation, in conjunction with other factors such as topic familiarity, group dynamics and positive feedback. Lucy’s confidence appeared to be negatively influenced by topic unfamiliarity (min. 7.5) and negative group dynamics (min. 42.5), backing up findings from Poupore (2013)

0

5

2,5 L: Here we were just given the task so I was 'right, we can do this'. K: This is when T was talking about what we were going to do so obviously your brain starts taking away thinking about things and then I gradually became more motivated [...] The people who are there are really really nice then it's fine.

2.5

10

7,5 L: Then I realised I really didn't knowwhat to talk about. So I wasn't as motivated.- We were given in our group such hard topics to think of.- I felt a bit frustrated . K: He wants to make you learn [...] so that you don't feel that pressure and therefore you want to learn it more and you want to engage with class discusssion and talk and say whatever, it doesn't really matter, it can be wrong.

7.5

Figure 8.2  Motivation chart – Class F1

0 L: This was right at the beginning so I was a bit like 'back again’. K: So that was when we started the lesson, when you're always a little bit reluctant.

0

2

4

6

8

10

15

10 L: We worked together well, and brainstormed ideas of what the topic could have meant.- I was friends with the two girls so it was much easier to talk French with them and work. K: Once people started throwing ideas back and forth then you think things and your brain starts going and then it starts taking away then obviously you want to talk more.

12.5

20

15 K: I think it was this point when T said it was going really well so obviously you get positive feedback you then realise you want to try harder and do even better. So that was good [...] we equally contribute, so one person thinks of an idea and then it sorts of naturally happens [...] you force yourself to keep on it, keep responding or counteract in their arguments.

17.5

25

17,5 K: And then that was there was a little bit of a low in the topic we were discussing and we sort of finished what we were doing [...] it's much easier to talk ingroups of three for instance you feel more confident.

22.5

30

22,5 L: Definitely (I felt more motivated) when we had to present to the class because I knew some of the words were quite good so that definitely pushed us. K: When you have to get back to the class as a whole you're always a little bit reluctant so you don't feel quite as motivated as when you're with your friends talking.

27.5

Class F1-Lucy and Kate

35

40

37,5 L: I guess it makes it more exciting (to change the task) cause we spend so long doing that beginning task so it was something new. But then I got scared. K:When we swapped and we began to discuss other ideas and questions so yes, I was more motivated by that point so also when I was doing well I was feeling more motivated.

37.5

Kate

25 L: This is when were listening to everyone else so I was taking notes but obviously I wasn't actually taking part. K: There was a little bit of a dip about halfway once we finished the discussion and you can't really think of anything else and you sort of think that's enough, can't really do anything so you feel less motivated at that point.

32.5

Lucy

45 42,5 L: One of the boys in our class is kind of fluent in French […] so I just really didn't want to speak in front of him, cause I was embarrassed. So i was less motivated. K: We were discussing the student revolution in May 1968 and I quite enjoyed that topic and knew about it so I really really enjoyed the […] so I wanted to try really hard at that point.

42.5

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0

5

2,5 H: The part of the class I enjoyed the most was probably when me and Lizzie were working together on the vocabulary [...] working with someone else is always nice cause I have new ideas. M: The groupwork was good. Cause then you have to do stuff cause if you are in a pair you can't just sit there and do nothing

2.5

10

5 M: I just liked it when we had to kind of speak about our topic, but if it's like a good topic. So I had the environment which was quite good cause that was interesting so... - I prefer speaking in little groups so my motivation is higher then to speak.

7.5

Figure 8.3  Motivation chart – Class F2

0 M: So the first one I came in quite motivated.. H: And at the start I was the least motivated just because you just sat there in the class and not much is happening.

0

1

2

3

4

5

6

7

8

9

10

12.5

17.5

7,5 H: Then when the task got going I was pretty consistently motivated. It never got below 6. I like the oral classes so that's quite a true reflection of how I'm normally motivated [...] the more at ease you get with your classmates and with the tutor your motivation to engage in the class goes up because you feel more selfassured.

15

22.5

10 M: (My motivation) it kind of fluctuates between ehm if I get a bit bored of the tasks then my motivation goes a bit (down). H: My motivation sort of spiked when I was talking directly to Romain because there was just more engagement with the language then.

20

27.5

12,5 M: And so that's why the drop went down a bit I think and then went back up like whenever he came over so that I could then try to run my ideas by him sort I think - So when he comes over then I want to say something so that he can like check what I'm saying is right cause that's like the whole point and then when he goes it's like of, yeah it drops like a

25

Class F2–Max and Hailey

32.5

22,5 M: I don't engage as much with the whole classroom but I definitely do more now than I did. H: It depends who you are with and who you are confortable with in terms of the tutor and your classmates for how much you're engaged. And also your confidence on the topic.

30

37.5

42,5 M: And in the pairs it felt really good cause we all know each other now so it's like it's easy to talk to people and there's lots to say. H: I think working in pairs is sometimes easier than working in three because the third person often doesn't say as much.

35

42.5

45

Hailey

45 M: When I was listening to other people I still was motivated but like not as much cause I don't have to be thinking I just have to be kind of take it in . H: f we just looked at the vocabulary for the whole class I probably would have got quite bored towards the end.

40

Max

47,5 M: And then it dropped off towards the end cause I knew it was just the end of the lesson so I was just like, I don't know. H: Then towards the end of the class it gets a bit flatter just because after 50 minutes of doing quite similar tasks your interest dips a bit.

47.5

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who also found both factors contributed to drops in motivation during task performance. Kate gained both confidence and motivation once she and her peers started to get actively involved in the activity (min. 10) and when provided with positive feedback from the teacher (min. 15). Both Kate and Lucy mentioned higher motivation when performing well on a given task (min. 37.5 and 22.5). The teacher’s feedback was also mentioned by Max; he checked his ideas with his tutor to determine whether he was on the right track (min. 12.5). Similarly, Hailey mentioned the importance of being at ease with classmates and the teacher and not being afraid of making mistakes in order to be motivated (min. 10). These results corroborate previous findings from MacIntyre and Serroul (2015), who found perceived competence as playing an important role in relation to changes in approach/avoidance motivation at the task level. Active involvement and participation in the learning activities

The degree of involvement and participation in a task also appeared to play a key role in fluctuations in motivation. This variable appeared sensitive to the type of tasks assigned, the tutor and the degree of peers’ involvement in the task. The present study found that a student’s active and direct participation in the classroom activities was an essential condition for intense motivation. When students had to passively listen to the teacher or to other students’ presentations, their motivation tended to decrease, whereas when they were invested in activities requiring continuous participation, such as small-group discussion activities, their motivation was high and sustained, consistent with Pawlak et al. (2014), who identified the opportunities for involvement in group work as a crucial factor contributing to dynamic fluctuations in motivation at the lesson level. Lucy, for instance, reported being less motivated when having to listen to her classmates’ contributions without actively participating in the task (min. 25). Both Kate (min. 42.5) and Max (min. 5) mentioned being more motivated when engaged in activities requiring continuous participation and providing opportunities for interaction, such as small-group activities. Hailey emphasised the role of the teacher for her engagement, reporting being more motivated when actively involved in conversation with her tutor, a sentiment echoed by Kate (min. 10 and 15). Topic interest and relatedness

All students mentioned a link between the topics dealt with during the discussion activities and their motivation. Lucy reported feeling frustrated and experiencing a drop in her motivation due to not being familiar enough with the topics and the topic-related vocabulary (min. 7.5). Both Kate and Max stated that topics provoking interesting discussions and critical thinking, which they could relate to their own life and

Dynamic Changes in Motivation  193

interests, sparked their motivation and task enjoyment (min. 42.5 and 5). This finding contrasts with Poupore (2013) who identified interest as catalysts for attractor states in the participants’ motivation; indeed, Kate and Max reported that topic interest acted as a trigger for their motivation, rather than a stabilising force. Finally, Hailey referred to being confident with the topic of the task at hand as a key motivating factor (min. 22.5), confirming the link between confidence and topic highlighted in the previous section. Group dynamics and classroom atmosphere

Confirming previous classroom-based research (e.g. Eddy-U, 2015; Poupore, 2016), changes in the social environment led to variability in learners’ motivation at a task and lesson level. Students often mentioned group dynamics and general classroom atmosphere as shaping their motivation, as well as their degree of confidence and involvement in class activities. While Lucy reported a high level of supportiveness and interaction during the first small-group activity (min. 10), the uncomfortable dynamics in the second small-group task led to a motivation drop (min. 42.5), corroborating Poupore (2013) who also found low perceived group dynamics as a negative force influencing motivation. Kate highlighted the supportive and well-balanced group dynamics within both groups, reporting that her peers’ involvement positively affected her participation in the task and motivation (min. 10 and 37.5). Like Max (min. 42.5) and Hailey (min. 22.5), she also mentioned peer familiarity as playing a role in her motivation and confidence (min. 10). Fluctuations in WTC at the lesson level

Looking at fluctuations in WTC over the course of the L2 lesson, Figures 8.4 and 8.5 illustrate the level of WTC measured at 2.5-minute intervals and plotted on the chart, combined with salient extracts from the interviews. The four main factors having the strongest impact on WTC as revealed by the process of the thematic analysis were (a) selfconfidence and sense of comfort, (b) peer involvement and perceived attitude, (c) task types and features and (d) topic familiarity. Self-confidence and sense of comfort

While in the case of motivation, self-confidence was paired with a sense of efficacy and self-assurance about one’s L2 competence, when reporting on their WTC, students referred to confidence as feeling comfortable when speaking. This variable appeared to have played a crucial role in shaping learners’ WTC, corroborating Pawlak and MystkowskaWiertelak (2015) and giving partial support to MacIntyre et al.’s (1998) pyramid model, in which state self-confidence appeared as an immediate

0

2,5 B: Then we went into group discussion which I quite like doing coz I think if you’re working with people you kind of know different things and get to have different ideas from things.

2.5

5

Figure 8.4  WTC chart – Class F1

0 B: I didn’t really know what we were gonna be doing […] it depends exactly what you’re doing as to how into it I wanna kind of get involved. J: generally I think I’m pretty up to communicat ing if it needs to happen or if I just feel like it.

10 9 8 7 6 5 4 3 2 1 0

5 B: then it kind of like dipped I think it’s, at the times where it was stopping our teacher was coming over. J: So, at the beginning since we have to like discuss in groups, I’m more willing to in order to make the group work

7.5

7,5 B: I think we had more to say on the environmen t stuff more because we’ve done more on it, it’s a bit more contempora ry - if you don’t know the people and [...]if they’re not as confident or they’re a bit shyer, then that kind of draws back from how much you can get.

10

15

10 B: I think the family stuff, we did it at the beginning of the year, and again it’s not the most involving of topics. J: Like at the beginning I’m just willing to start the conversation going but I mean if nobody else says anything then it’s just like, alright.

12.5 15 B: We got to the family bits at the end, and then that just wasn’t as exciting so we kind of didn’t have as much to say, erm, still we were trying, but it wasn’t as engaging.

17.5

20 17,5 B: It’s just kind of something different, you get to hear what other people think. J: We started to talk about a topic I was more interested about - I’m pretty confident in French, talking in French so it’s fine with me.

22.5

27.5

22,5 J: I think it was the moment when the teacher was just talking by himself, talking in general, things we shouldn’t actually contribute or there’s nothing to say at that time, so that’s probably why it was low.

25

30 25 B: Then I think it started dipping down round here just cause then it was kind of the same thing like kind of going round and giving like, words basically. J: I’m pretty confident in French, talking in French so it’s fine with me.

Bryce

Class F1–Bryce and James

35

32,5 B: I know it’s good to kind of have contact with different people when you’re learning another language and things but, we just didn’t have a very good dynamic. J: in general the mood it’s not motivating me and at the same time I don’t have motivation

32.5

James

35 B: It wasn’t really a discussion it was more like, well this is what I think this is what I think, ok next. It wasn’t very enthusiastic J: t’s pretty much the same as the beginning, we were starting in a group again, so trying to get that thing going.

37.5

42.5 40 J: But once it just doesn’t go, the motivation also goes down, or the willingness […] it goes down at the times where the class is more quiet, like although someone has said something nobody kind of like either replies or keeps on going.

40

45 B: I think that was just kind of like a relief thing that it’s, you’re comingback to a group setting so again I was quite happy to kind of chat when it’s more like that dynamic cause then you have people talking who are more willing because it’s a larger setting.

45

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0

2,5 S: It was high […] because the first topic me and partner had was, I was interested in […] it was a recent topic and I knew more about it. C: I was sat next to someone who I work with most weeks so I feel quite confident speaking French with her.

2.5

5

7.5

5 S: The other topic was […] something that we didn’t really know as much about...it’s harder to think like, issues on it. C: We just looked at what we’d both done in revision and were pulling words together.

Figure 8.5  WTC chart – Class F2l

0 S: I enjoy the beginning of the lesson like seeing them and saying hi to everyone and it’s an enjoyable lesson, it’s quite relaxed, so I always enjoy it at the beginning. C: When you come in you’re not quite ready yet.

10 9 8 7 6 5 4 3 2 1 0 12.5

7,5 C: We moved onto modern families, which is, cause obviously I study sociology as well, that’s something I know quite a lot about, so I think I was more leading it there, cause it was an area that I am quite well informed on.

10 10 S: Today in the group that we had today, it was a lot easier for everyone to get involved and everyone to feel comfortable getting involved and saying their opinion, and I much prefer it like that it means, it makes me want to get involved more.

15

20

15 S: my willingness is always quite high, if I have something to say I’ll say it, butif I don’t know what to say then I might still be willing but not know how to say it.

17.5 20 S: We had to talk about the working world and about life as students first, and so that’s when it went down because we didn’t have much to say […] we were the first group to present our topic, so when you’re the first group to do something then you’re less confident.

22.5

27.5

25 C: That was when we were feeding back, so I wasn’t really speaking or anything cause it was the other group. S: I think that was the same like, it was the other groups participatin g so there was no need for me to do so.

25

Class F2–Sylvia and Claire

30 S: Then it was higher when it was on the environmen t when we knew, when we’d heard other groups talk and we’d got the general idea of how we were supposed to present the topic, and we knew more about this topic so, that was easier.

30

35

37,5 S: When we’re just working in small groups then, again, it’s like very easy to talk. C: Then there’s just a group […] there’ll be like a list of questions and we discuss them, so everyone gets a chance to speak and everyone like bounces off each other.

32.5

Sylvia 40

40 S: When you’re discussing with other people, you’ve got your own ideas that you’ve gained off the first group but then you’re bouncing off their ideas. C: We were doing that activity for quite a while […] it was like continuous conversation.

37.5

Claire

42,5 S: When I was waiting for the other girl in our group of three to talk, and I think there was a point when we said everything that needed to be said […] I was less willing to communicat e because I’d already discussed it and I was wanting to listen.

42.5

45 S: Right at the end when he’s explaining the homework or something, then I don’t really have a willingness to communicat e cause the lesson finished and you’re kind of done.

45

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antecedent to WTC, together with the desire to communicate with a specific person. In this case, dynamic self-confidence was largely influenced by learners’ relationship with the interlocutors or the audience. Bryce, for instance, was feeling more comfortable when speaking with friends in the first group (min. 2.5), a sentiment echoed by Sylvia and Claire (min. 2.5), showing a strong link between confidence, peer familiarity and WTC. Sylvia mentioned a drop in both her WTC and self-confidence when having to present to the rest of the class, as she was not sure about what was expected of her (min. 20). In spite of generally high self-confidence, James’ WTC dropped due to the uncomfortable dynamics within the group (min. 10). Peer involvement and perceived attitude

Both the degree of involvement and the degree of confidence and friendliness displayed by peers were deemed by learners as contributing to shape WTC fluctuations at the lesson level, in addition to learners’ own willingness to actively partake in the classroom activities. Bryce and Sylvia mentioned that their WTC was higher when their classmates were confident and appeared willing to interact (min. 7.5 and 10). Similarly, James experienced a drop in his WTC during the small-group activities due to the perceived lack of interaction from his peers (min. 40). This finding supports Mystkowska-Wiertelak and Pawlak (2017), who also identified the degree of the interlocutor’s involvement in the task as a critical variable affecting fluctuations in WTC in their classroom-based research. Similarly, our findings are consistent with Yashima et al. (2016), who report that the group-level affective state, ambience and other students’ reactions had a large impact on WTC. Task types and features

The type of task carried out in class added to fluctuations in WTC. All students reported a preference for small-group tasks as opposed to whole-class activities given that the former required their constant and direct involvement, which made them more willing to communicate and share ideas. Consistent with our results, Pawlak et  al. (2016) and Mystkowska-Wiertelak and Pawlak (2017) participants also revealed a predilection for small-group interaction during the L2 lesson. Bryce mentioned that small-group tasks provided opportunities to chat with different peers and get new ideas from them (min. 2.5), while James’ higher WTC in this context was triggered by his aim to make the group work (min. 5). His lower WTC appeared during teacher-fronted time as he did not have to actively contribute to the activity (min. 22.5). Sylvia and Claire point to ease and enjoyment as a factor supporting WTC during small-group tasks (min. 37.5).

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Topic familiarity

All four students mentioned that familiarity with the topic affected their WTC. Bryce underlined the importance of having opinions about a given topic and being informed about it (min. 15), a feeling echoed by Sylvia (min. 2.5). Similarly, both James and Sylvia reported that their levels of WTC were dependent upon variations in the topics under discussion (min. 17.5 and 5). Claire also cited topic familiarity as causing her WTC to fluctuate during the different activities (min. 7.5). This finding corroborates MacIntyre et al. (1998) who see topic familiarity as key to encouraging language use, while a lack of content knowledge or familiarity inhibits communication. These results tie in with earlier work that identified task topic as a vital factor influencing fluctuations in WTC (Mystkowska-Wiertelak, 2016; Mystkowska-Wiertelak & Pawlak, 2017; Pawlak et al., 2016). In sum, the four students reported substantial fluctuations in their motivation and WTC throughout the lesson, interspersed with periods of relative stability. For motivation, students named self-confidence, direct involvement in the task, topic interest and relatedness, and group dynamics as the main factors accounting for these changes. Correspondingly, data triangulation on WTC revealed that the most frequently cited variables were self-confidence, peer involvement and attitude, the intrinsic nature of the task and topic familiarity. Importantly, for both motivation and WTC these factors did not act in isolation but were interconnected and mutually interdependent as the findings in the next section reveal. The interrelationship between motivation and WTC

The students’ self-reports do not allow to establish causal relationships nor direct links between motivation and WTC. Nonetheless, it was possible to identify three macro-factors which appeared to provide the conditions for motivation and WTC to flourish. Furthermore, these factors mediated the interrelationship between the two constructs when combined with other individual, social and academic variables at specific points in time during the lesson. The mediating role of confidence

Based on students’ accounts, self-confidence played a crucial role with regard to fluctuations in motivation and WTC at the lesson level, partly consistent with MacIntyre et  al.’s (1998) pyramid model. While earlier work revealed how motivation affected WTC through self-confidence (e.g. Yashima, 2002), data from the current study suggest that self-confidence appeared as a prerequisite for similar levels of both motivation and WTC. Specifically, self-confidence appeared highly dynamic and responsive to learners’ perceptions of their own competence in relation to the

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specific communicative event at hand; as highlighted by MacIntyre and Ayers-Glassey (this volume), ongoing competence appraisals are indeed the main influence on dynamic self-confidence. In Lucy’s case, it seemed that motivation and WTC were indirectly connected and mediated by the interplay of self-confidence and group dynamics. She was highly motivated to present back to the class when confident about her answers (min. 22.5). In contrast, both her motivation and WTC dropped during the second group activity due to her perceived lack of proficiency in relation to another group member who was a near-native speaker of French and actively contributed to the discussion. She reported feeling embarrassed and not confident to speak in front of him, which led to a substantial drop in her motivation during the task at hand (min. 42.5). Interestingly, Lucy’s profile appears very much in line with one of the participants of Yashima et  al. (2016), who also experienced drops in self-efficacy and was silent when he perceived his classmates as overly fluent; in his case, a combination of high levels of trait anxiety and low trait WTC, combined with high responsiveness to contextual factors could explain this drop in confidence and WTC. A combination of self-confidence and group dynamics was also mentioned by Kate as affecting both her motivation and WTC. The comfortable class atmosphere contributed to her overall high motivation as she wanted to partake in classroom discussions without feeling any pressure from the teacher or her classmates (min. 7.5). In addition, her self-confidence was boosted by positive feedback, which in turn made her more motivated and willing to contribute to the group discussions (min. 15). She also reported that she gained further confidence as she got progressively involved in the task; this contributed to motivate her to keep participating and discussing with her peers (min. 10). Hailey reported high motivation and willingness to interact during both small-group discussions and whole-class activities without being afraid of making mistakes. She mentioned that peer and teacher familiarity affected her self-confidence which in turn impacted the two constructs under investigation (min. 7.5). Similarly, Bryce mentioned the importance of feeling comfortable with peers in order to be willing to communicate and motivated to engage in the classroom activities; he also underlined the importance of interacting with peers who are also self-confident and willing to get involved in the task at hand (min. 7.5). James’ profile was rather different in comparison with the other participants; he charted very high WTC but reported low motivation (min. 15 and 17.5). He stated that he had already reached his learning goal in French and his high self-confidence combined with low anxiety positively affected his WTC but not his motivation. Interestingly, James displayed high L2 self-confidence but not the other types of motivational propensities present in MacIntyre et al.’s (1998) pyramid model. In contrast with James, Sylvia reported both high motivation and WTC; she was highly motivated due to her intrinsic interest in French and she

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experienced high self-confidence, influenced in part by the classroom atmosphere and her knowledge of the discussion topic (min. 2.5 and 10). In contrast, she noted that when switching from a topic which she knew a lot about to one she was less interested and confident in, her WTC and subsequent motivation to engage in the activity fell (min. 20). Topic familiarity was also mentioned by Claire as affecting her confidence, as well as her WTC and willingness to engage in the classroom activities (min. 7.5). Individual involvement in the learning activities

In conjunction with confidence and classroom dynamics, another crucial variable affecting both individual motivation and WTC, when paired with factors such as type of task and topic familiarity, was task participation. Students reported that when they were directly and actively involved in the task at hand, both their WTC and motivation were generally higher, as opposed to when they had to listen to other groups’ contributions or during teacher-fronted time. Lucy, for instance, reported lower motivation when having to listen to the other groups during the feedback session, as she did not have to contribute at that point in the lesson (min. 25). However, when she was directly involved in the activity and had to present the answers of her group, she was highly motivated and willing to share her work, also due to her confidence about the work done (min. 22.5). Kate also highlighted the role of task involvement for both her motivation and willingness to engage in the discussion; she mentioned that the more she spoke French in the first group activity, the more she was motivated to keep reacting and counteracting her peers’ arguments (min. 10–15). She also underlined the role of the teacher in making her want to engage and interact in the class (min. 7.5). She explained that she did not feel the pressure of making mistakes while speaking, due to the positive and relaxed classroom atmosphere provided by the teacher; this made her more willing to learn French in the classroom and to use it in communicative contexts with her peers. Max also reported both high motivation and WTC during the small-group activities, as they required learners to interact and actively contribute in order to achieve the task aim (min. 2.5). In contrast, his motivation dropped when not having to proactively contribute to the whole-class discussion (min. 22.5). Hailey did not talk about task participation but rather her involvement in conversation with the teacher; she reported being most ‘engaged with the language’ at that point and being intensely motivated while talking directly to her tutor (min. 10). According to Bryce, the type of activity had an impact on his willingness to get involved in the task at hand and his WTC, in conjunction with peer confidence and involvement and topic familiarity (min. 0 and 7.5). Similarly, James underlined the impact of peer involvement on his own willingness to interact and

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engage with the group tasks (min. 10); he added that not having to contribute to the task, as for instance during teacher-fronted time, would decrease his motivation and WTC (min. 22.5). Like Max, both Sylvia and Claire reported being more motivated to get involved and willing to interact during the small-group activities, as they provide opportunities for equal participation and contribution to the discussion (min. 10 and 37.5). Finally, Claire added that topic familiarity, in turn, had an impact on her participation in the activities (min. 7.5). While previous research highlighted the role of peer involvement in shaping motivation and WTC during the lesson (e.g. Mystkowska-Wiertelak & Pawlak, 2017), the present study elaborates this earlier work by showing the combined impact of peer involvement and individual involvement in the learning activities on both constructs, suggesting a strong link between motivation, WTC and classroom engagement. Group and classroom dynamics

Another important determinant of the relationship between motivation and WTC was the classroom atmosphere, reflecting a combination of group dynamics and teacher factors. Learners’ motivation and WTC were shaped by the social and academic environment in the classroom, and the environment in the classroom was in turn shaped by individual learners’ attitudes and behaviour, consistent with the co-adaptation process described earlier by Ushioda (2015). Each of the interviewed students revealed that the social relationships within the class influenced individual motivation and willingness to engage in a conversation, in conjunction with factors such as task type and self-confidence. Lucy, for instance, mentioned that the specific group dynamics within the first and second group affected her motivation and WTC in distinct ways. She reported feeling comfortable and motivated to interact with the first group; furthermore, although she and her peers were struggling with the first activity, they nonetheless attempted to face the challenges posed by the task cooperatively (min. 10). In contrast, in the second group, Lucy did not feel comfortable to speak (both her WTC and motivation dropped) as she felt much less proficient in comparison to one of the groupmates and was too embarrassed to partake in the discussion (min. 42.5). Group dynamics were also deemed to be important by Kate, who reported that, once she and her peers got progressively involved in the first task and equally participated in the discussion following a natural pattern of contribution, she was even more motivated to participate and share her ideas (min. 7.5–15). Both Kate and Max added feeling more motivated and comfortable to interact within small-group tasks, as opposed to whole-class activities, where they felt more reluctant to engage (min. 22.5 and 2.5). They also both mentioned the role of the teacher in creating a relaxed and pressure-free classroom atmosphere where learners feel at ease with

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participating and interacting with each other (min. 7.5 and 12.5), echoing Kang (2005) and MacIntyre and Legatto (2011), who also highlighted the central role played by the teacher in shaping learners’ WTC. Hailey underlined familiarity with peers and teachers as playing a key role for her motivation, willingness to get involved in discussion activities and self-confidence (min. 22.5). Both Bryce and James highlighted the importance of working with partners who are also confident and willing to participate in the activities; they reported that the degree of peer involvement both at a group and at a class level had a large influence on their WTC and their motivation to participate in the tasks (min. 7.5 and 10). While Sylvia mentioned the influence of her classmates’ displayed confidence and degree of involvement on her own WTC and motivation to actively participate in class (min. 10), Claire reportedly felt more confident when working with someone she previously knew (min. 2.5). Summary of Findings and Conclusion

This study set out to explore dynamic changes in motivation and WTC at the lesson level taking a micro-perspective drawing on selfreport charts and student interviews. Our data revealed the multifaceted and dynamic nature of both constructs, as alternating periods of change and stability were identified during the lesson and within each task. Fluctuations over time were due to an interplay of factors which were individual, social and contextual in nature, and which mutually affected each other in complex ways, in alignment with a CDST perspective (de Bot et  al., 2007; Larsen-Freeman & Cameron, 2008). Indeed, dynamic variability over time in motivation and WTC was not determined by the impact of one isolated variable but was due to the combination of a series of situation-specific interacting variables at a given moment in time, each also subject to variability at different timescales. Among the most prominent factors contributing to dynamic fluctuations in motivation were self-confidence, classroom atmosphere (including teacher and group dynamics), task participation and interest in the topic, which mirrors earlier work (Pawlak et  al., 2014; Poupore, 2013; Waninge et  al., 2014). When these factors were combined with other variables (e.g. type of task, peer involvement) at a specific moment during the lesson, either positive or negative fluctuations, or periods of relative stability in motivation were experienced by students. In line with earlier work, changes in WTC were mostly affected by different combinations of factors including self-confidence, peer involvement, task type and familiarity with the topic (e.g. Kang, 2005; Mulvaney, 2015; Mystkowska-Wiertelak, 2016; Mystkowska-Wiertelak & Pawlak, 2017; Pawlak et al., 2016). Importantly, motivation and WTC appeared to go hand in hand when a series of factors were at play at a given point during the lesson. In addition to self-confidence and individual involvement, the social

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relationships within the classroom appeared to have played a crucial role in providing favourable conditions for both high motivation and WTC. When students felt that other people in their group were not particularly willing to engage, their motivation and WTC tended to decrease. In contrast, their motivation and WTC were high when students perceived that their peers were willing to interact and to get involved. WTC and motivation appeared thus as self-sustaining, shared among participants. Furthermore, the teacher in the present study played a key role in generating a supportive classroom atmosphere where learners felt motivated to engage in the activities and interact without being afraid of making mistakes. Limitations and directions for future research and practice

This study has several limitations, the most prominent being the fact that a situated and micro-scale approach that draws on the data of eight learners does not allow generalisations to other L2 learning contexts. In addition, the participants in our study had already studied French for at least five years; investigating the motivation and WTC of learners at different stages of L2 learning could provide further information about the impact of initial conditions on variability in the two constructs. Furthermore, only one lesson per class taught by one teacher of one target language was investigated. A wider variety of lessons, tasks and target languages would have certainly provided a broader picture of motivation and WTC in the L2 classroom. Investigating classes taught by different teachers would have also contributed to determine the impact of different teaching personalities on motivation and WTC. An important caveat to our data is the fact that the participants in this study, with one exception, displayed an overall high level of motivation and WTC and had similar French proficiency. Participants had signed up voluntarily to the study, which made it more likely that either more motivated students or students who wished to complain about their French class would take part. It would be vital to study students with a broader variety of motivation, WTC and proficiency levels, as well as their personality types to receive further insights into the different factors accounting for changes over time of motivation and WTC, and the interconnections between the two constructs. Despite these limitations, we cautiously formulate some implications for L2 teaching practice. Teachers and learners alike would benefit from knowing about the different factors accounting for fluctuations in motivation and WTC. Indeed, though teachers are likely to be implicitly aware of which activities seem to boost motivation in their students, they may not explicitly be able to underline which specific factors converge to create motivation and WTC in their students. Some might also tend to think that if a student appears unmotivated or unwilling to communicate, it is due to more enduring personality traits not subject to change over the

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course of the single lesson. For this reason, it is important that teachers acknowledge the highly dynamic nature of motivation and WTC and the reasons underlying their changes even at very short timescales. Following the students’ comments, implementing tasks that require extensive and constant involvement of the learners (e.g. discussion activities), particularly when performed in small groups, could be highly beneficial to both WTC and motivation. In contrast, teacher-led or whole-class activities seem to trigger drops in both motivation and WTC, as participation in these activities is mostly based on volunteering. Yashima et al.’s (2016) intervention study revealed that, in the context of whole-class activities, when Initiation-Response-Feedback (IRF) patterns were avoided, and therefore the responsibility to partake in discussions was left to learners rather than the teacher, learners showed higher initiative and classroom participation. The choice of interesting and personally relevant topics and familiar topics also appeared key to high motivation and WTC in the classroom. Finally, it is important to bear in mind that a student displaying low WTC is not necessarily unmotivated, but might perhaps have a lack of self-confidence or be negatively affected by group dynamics. A possible solution to this seems to be encouraging students through positive feedback and creating a relaxed, low-pressure classroom atmosphere and probably change groups with unfavourable dynamics. As suggested by Dewaele and colleagues (see, for instance, Boudreau et  al., 2018; Dewaele & MacIntyre, 2014), since there is not much that teachers can do to reduce anxiety in the L2 classroom, they should focus instead on fostering positive emotions such as enjoyment. Finally, from a methodological perspective, the innovative combination of the idiodynamic method and Motometer (MacIntyre & Legatto, 2011; Waninge et al., 2014) developed for the present study has shown to be a fruitful approach that allows for a micro-level analysis of intra- and inter-individual changes in motivation and WTC in the L2 classroom. Crucially, this method let us investigate personal, social and contextual variables affecting motivation and WTC in the classroom without being disruptive for learners or teachers. Future research could draw on a similar approach for the classroom investigation of other affective variables and self-beliefs (e.g. anxiety, self-efficacy), peer interaction and both observable and unobservable forms of engagement with learning activities. The methodology developed for this study would also suit a mixedmethod research design drawing on a larger sample size. References Boudreau, C., MacIntyre, P. and Dewaele, J.-M. (2018) Enjoyment and anxiety in second language communication: An idiodynamic approach. Studies in Second Language Learning and Teaching 8 (1), 149–170. doi: 10.14746/ssllt.2018.8.1.7 Braun, V. and Clarke, V. (2006) Using thematic analysis in psychology. Qualitative Research in Psychology 3, 77–101.

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Nitta, R. and Asano, R. (2010) Understanding motivation-in-action from a dynamic systems approach. Nagoya Gakuin Daigaku Ronshu 21 (2), 37–49. Papi, M. (2010) The L2 Motivational Self System, L2 anxiety, and motivated behavior: A structural equation modeling approach. System 38 (3), 467–479. https​://do​i.org​/10.1​ 016/j​.syst​em.20​10.06​.011 Pawlak, M. (2012) The dynamic nature of motivation in language learning: A classroom perspective. Studies in Second Language Learning and Teaching 2 (2), 249–278. https​://do​i.org​/10.1​4746/​ssllt​.2012​.2.2.​7 Pawlak, M. and Mystkowska-Wiertelak, A. (2015) Investigating the dynamic nature of L2 willingness to communicate. System 50, 1–9. https​://do​i.org​/10.1​016/j​.syst​em.20​ 15.02​.001 Pawlak, M., Mystkowska-Wiertelak, A. and Bielak, J. (2014) Another look at temporal variation in language learning motivation: Results of a study. In M. Pawlak and L. Aronin (eds) Essential Topics in Applied Linguistics and Bilingualism: Studies in Honor of David Singleton (pp. 89–109). Heidelberg/New York: Springer. https​://do​ i.org​/10.1​007/9​78-3-​319-0​1414-​2_6 Pawlak, M., Mystkowska-Wiertelak, A. and Bielak, J. (2016) Investigating the nature of classroom WTC: A micro-perspective. Language Teaching Research 20 (5), 654–671. https://doi.org/10.1177/1362168815609615 Peng, J. (2007) Willingness to communicate in the Chinese EFL classroom: A cultural perspective. In J. Liu (ed.) English Language Teaching in China: New Approaches, Perspectives, and Standards (pp. 250–269). London: Continuum. https​://do​i.org​/10.5​ 040/9​78147​42121​99.ch​-013 Peng, J. (2012) Towards an ecological understanding of willingness to communicate in EFL classrooms in China. System 40, 203–213. https​://do​i.org​/10.1​016/j​.syst​em.20​ 12.02​.002 Peng, J.E. (2014) Willingness to Communicate in the Chinese EFL University Classroom: An Ecological Perspective. Bristol: Multilingual Matters. Poupore, G. (2013) Task motivation in process: A complex systems perspective. The Canadian Modern Language Review/La revue canadienne des langues vivantes 69 (1), 91–116. https://doi.org/10.3138/cmlr.1139 Poupore, G. (2016) Measuring group work dynamics and its relation with L2 learners’ task motivation and language production. Language Teaching Research 20 (6), 719–740. Ushioda, E. (2015) Context and complex dynamic systems theory. In Z. Dörnyei, P.D. MacIntyre and A. Henry (eds) Motivational Dynamics in Language Learning (pp. 47–54). Bristol: Multilingual Matters. Verspoor, M. (2015) Initial conditions. In Z. Dörnyei, P.D. MacIntyre and A. Henry (eds) Motivational Dynamics in Language Learning (pp. 38–46). Bristol: Multilingual Matters. Waninge, F., Dörnyei, Z. and De Bot, K. (2014) Motivational dynamics in language learning: Change, stability, and context. The Modern Language Journal 98 (3), 704–723. https​://do​i.org​/10.1​111/m​odl.1​2118h​ttps:​//doi​.org/​10.11​11/j.​1540-​ Yashima, T. (2002) Willingness to communicate in a second language: The Japanese EFL context. The Modern Language Journal 86, 55–66. https://doi. org/10.1111/1540-4781.00136 Yashima, T. (2009) International posture and the ideal L2 self in the Japanese EFL context. In Z. Dörnyei and E. Ushioda (eds) Motivation, Language Identity and the L2 Self (pp. 144–163). Bristol: Multilingual Matters. Yashima, T., Zenuk-Nishide, L. and Shimizu, K. (2004) The influence of attitudes and affect on willingness to communicate and second language communication. Language Learning 54, 119–152. https​://do​i.org​/10.1​111/j​.1467​-9922​.2004​.0025​0.x Yashima, T., MacIntyre, P.D. and Ikeda, M. (2016) Situated willingness to communicate in an L2: Interplay of individual characteristics and context. Language Teaching Research 22 (1), 115–113. https://doi:10.1177/1362168816657851

9 Nested Locatives: Conceptual Basis and Theoretical Import Ronald W. Langacker

As a variant of simple locative sentences like The report is on my desk, English permits nested locatives (NL), as in The report is in the study, on my desk, in a folder. Any number of locational expressions can be chained together in this fashion. Moreover, the sentence obtained by reversing the order of these expressions is equivalent in the sense of referring to precisely the same situation: The report is in a folder, on my desk, in the study. Linguistic analysis of the nested locative construction raises a variety of descriptive and theoretical issues that are addressed from the standpoint of Cognitive Grammar (CG), which seeks an integrated account of structure, processing and discourse. The construction illustrates the dynamicity of linguistic structure, which consists of patterns of activity that occur in processing windows on different timescales. It exhibits iconicity, whose characterisation hinges on the correct identification of the linguistic and ‘extralinguistic’ structures involved and the nature of their relationship. If the locatives are ‘nested’, the construction nonetheless appears to be serial rather than hierarchical, raising the issue of how these fundamental aspects of conceptual and linguistic organisation can both be accommodated. This is straightforward in CG, where grammar resides in flexible assemblies of symbolic structures (formmeaning pairings) effecting the implementation of semantic functions, including both descriptive and discursive factors.

Nested locatives are exemplified in (1). In this construction, a series of locatives (usually prepositional phrases) all serve to locate the clausal subject. The series can be of any length, and gives the impression of either ‘zooming in’ to successively smaller regions or ‘zooming out’ to successively larger ones. Yet, the sentences in (1) describe the same situation: in purely objective terms, reversing the sequence of locatives makes no difference. Although the NL construction is intuitively easy to grasp, its linguistic characterisation is neither simple nor straightforward. It raises

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both descriptive and theoretical issues, to be addressed from the standpoint of CG (Langacker 2008, 2016a). (1) (a) The report is in the study, on my desk, in a folder. [‘zooming in’] (b) The report is in a folder, on my desk, in the study. [‘zooming out’] Preliminaries

Cognitive Grammar is specifically characterised as a dynamic usagebased model (Langacker, 2000). This characterisation pertains not only to language learning, as featured in Verspoor’s research, but also to the very nature of linguistic structure. Most generally, structure resides in patterns of activity, which can be viewed on various levels (e.g. neurological, processing, physical, interactive, discursive). Learning thus consists of mastering a dynamic system of conventionalised routines (referred to as units), which are flexibly applied as elements adapt to one another as well as the larger context. The present discussion centres on a particular aspect of this dynamicity: the notion that many and varied paths of access are both inherent in linguistic structures and essential to their import. Their apprehension can therefore be described as a matter of subjective motion on the part of the conceptualiser. The cases analysed in Verspoor (1997) further illustrate this very general phenomenon. CG posits just three basic kinds of structures: semantic, phonological and symbolic. Abstractly characterised, structure is a matter of elements being connected in certain ways, notably by association, contiguity or overlap, e.g. a symbolic structure resides in the association of a semantic and a phonological structure. Connected elements influence and adapt to one another. They constitute a grouping, which has the potential of functioning as a whole – effectively as a single element – in further connections. A set of connected elements, of any size or configuration, constitutes an assembly. Lexicon, grammar and discourse are described in CG as assemblies of symbolic structures, and since these overlap, they constitute a single, vast assembly. As noted, CG views structure as dynamic, consisting of patterns of activity. Thus, it has a time course, unfolding through processing time (T) in a certain manner. Obvious for phonology, where T is known as speech time (sp), it is also true for conception, where T functions as conception time (cc). Processing activity runs concurrently at different levels and on different timescales. On a given timescale, we can posit windows of a certain rough duration, within which connections are made and structure emerges. A connection involving temporal asymmetry amounts to access. In what follows, it is argued that an assembly includes multiple paths of access residing in successively connected elements. The co-alignment of access paths is a feature of iconicity and presumably makes for processing efficiency. Assemblies have no specific form, but represent a complex mixture of the basic configurations in Figure 9.1. These actually differ only in degree

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Figure 9.1  Basic structural configurations

(Langacker, 2016b), the arrows in each case indicating direction of access. At each level in a hierarchy, substantive component elements are grouped to form a composite whole, itself a component in a larger grouping. The essential feature of seriality is that elements occur in sequence, adjacent elements being connected by temporal contiguity. Layering involves an asymmetry between a substantive core and its elaboration, at successive levels, by elements of lesser substance which can also be viewed as operations (hence the alternate notations in [c] and [d]). All these paths figure in a word like helpfully (Figure 9.2) at both the semantic pole (shown at the top) and the phonological pole (below). It illustrates the co-alignment of paths, indicated formulaically in (2); this parallelism (‖), a main factor in the morphological regularity of such expressions, represents a basic kind of iconicity. For each type of configuration, semantic structures (represented in upper case) are accessed in the same sequence as the corresponding phonological structures (in lower case). In this and other diagrams, boxes with rounded corners enclose various sorts of groupings and their nesting indicates layering. (2) (a) Hierarchy: {HELP, FUL} → HELPFUL; {HELPFUL, LY} → HELPFULLY ‖ {help, ful} → helpful; {helpful, ly} → helpfully (b) Seriality: HELP > FUL > LY ‖ help > ful > ly (c) Layering: HELP ⇨ HELPFUL ⇨ HELPFULLY ‖ help ⇨ helpful ⇨ helpfully

Figure 9.2  A morphological assembly

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Iconicity

Iconicity resides in some kind of similarity. The sort that concerns us has several properties. It is form-meaning iconicity because it holds between semantic and phonological structures. It is diagrammatic because the resemblance does not reside in these structures taken individually, but rather in the relations connecting corresponding structures at the two poles. Because these relations are based on temporal sequencing (>), the iconicity has a serial aspect. And because it involves a similarity between linguistic structure and something external to it, it also has an extralinguistic aspect. These properties are all exemplified in (3), where the order of event description is conceived as mirroring the actual order of events. (3) He won the lottery, quit his job, and moved to Hawaii. The first three properties characterise a kind of iconicity inherent in all complex expressions: a path of access based on symbolisation, consisting of the co-alignment of a series of semantic structures (X > Y > Z) with the corresponding series of phonological structures (x  >  y  >  z). Exemplified by the parallelism in (2)(b), a symbolisation path is shown abstractly in Figure 9.3(a). In expressions like (3), the relevant semantic structures designate events (E), as shown in Figure 9.3(b). As it stands, however, this diagram fails to capture the extralinguistic aspect of iconicity. Being internal to the expression, the series X > Y > Z unfolds through processing time (T), so 3(b) merely indicates that the events are conceived in the order of their symbolisation, not that they occurred in that sequence. For this, we need the more elaborate representation in 3(c). Processing time (through which conception occurs) is distinguished from conceived time (t): its role within the situation described referred to as the descriptive target (DT). Whereas the series of symbolised event conceptions (X > Y > Z) unfolds through T, the series of described events (E1  >  E2  >  E3) unfolds through t (a facet of DT). The iconicity thus

Figure 9.3  Symbolization paths

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involves a three-way parallelism: E1 > E2 > E3 ‖ X > Y > Z ‖ x > y > z. If we think of DT as a prelinguistic structure, its evocation and symbolic description bring it within the purview of linguistic meaning. Their relation is one of categorisation, in which each semantic structure (say, X) construes its conceptual target (E1) in accordance with its conventional import: [X[E1]]. A categorising structure and its target interact, each adapting to the other; if I describe a foetus as a baby, I am stretching the meaning of baby while ascribing to the target certain of its specifications and connotations. Likewise, the blended conception [X[E1]] represents both the linguistic construal of [E1] and any adjustment needed for [X] to apply to it. Owing to this interactive relationship, it makes no real difference whether the parallelism of X > Y > Z and E1 > E2 > E3 is induced by linguistic expression (x  >  y  >  z) or is reflected in it. Either way the structure is the same. What about examples like (4)? I have heard them cited in arguing against the prevalence of iconicity: (4) He lives now in Hawaii. He quit his job in Chicago. He won the lottery. However (4) clearly is iconic, if not in the narrow sense of mirroring the order of occurrence, at least in the broader sense of being determined by it. This reverse iconicity would be as shown in Figure 9.4(a). But instead of positing a distinct kind of iconicity, it seems preferable to ascribe the reversal to the target situation. From the cognitive linguistic perspective, DT is a conception (even when it pertains to objective reality), hence subject to elaboration (⇨) by mental operations. Here, we can say that DT reflects our ability to run through a series of prior actions, in reverse, in order to figure out how a situation has come about, as in (5):

Figure 9.4  “Reverse” temporal iconicity

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(5) I’m in jail because I assaulted someone, because I drank too much, because I was depressed. Based on this analysis, the iconicity in (4) is depicted in Figure 9.4(b). The event sequence E1  >  E2  >  E3, where ‘>’ can be read as ‘precedes in t’, functions as a baseline. From that, elaboration by reversal yields the sequence E3 ​ y > ​z. Nested Locatives

The meaning of a spatial preposition is sketched in Figure  9.5. It profiles a relationship (bold arrow) between two participants, its trajector (tr) and its landmark (lm). The trajector is the entity being located (mentally accessed), and as the arrow indicates, it is accessed via the landmark. A preposition does not locate its trajector with full precision, but merely confines its position to a certain region – its search domain (SD; Hawkins, 1984); e.g. the SD for in is the landmark’s interior, for on its upper surface and for near its vicinity. The outer box represents the preposition’s immediate scope (IS): the expanse of space in which the profiled relationship is manifested. The NL construction comprises a series of prepositional phrases with different landmarks (specified by the prepositional object), but which all have the same trajector (specified by the clausal subject). It has two variants, in which the locative phrases occur in opposite orders, e.g. The report is in the study, on my desk, in a folder [(1)(a)] vs The report is in a folder, on my desk, in the study [(1)(b)]. Despite containing the same elements and describing the same objective situation, these variants are semantically non-equivalent because they construe this situation in alternate ways, characterised impressionistically as ‘zooming in’ vs ‘zooming out’. From the CG perspective – where meaning is dynamic, residing in conceptual structure with a time course – this is more than just an impression, but an actual semantic distinction. The difference does not

Figure 9.5  Semantic pole of a spatial preposition

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Figure 9.6  Nested locative sequences

inhere in the objective situation described (DT), but in how that configuration is accessed through conception time (cc). The contrasting locative sequences are represented in Figure 9.6. In each case, the locatives are connected by conceptual overlap (indicated by dotted correspondence lines). They have the same trajector, referred to in the full expression as the report. The impression of zooming in or out stems from another sort of overlap, which is less obvious because the notions involved – SD and IS – are abstract; they are adopted in CG on multiple grounds (Langacker, 1999a), being needed for the explicit characterisation of semantic and grammatical structure. As shown in 6(a), the effect of zooming in results from the SD of one locative being identified with the IS of the next. Thus SD1, the interior of the study, functions as IS2, the region in which the relation on my desk is manifested. SD2, the upper surface of the desk, functions in turn as IS3, where the relation in a folder is manifested. In 6(b), we find exactly the same correspondences, but since the order is reversed, the effect is one of zooming out. Hence, the same static array of nested regions gives rise to opposite impressions based on the sequence of mental access. An expression’s IS can be thought of as a window of attention, in which its profile stands out as the focus of attention. Thus, a series of expressions, like that in 6(a) or 6(b), amounts to a moving window that progresses through the descriptive target. At each step along this symbolisation path, the currently active expression directs attention to the portion of DT it delimits and focuses attention on its profile. In Figure  9.7, the outer box corresponds to DT, while the inner boxes represent the nested SDs. Each locative profiles the relation between its two focused participants, shown in bold: the report (r), expressed by the

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Figure 9.7  Alternate paths of access through a descriptive target

clausal subject; and the referent of the prepositional object, either the study (s), the desk (d) or the folder (f). At each stage, solid lines indicate the entities attended to, the others (in dotted lines) being left momentarily in the background. It can be seen that the window moves through DT in the sense of either confining attention to smaller and smaller areas or expanding it to larger and larger ones. The NL construction is a parade example of linguistic construal, where the same situation is conceived and portrayed in alternate ways. It also exhibits the kind of iconicity under discussion: diagrammatic form-meaning iconicity with serial and extralinguistic aspects. It does, however, differ from cases like (3), involving a series of events, in that temporal sequencing is not inherent in the target situation; in and of itself, DT is just a spatial configuration describable without invoking conceived time. We still have a three-way parallelism, as in (3), but instead of a series of events in t (E1 > E2 > E3), the target comprises a set of locations (L) related by spatial inclusion: L1 ⊃ L2 ⊃ L3 ‖ X > Y > Z ‖  x > y > z. Otherwise, the structures are analogous, as seen by comparing Figures 9.3(c) and 9.8(a). The analogy extends to reversal, as seen by comparing Figures 9.4(b) and 9.8(b). The alternate ways of describing events – in their order of occurrence or in reverse – are comparable to the zooming-in and zooming-out variants of the NL construction. As shown in 8(b), we obtain the zooming-out variant by reversing the sequence of access, so that successive locations are no longer related by spatial inclusion, but by expansion (⊂). The latter sequence is thus the one included in the parallelism constituting diagrammatic iconicity: L1 ⊃ ​L2 ⊃ ​L3 ∦ ​L3 ⊂ ​L2 ⊂ ​L1 ‖ ​X > Y​ > Z ​ ‖ x >​ y > ​z. Why is this a reversal? In other words, why should the zooming-in variant be considered more basic? It is, I suggest, both more common and less effortful. Moreover, it reflects a fundamental and very frequent aspect of everyday experience: that of moving through space – physically,

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Figure 9.8  Nested locatives: “zooming in” vs. “zooming out”

perceptually or mentally – in order to find something or reach it. And indeed, expressions like (1)(a) are typically used when an actual instance of such motion is either intended or recalled. To the extent that it is, that event (hence t) is included in DT, but only as a background conception (as opposed to being profiled as the onstage focus of attention). This dynamic construal of a static situation amounts to a kind of fictive motion (Langacker, 1999b; Talmy, 1996). It is, in fact, very similar to the kind known as ‘endpoint focus’ (e.g. Their house is across the street), in which the profile of a path preposition – comprising a series of spatial configurations – is restricted to the last one. The NL construction is comparable except that, instead of being evoked by a single preposition, the path in question is specified by a series of locatives describing salient locations along it. Any notion of moving along this path remains implicit (subjectively construed). Rather than being onstage as the focused object of description, it is manifested indirectly, via the expression’s grammatical organisation. The zooming-out variant is also grounded in an aspect of everyday experience. We have the ability to mentally scan through a series of events, in reverse, in order to figure out how a situation has come about (cf. (5)). Expressions like (1)(b) reflect a special case of this capacity: given a specific location, we can figure out what path we might have taken to get there. (This comes into play when the first locative is too specific. Sure, the report is in a folder. But where is the folder?) Moving step by step along the inverse path is equivalent to successively expanding the scope of awareness (hence zooming out) until it encompasses a known point of origin. As indicated in Figure 9.8(b), this inverse path – being obtained from the zooming-in path by a kind of reverse engineering – constitutes an elaboration (⇨) with respect to it. The diagrams in Figure 9.8 represent only a portion of the NL construction in (1): the locative sequence itself. In a full description, we must

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Figure 9.9  Intermixture of hierarchy and seriality

also spell out its connection with the remainder of the clause. This raises descriptive and theoretical issues of a general nature centring on the relation between hierarchy and seriality. To describe (1)(a), the assembly in Figure 9.9 can be offered as a first approximation. Recall that the connection of elements defines a grouping, which may in turn function as an element in further connections. An assembly is just a set of connected elements; it can be of any size, consisting of groupings arranged in any fashion, and usually represents a mixture of the basic configurations in Figure 9.1. The assembly in Figure  9.9 incorporates two major groupings: one based on hierarchy and the other on seriality. They are connected by overlap, in the study being an element of each. This is correct and unproblematic as far as it goes, but it only goes so far. As it stands, the diagram does not specifically indicate that the report is currently located, not only with respect to the study, but also with respect to the desk and the folder. It shows the clausal grouping and the locative sequence as being connected, but not as being fully integrated, so that the description the report is X applies to them all. A second limitation is that Figure 9.9 does not address the construction’s special prosody, which it shares with a general pattern of serialisation. Discursive Organisation

Lexicon and grammar form a continuum of symbolic structures effecting the implementation of semantic functions. While there is no clear line of demarcation, these are broadly divisible into descriptive and discursive functions (Langacker, 2015a). In an assembly, their implementing structures are interspersed, representing co-existing dimensions of organisation (rather than separate levels or components). As traditionally conceived, grammatical structure is primarily descriptive and basically hierarchical – a matter of composition giving rise to successively more complex composite structures, as in Figure 9.2 (helpfully) or the clausal grouping in Figure 9.9. Discursive functions pertain to the presentation

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and packaging of descriptive content, being manifested through their effect on it. The implementing structures are symbolic. Their meanings involve such factors as salience, locus of attention and information structure (e.g. topic, informational focus). These tend to be symbolised by non-segmental means, including temporal sequencing, prosody and grouping in windows on different timescales. The assembly for a given array of content includes both descriptive and discursive groupings, which can be either coincident or cross-cutting. Since it makes for processing efficiency, coincidence is characteristic of simpler, more canonical structures. An important aspect of discursive organisation is the packaging of descriptive content in prosodic groupings on different timescales. How these relate to descriptive groupings is a key to analysing the NL construction. Semantically, a prosodic grouping consists of a window of attention on descriptive content. Phonologically, it comprises a continuous span of (primarily segmental) content characterised by rhythmic association and internal cohesion, which tend to set it off from others. As a phonologically delimited window of attention, a prosodic grouping reinforces the symbolic relationship inherent in a coincident descriptive grouping; being advantageous from the processing standpoint, their congruence is incorporated in the basic form of many descriptive constructions. Canonical in this respect is a simple clause like The report is in the study, whose hierarchical organisation is indicated in Figure 9.10(a) by nested boxes (a notational variant of tree-like structures). The boxes at these various levels represent descriptive groupings corresponding to familiar grammatical notions, ranging from individual words, through phrases of different sizes, to the clause as a whole. With the most neutral pronunciation, each box is not only a descriptive grouping but also a prosodic grouping on some timescale, so that the hierarchical organisation correlates with the degree of cohesion and rhythmic association. Since this is more evident on larger timescales, the most salient internal groupings (marked in bold) are the largest phrases, corresponding to the classic division into subject and predicate. Discursive organisation has its own rationale, so instead of dovetailing with descriptive organisation, it often crosscuts it. A simple example results from the reduction of a finite verb and its cliticisation to the subject, as in The report’s in the study. In addition to expressive efficiency, its discursive motivation includes the creation of a prosodic grouping

Figure 9.10  Alternate prosodic groupings

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that offers a schematic preview of the clause as a whole (Langacker, 2015b). This yields the prosodic organisation in Figure 9.10(b), where the most salient internal groupings – the report’s and in the study – crosscut the organisation in 10(a). In and of itself, this alternate scheme does not eliminate the descriptive hierarchy, but does overshadow it by imposing a non-congruent symbolisation path based on discursive considerations. The more salient they are, the more the windows of attention delimited by prosodic grouping take over as the moving window that progresses through DT. The prosodic distinction in Figure  9.10 is represented in (6)(a)–(b), where a slash (/) marks the division between high-level prosodic groupings. Such groupings are clearly evident in the NL construction. At the highest-level of organisation, Figure  9.9 comprises three structures arranged in serial fashion: (the report is in the study) > (on my desk) > (in a folder). These are prosodic groupings, set off from one another by slight hesitations indicated orthographically by commas (‘comma intonation’). By substituting slashes for commas, we obtain the representations in (6)(c)–(d) for the NL expressions in (1)(a)–(b). (6)

(a) (b) (c) (d)

The report/is in the study. The report’s/in the study. The report is in the study/on my desk/in a folder. The report is in a folder/on my desk/in the study.

The locative sequences instantiate a general discursive pattern of English. Marked here by underlining, this construction consists of the serial organisation of prosodic groupings exhibiting various sorts of parallelism, e.g. in size, grammatical category and role in larger structures. These are, of course, matters of degree, with other factors coming into play. The locatives in (6)(c)–(d) are prepositional phrases of about the same size, parallel in regard to both their internal structure and their external role (all specify the current location of the clausal subject). And when the sequence stands alone (e.g. in response to the question Where’s the report?), the locatives are clearly delimited prosodic groupings representing windows of roughly the same duration. But in the full NL construction (Figure 9.9), they exhibit a lesser degree of parallelism because the first locative is grouped prosodically as part of the initial clause-like structure. Though it could stand alone as a fully independent clause, that structure is temporally compressed into a time span comparable to that of the other two locatives. Thus, in what I judge to be the most natural rendition, the three prosodic groupings in (6)(c) or (6)(d) have approximately the same duration. The discursive pattern they instantiate, further exemplified in (7), can be imposed on a wide variety of descriptive structures (e.g. noun modifiers, relative clauses, complement clauses, possessives). It comprises a

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series of prosodic groupings, and since these are parallel both prosodically and descriptively (as just noted), it represents a kind of iconicity. The series can be of any length, and as the length increases, the serial organisation becomes more salient and tends more strongly to overshadow the descriptive organisation. (7) (a) Noun modifier: a collection of volumes/of reports/of misconduct (b) Relative clause: a man who has a son/who has a lawyer/who works for Trump (c) Complementation: She believes/they know/Donald lied. (d) Possession: Jill’s/friend’s/sister’s husband (e) Path of motion: They drove from Chicago/to Philadelphia/to New York. (f) Predicate nominative: A lie is a lie/is a lie/is a lie/is a lie. (g) Event descriptions: He won the lottery/quit his job/and moved to Hawaii. (h) Nominals: She has a dog/a cat/a ferret/and a parakeet. (i) Iteration: He ran/and ran/and ran/and ran/and ran. The NL construction thus incorporates a general discursive construction of the form [[X1]/[X2]/[X3]], in which a series of similar structures, representing prosodic groupings on a certain timescale, are delimited by the features informally described as ‘comma intonation’. In addition to their internal similarity (X), these structures are in some way parallel in regard to their external function; whether collectively or individually, they play a certain role in a more inclusive structure. In (7)(d), for example, the possessive sequence Jill’s/friend’s/sister’s collectively fulfills the function of nominal grounding, as it singles out a particular instance of husband. In (7)(h), each conjunct individually serves the function of specifying what she has. The NL construction does it both ways. While the objective in (6)(c) is to locate the report based on the full sequence in the study/on my desk/in a folder, it is also true that each locative, taken individually, accurately describes where it is. Despite their diversity, the expressions in (7) all involve the serial elaboration of a basically hierarchical descriptive structure. This connection of a descriptive hierarchy and a serial structure, resulting in a more inclusive assembly, is shown abstractly in Figure  9.11. Their integration is based on overlap; in the NL construction, the point of overlap – the site of elaboration – is the complement of be (Figure 9.9). Figures 9.11(a) and (b) distinguish the cases of its descriptive function being implemented collectively or individually by elements of the serial structure. As already indicated, the distinction is anything but sharp: a connection with the whole can often be resolved into connections with individual elements; and conversely, these add up to a connection with the whole (Langacker, 2009).

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Figure 9.11  Fulfilling a function collectively vs. individually

Here, it is worth reiterating that assemblies are dynamic, residing in processing activity that unfolds through time in a certain manner. Despite the different connections, the assemblies in Figure 9.11(a) and Figure 9.11(b) lend themselves to a common dynamic characterisation. The elaboration site is a schematic substructure within the descriptive hierarchy (the remainder of which is given as W). The elaborating structure consists of prosodic groupings accessed in a particular temporal sequence: [X1] > [X2] > [X3]. Representing the first in a series of elaborative operations occurring at the site, [X1] is the first structure to occupy the site, whether it does so individually or as the initial element in a series that does so collectively. So when the hierarchical and serial structures occur in that order, and the site is the last element in the former, its initial elaboration by [X1] results in the sequence W > [X1] > [X2] > [X3]. This sequencing is one facet of the overall expression’s phonological organisation, whose full characterisation must also specify the resulting prosodic grouping. Depending on the structures involved, there are two options pertaining to the phonological integration of W and [X1]. On the one hand, they can be loosely integrated by mere juxtaposition, so that the serial structure retains its integrity as a higher-level prosodic grouping. In this case, W is external to it: W[[X1]/[X2]/[X3]]. Alternatively, they are more closely integrated when W and [X1] undergo compression so that together they occupy the first window of that higher-level grouping: [[W[X1]]/[X2]/[X3]]. The expression in (7) allows both options: (8) (a) a collection [of volumes/of reports/of misconduct] (b) [a collection of volumes/of reports/of misconduct] As indicated in Figure 9.9, the NL construction specifies the grouping of W and [X1] in a single window: (9) (a) [The report is in the study/on my desk/in a folder.] (b) [The report is in a folder/on my desk/in the study.] So, in either the zooming-in or zooming-out variant, the initial grouping could stand alone as a full statement describing the situation in less detail.

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Serial Elaboration

A final descriptive question concerns a limitation of Figure 9.9 noted earlier: as it stands, it does not specifically indicate that the report is currently located, not only with respect to the study, but also with respect to the desk and the folder. This, however, proves not to be a limitation of the analysis itself, but rather of the diagrammatic format employed. It is just a matter of no single diagram, given the restrictions of a printed page, being capable of showing everything. Apart from the dual role of in the study (as part of both the hierarchical and serial structures), Figure 9.9 is not explicit regarding connections at the semantic pole. In particular, it does not show correspondences, which are indications of conceptual overlap, in the manner of Figure 9.6. In a more complete representation, these series-internal correspondences would be supplemented with the ones connecting each element with the elaboration site, as in Figure  9.11(b). Owing to its complexity, the full assembly that results is best presented in stages. To simplify the diagrams, the shorthand notations in Figure 9.11 are used for the structures in Figure 9.9. With these abbreviations, and substituting L (location) for X, Figure 9.9 reduces to Figure 9.12(a), in which [W > [L1]] represents the hierarchical structure, and [[L1] > [L2] > [L3]] the overlapping serial structure. Diagram (b) adds to this the effect of prosodic reinforcement. Heavy lines indicate the salience conferred by prosodic groupings at the highest level of organisation. In the NL construction, as shown in (9), these are [W[L1]], [L2] and [L3]. What this diagram does not yet indicate is that the elaboration site does not just correspond to [L1], but to [L2] and [L3] as well. They elaborate this site not only individually, implying the structures [W[L1]], [W[L2]] and [W[L3]], but also successively, in accordance with their seriality. Though unproblematic given the flexible and dynamic nature of assemblies, this is hard to show in a single static diagram. An attempt is made in 12(c), in which [W[L1]], [W[L2]] and [W[L3]] are all represented in the proper sequence. Of course, this format is less than optimal because it wrongly suggests that these structures are disjoint and manifested fully; thus, the latter two are enclosed in dotted lines as an ad hoc means of indicating that they are not. The import of this notation is basically what is shown in Figure 9.11(b): that instead of separate structures, we are dealing with a single structure one facet of which – the site – has divergent elaborations activated sequentially. We obtain Figure 9.12(d) by collapsing the separate representations of the shared structure and assuming its continued activation. As indicated by the larger boxes, what we actually have is a path of access based on layering (cf. Figure  9.1(c)), where each successive layer invokes and builds on what has already been established. In this case, layering correlates with temporal sequencing (as it often does). Hence, the assembly conflates two access paths involving the structures made salient through

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Figure 9.12  Layering based on prosodic grouping

prosodic reinforcement: the serial path [W[L1]]  >  [L2]  >  [L3], where they function as discursively focused elements; and the elaborative path in (10), where they function as operations connecting successive layers. (10) [W[L1​]] ⇨ ​[[W[L1​]]/[L​2]] ⇨​ [[[W[L​1]]/[​L2]]/[​L3]] With respect to this path, [L2] and [L3] represent a descriptive construct I refer to as the differential: in comparing two structures, the differential is what stands out as different in the second one (Langacker, 2012; cf. Culicover & Jackendoff, 2012). This construct figures in the analysis of many phenomena, including information structure, ellipsis and coordination. In the NL construction, symbolisation of the differential constitutes the elaborative operation relating successive layers. It remains true that [L2] and [L3] invoke the shared structure as the basis for their interpretation, as in 12(c), but each relies on the previous layer for this purpose. In this way, the overall construction achieves processing efficiency. Conclusion

Despite the NL construction’s intuitive simplicity, its analysis raises numerous points of descriptive and theoretical interest. The issues addressed here fall under several broad headings: symbolisation, iconicity and the nature of linguistic meaning; the notion that language structure resides in assemblies, whose characterisation involves such factors as dynamicity, access paths, overlap and basic configurations (hierarchy, seriality, layering); and the idea that grammar, as the implementation of semantic functions, represents the intermixture of descriptive and discursive organisation (the latter including both order of presentation and prosodic grouping). While these have been dealt with here only briefly and in preliminary terms, this account of the NL construction may help to illuminate their role in linguistic structure more generally.

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References Culicover, P.W. and Jackendoff, R. (2012) Same-except: A domain-general cognitive relation and how language expresses it. Language 88, 305–340. Hawkins, B.W. (1984) The Semantics of English Spatial Prepositions. Doctoral dissertation, University of California, San Diego. Langacker, R.W. (1999a) Grammar and Conceptualization. Berlin/New York: Mouton de Gruyter. Cognitive Linguistics Research 14. Langacker, R.W. (1999b) Losing control: Grammaticization, subjectification, and transparency. In A. Blank and P. Koch (eds) Historical Semantics and Cognition (pp. 147–175). Berlin/New York: Mouton de Gruyter. Langacker, R.W. (2000) A dynamic usage-based model. In M. Barlow and S. Kemmer (eds) Usage-Based Models of Language (pp. 1–63). Stanford, CA: CSLI Publications. Langacker, R.W. (2008) Cognitive Grammar: A Basic Introduction. New York: Oxford University Press. Langacker, R.W. (2009) Metonymic grammar. In K-U. Panther, L.L. Thornburg and A. Barcelona (eds) Metonymy and Metaphor in Grammar (pp. 45–71). Amsterdam/ Philadelphia, PA: John Benjamins. Human Cognitive Processing 25. Langacker, R.W. (2012) Elliptic coordination. Cognitive Linguistics 23, 555–599. Langacker, R.W. (2015a) Descriptive and discursive organization in Cognitive Grammar. In J. Daems, E. Zenner, K. Heylen, D. Speelman and H. Cuyckens (eds) Change of Paradigms—New Paradoxes: Recontextualizing Language and Linguistics (pp. 205–218). Berlin/Boston, MA: De Gruyter Mouton. Applications of Cognitive Linguistics 31. Langacker, R.W. (2015b) How to build an English clause. Journal of Foreign Language Teaching and Applied Linguistics 2 (2), 1–45. Langacker, R.W. (2016a) Toward an integrated view of structure, processing, and discourse. In G. Drożdż (ed). Studies in Lexicogrammar: Theory and Applications (pp. 23–53). Amsterdam/Philadelphia, PA: John Benjamins. Human Cognitive Processing 54. Langacker, R.W. (2016b) Baseline and elaboration. Cognitive Linguistics 27, 405–439. Talmy, L. (1996) Fictive motion in language and ‘ception’. In P. Bloom, M.A. Peterson, L. Nadel and M.F. Garrett (eds) Language and Space (pp. 211–276). Cambridge, MA/ London: MIT Press/Bradford. Verspoor, M. (1997) Predicate adjuncts and subjectification. In M. Verspoor, K-D. Lee and E. Sweetser (eds) Lexical and Syntactical Constructions and the Construction of Meaning (pp. 433–451). Amsterdam: John Benjamins.

10 Getting Out the Word on Phrasal Verbs: It Turns Out Phrasal Verb Construction Meanings are Systematic and Teachable Andrea Tyler, Hana Jan, Nargas Mahpeykar and Brandon Tullock

One of the most important second language acquisition (SLA) trends of the past 15 years is applying cognitive linguistic (CL) analyses and principles to teaching traditionally challenging areas of English. This chapter continues in this vein by presenting a CL-based, effects-of-instruction study of English phrasal verb constructions (PVCs). The multiple meanings of PVC have largely been considered arbitrary and thus a particular challenge for L2 learners. Analyses aimed at finding systematicity have tended to focus exclusively on the contribution of the multiple meanings of the prepositions in PVCs and assumed a single meaning for the verb. However, using a CL-inspired framework (Goldberg, 2005; Langacker, 2008; Tyler & Evans, 2003), Mahpeykar and Tyler (2014) noted that verbs in PVC constructions also have multiple meanings. Their corpus-based analysis established that considering the contribution of the polysemy networks of both verbs and the prepositions allows for a systematic representation of the multiple meanings of PVCs. After presenting this framework, we discuss the results of a small-scale study which investigated using the CL framework as the basis for classroom instruction. The participants were enrolled in two, low intermediate classes in an intensive English programme; 11 participants received CLbased instruction on the multiple meanings of four PVCs; 14 received non-cognitive instruction. The intervention consisted of three  hours of instruction, which combined interactive, teacher-fronted PowerPoint presentations interspersed with student centred, task-based instruction. 224

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All participants took a pre-test, immediate post-test and delayed posttest; each test item included a ‘guessed’/‘didn’t guess’ confidence rating. Accuracy results showed both groups improved (CL gain scores were 2.5 points, control were 0.9) but there were no significant between-group differences. However, the confidence ratings showed that the CL group’s ‘didn’t guess’ scores went from 1.5 to 9.1, while the control group’s went from 6.3 to 9.8; a repeated analysis of variance (ANOVA) showed that the CL group’s confidence gains by the post-test were significantly greater (p = 0.000); this gain was maintained for the delayed post-test. Introduction

One of the most important trends in second language acquisition (SLA) of the past 15 years is applying cognitive linguistics (CL) analyses and principles to teaching traditionally challenging areas of language (e.g. Ortega et al., 2016; Tyler, 2012; Tyler et al., 2018a, 2018b; Verspoor & Tyler, 2009). This chapter continues in this vein by presenting a new CL analysis of English phrasal verb constructions (PVCs) and a consideration of how the analysis can be used in creating a second language (L2) pedagogical treatment. One of the primary reasons L2 students of English find many constructions challenging is that they are typically represented as being arbitrary in their meaning and/or use. CL has a number of attributes that make its approach to language particularly potent for re-analysing such challenging areas and crafting theory-consistent pedagogy. With its commitment to putting meaning at the centre of language (meaning is central to all linguistic units from lexical to sentence level to discourse level [Langacker, this volume]), its commitment to embodied meaning and to the usage-based nature of language, CL has provided theoretical insights that allow us to shift our understanding of how language works and discover systematicity in what had seemed arbitrary and outside the purview of analysis. The multiple meanings of PVCs have largely been considered arbitrary and thus a particular challenge for L2 learners. For instance, according to the online dictionary, WordNet, the phrasal verb take off has more than a dozen meanings, some of which include: remove, as in He took off his coat; leave, as in She took off for Alaska in 1945; become popular or successful, as in The singer’s career took off after she had a hit record; stop working temporarily, as in Many people in the area will take off work for the holiday; provide a discount, as in In order to encourage people to shop, stores are taking off 10% for most of their merchandise. These multiple meanings are often not obviously related, leading to the conclusion that they are non-compositional and arbitrary. Recent analyses aimed at finding systematicity in PVCs have appeared (e.g. Linder, 1981; Rudzka-Ostlyn, 2003); however, they have tended to focus exclusively on the contribution of the multiple meanings of the prepositions in

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the PVCs and assumed a single meaning for the verb. Using a CL-inspired framework (e.g. Goldberg, 2006; Langacker, 2008; Tyler & Evans, 2003), Mahpeykar (2014) and Mahpeykar and Tyler (2014) noted that verbs in PVCs also have multiple meanings. Their corpus-based analysis established that considering the contribution of the polysemy networks of both verbs and prepositions allows for a systematic representation of the multiple meanings of PVCs. After presenting this framework, we consider some ways in which the analysis might guide the creation of pedagogical materials. Finally, we present an exploratory study which investigated using CL-inspired materials as the basis for classroom instruction. CL recognises that cognition is crucially shaped by the kinds of bodies we have, including our perceptual systems and how they are configured, and our interactions with the spatial-physical world (e.g. Bybee et al., 1994; Gibbs, 1994; Grady, 1997; Johnson, 1999). This shaped cognition is robustly reflected in language. For the purposes of this chapter, three key reflections of embodied experience will prove central: (1) figure/ ground (F/G) organisation; (2) experiential correlation; and (3) invited ­inferencing or micro consequences. Ever since the work of the Gestalt psychologists in the early 1900s, F/G organisation has been recognised as a fundamental principle of our visual perceptual system. Humans do not view the world in terms of flat arrays of objects. Rather, we perceive the world in terms of focal entities (generally smaller and more mobile) located in terms of a grounding or locating entity (generally larger and less mobile). F/G is an important organising principle for many levels of linguistic organising from prepositions (The banana (F) is in the bowl (G)) to discourse-level patterns (e.g. Evans & Green, 2006; Goldberg, 2008; Langacker, this volume; Taylor, 2002). In the current study, our focus will be on the F/G configurations labelled by English prepositions. A fundamental aspect concerning how we experience the world is that our everyday physical actions and the spatial configurations we observe have important, nearly unavoidable ‘micro’ consequences for us. Even though these consequences are central to how we understand the world, they tend to occur below the level of the consciously noted. These ubiquitous, often unremarkable, consequences are crucial as we navigate the world and they are central to the configuration of language. We will consider two areas: invited inferences, largely associated with verbs, and experiential correlation, largely associated with prepositions and other forms of spatial language. Linguistically, events and actions are labelled by verbs (Langacker, 1987, this volume); these verb ‘labels’ tend to tag the whole action, not directly denoting the smaller movements that make up the action nor the inevitable consequences for humans engaging in these movements. Bybee et al. (1994) discuss these micro consequences in terms of invited inferences. Consider the action of turning. To clarify the effects of this simple

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action, station yourself and look straight ahead. Note what you see. Now turn your head to the right. You see a different scene; in viewing this new scene, your mental map of the world was slightly updated or changed. In all likelihood, you learned a little something. Maybe you noticed dust accumulated on a shelf that you did not know about or a ‘missing’ book stacked on a table. You experienced a change of state in your knowledge. Such a micro consequence occurs almost every time you engage in an act of turning your head or your body. Frequently, when you describe an action that involves the act of turning, you invite your listener to infer that some change (often very small) took place. Of course, sometimes the act of turning will result in more startling change, such as witnessing something out of the ordinary. The ubiquitous consequence of change arising from turning has resulted in the notion of change becoming an important extended meaning connected to the word turn. We will return to this below. Another set of similar micro consequences has been discussed in the literature in terms of experiential correlation. Here, the link between linguistic forms and extended meanings involves observations concerning frequent co-occurrences between two events in everyday experience. For instance, in our daily experience we encounter a recurring correlation between quantity and vertical elevation, such as when objects are added to a pile or liquid is added to a container. In these instances, an increase in quantity correlates with an increase in vertical elevation. The ubiquitous observation of these two co-occurring phenomena results in a strong cognitive association between the two. This conceptual association, in turn, is reflected in language such as The prices have gone up, in which language from the domain of vertical elevation (up) is used to talk about an increase in amount (e.g. Grady, 1997; Johnson, 1999; Lakoff, 1987). Armed with the insights into language provided by embodied meaning, we tackle the mystery of PVCs. The Analysis of English Phrasal Verb Constructions

The semantics of English PVCs and their multiple meanings are a widely recognised challenge in representations of English. In spite of several attempts at analysis (e.g. Bolinger, 1971; Kennedy, 1920; Live, 1965), the multiple meanings of these lexical units have been generally regarded as arbitrary and unpredictable (e.g. Celce-Murcia & Larsen-Freeman, 1999; Fraser, 1976; Lipka, 1972). However, CL research has shown that word and constructional (Goldberg, 2006) polysemy is often motivated, suggesting that the multiple meanings of PVCs should also exhibit systematicity (e.g. Brugman & Lakoff, 1988; Deane, 2005; Dirven, 2001; Lakoff, 1987; Linder, 1981; Newman, 1996; Rudzka-Ostyn, 2003; Taylor, 2002; Tyler & Evans, 2001, 2003; Vandeloise, 1991). Indeed, advances in CL have provided some evidence for the systematicity of PVCs, primarily

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through examining regularities found in the polysemy of prepositions and particles (e.g. Linder, 1981; Rudzka-Ostyn, 2003; Taylor, 2002; Tyler & Evans, 2003). Nevertheless, most CL studies have not provided a detailed explanation of the semantics of PVCs generally. Mahpeykar (2014) and Mahpeykar and Tyler (2014) argue that much of the lack of progress is due to the exclusive focus on the multiple meanings of the particles, without consideration of the polysemy networks of the verb with which the particle is combining. They point out that we know the verbs in these constructions are also highly polysemous; for instance, take has over 25 meanings listed in unabridged dictionaries. Newman (1996) provided a book length analysis of the polysemy of give. Mahpeykar and Tyler (2014) presented an analysis of PVCs which accounts for the semantics of PVCs by examining the semantic contributions of both the verb and the particle in a set of high-frequency phrasal verbs, including turn off, turn out, take off and take out. The study provides a detailed account of the complex semantic networks of these PVCs, showing that the multiple meanings are compositionally formed through the interaction between the polysemy networks of both the verb and the particle. The phrasal verbs selected for Mahpeykar’s (2014) original analysis consisted of a set of frequent and highly polysemous English verb– particle combinations. In this chapter, we present a subset of those PVCs, focusing on the particle out as it combines with the verb turn. The semantic analysis of out is based on Tyler and Evans’s (2003) proposed polysemy network of this spatial particle; the semantic networks for turn were developed specifically in Mahpeykar’s (2014) study and drew largely on the methodology established by Tyler and Evans for the analysis of spatial particles, in conjunction with Langacker’s (1987/2008) analysis of the semantics of verbs. The analysis of these PVCs is based on a set of naturally occurring data randomly extracted from the Corpus of Contemporary American English (COCA; http://corpus.byu.edu/coca). The study by Tyler and Evans (2003) provides an articulated set of linguistic tools with which to analyse lexical polysemy, in particular the polysemy of prepositions. The researchers developed a framework of semantic analysis referred to as the Principled Polysemy Model. In the principled polysemy approach, the analysis of meaning extension relies on recognised principles of cognition such as knowledge of force dynamics and embodied experience (e.g. Johnson, 1987; Lakoff & Johnson, 1980; Mandler, 1992; Sweetser, 1990; Vandeloise, 1991). Tyler and Evans argue that language directly refers to the human conceptual system rather than the ‘real world’. The conceptual structure is largely mediated by how we as humans experience and interact with objects and the spatial-physical world around us; in other words, experience is embodied. Consequently, many of the meanings of prepositions are derived from our embodied experience and conceptualisation of the spatial-physical world. The model relies on cognitive processing including

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pragmatic inferencing and experiential correlation (e.g. Bybee et  al., 1994; Grady, 1997, 1999; Hopper & Traugott, 1993; Johnson, 1999; Lakoff, 1987; Langacker, 1987; Talmy, 2000; Traugott, 1989). CL posits that the meanings of lexical and grammatical items are not fully predictable, with no extra meaning and no gaps. Instead, CL argues that meaning is based on domains of knowledge which are activated by the communicative context and the interlocutors’ background knowledge. The CL approach does not deny the existence of the compositional patterns, but considers them insufficient to explain the multiple, complex interpretations regularly assigned to utterances. The meaning produced from semantic composition of the lexical items and the sentence-level constructions in which they occur provides only some of the resources used in the process of creating and interpreting complex expressions. Other sources include our knowledge of the world, the meaning provided by the context and cognitive mechanisms such as pragmatic inferencing. Nevertheless, CL holds that meaning is extended through regular processes making polysemy networks motivated and open to analysis. In the CL tradition, language is only partially compositional rather than fully compositional (Evans & Green, 2006; Goldberg, 1995; Langacker, 1987, 2008; Taylor, 2002). The polysemy of PVCs in Mahpeykar (2014) is explained as being largely compositional. In this chapter, the PVC turn out will be considered in some detail. The CL analysis used here, which reflects the constructs of embodied experience, micro consequences and experiential correlation, involves diagrams and relies on naturally occurring example sentences. For us, the analysis offers many possibilities for pedagogical materials. Select diagrams and example sentences from the analysis were repurposed for the development of pedagogical materials. For the study reported at the end of the chapter, four PVCs which share the same two verbs and the same two prepositions were presented. The PVCs are turn off, turn out, take off and take out. Mahpeykar (2014) selected these particular PVCs because, based on an examination of the entries in the online dictionaries WordNet and the Cambridge dictionary, as well as the Collins COBUILD Dictionary of Phrasal Verbs (Sinclair et  al., 1994), she determined that the verbs turn and take were highly polysemous, highly frequent and combined with many particles in PVCs. Following Tyler and Evans (2003), she verified that off and out are highly polysemous particles. An examination of the Collins COBUILD Dictionary of Phrasal Verbs (Sinclair et  al., 1994) showed that these particles participated in numerous PVCs, including several involving turn and take (see below for more specifics). COCA was used for investigating the different uses of the phrasal verbs in naturally occurring data. Two hundred instances of each PVC were randomly extracted for a total of 800 tokens. For detailed explanation of the coding scheme, see Mahpeykar (2014).

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For analysing out, initially the polysemy network of these particles proposed by Tyler and Evans (2003) was applied. The proposed semantic networks for this particle were refined in the course of analysing the phrasal verb meanings in the data. Detailed analysis of turn out

This section provides a detailed analysis, based on Mahpeykar (2014), of turn out. First, a brief description of the core and extended meanings of turn is provided. Following this, the semantics of the particle out are explored. Finally, the multiple meanings of turn out are examined. Turn. The WordNet dictionary lists up to 26 separate senses of turn. However, the CL-based analysis of turn raised questions about whether these many senses represented a proliferation of senses that were not truly distinct. Mahpeykar argued that these extended meanings could be subsumed by the concept of ‘change’. In order to avoid a proliferation of meanings related to change, Mahpeykar (2014) determined that postulating a central sense and one distinct extended sense, the Change/Become sense, was sufficiently fine-grained. The Change/ Become meaning subsumes several submeanings: the Change location sense (I turned the soil last spring) and the Become/Change of State sense (e.g. The sky turned blue); the change of state sense has several manifestations – physical change of state (The water turned to ice); emotional/internal change of state (His mood turned grim); change from routine or previous status (She turned to tackling the problem. She turned pro when she was only 15). We decided to maintain Mahpeykar’s single representation of Change to facilitate the development of pedagogical materials. We will return to this issue in the section on future directions. The word turn originates from Old English turnian, which meant to rotate or revolve (Online Etymology Dictionary). After recursive coding of the corpus data, the Rotate Sense was determined to be the core meaning of this verb. Figure  10.1 represents the central sense of turn proposed by Mahpeykar (2014) and adopted in this study. The diagram

Figure 10.1  Central sense of turn

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includes different spatial configurations. One represents the movement of the body around the axis as in I turned around to see him. In this case, the person’s body is both the agent (the cause of the movement) and the patient (the entity undergoing the movement). A second spatial scene involves the person’s hand as the agent and the object undergoing the rotation as the patient. Initially, the object is oriented to the left and, after the rotation is completed, the object is oriented to the right. The initial position of the fist is with the palm up and the fingers showing; the second position is with the palm down and the back of the fist showing. Note that not all instances of turn involve an object. We represent turn in terms of the human body because of the centrality of our embodied experience in establishing meaning. In the figure, the time element is shown by a horizontal arrow and the bolded objects are profiled in the scene. Figure 10.1 illustrates two instances of turning. Note that the action of turning (not illustrated in the figure) may involve the hand turning from thumb up to thumb down (either just the hand itself or the hand holding something) as in I turned the bottle upside down (as in the act of emptying out the contents of the bottle). Additionally, many parts of the human body (heads, legs, ankles) turn. Moving away from the human body, objects such as wheels turn. What is common to all these spatial scenes is that the focus object (F) is moving around an axis, hence there is a rotating movement. The schematic image proposed for turn shows only two specific types of rotation; we argue that they provide a reasonable prototypical illustration. One extended meaning of turn, Change, participates in the phrasal verbs examined for this chapter. The primary Change Sense extends from the central sense through a micro consequence associated with the central Rotate Sense. A ubiquitous consequence of rotating is that the original position does not continuously hold. Even with a relatively anchored F object, such as a knob on a stove, when we turn the knob, the position of the knob changes. A closely related situation involves a change of location of the object being manipulated. In this situation, the object/F does not necessarily return to its original position. For instance, if we are acting on an object, such as the lid of a jar, turning the lid creates a situation in which the lid is very likely to be detached and removed from the jar. Because of the frequent co-occurrence between turning and the F changing location, turn has come to indicate a change of location, as found in the longestablished meaning for turn which reflects the agricultural practice of moving layers of soil so that the lower levels are brought to the surface and the top layer is shifted to a lower level. Another type of change involves the F object undergoing a change of state from State A to State B, as in The water turned to ice. In this scene, the F or the water goes from the state of being a liquid to the state of being a solid object. We would argue that this extended sense likely arises

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from changes that take place when objects are turned. If we change position by turning our bodies, we may experience change in the environment which is often accompanied by change in the self. For instance, if we are sitting outside with the sun behind us and we turn our head to face the sun, we will receive more sunlight on our face. And if this is too long, we get sunburnt. Turning or changing the position of objects can also result in a change of state in the object. For instance, when cooking we turn the food in the pan so that both sides (as in two sides of a hamburger) are cooked. In this case, the object goes through a change of state as a result of being physically turned. An unavoidable consequence of turning a cooking entity is a change of state in that entity. Through pragmatic inferencing, change of state became an independent meaning associated with turn, as in The cookies turned light brown, even when rotating is not part of the meaning. So far, we have illustrated physical change of state. It is important to recognise that ‘change of state’ can also refer to an internal change of state concerning emotions or thinking, for instance, The little girl turned from sullen to bubbly; The mood of the crowd turned restless. Finally, change of state can indicate a change from a previous status or a change from routine. This is exemplified in My mother turned 97 in July; Iverson turned pro after his freshman year of college. The following examples provide minimal pairs, which illustrate the different meanings of turn: the core Rotate Sense and the extended Change Sense: (1) Turn your head to the left/Turn the page (core Rotate Sense) Extended, Change sense: (2) Change of location: My husband turns the soil every spring. (3) Change of State: Physical: The water turned to steam. (4) Change of State: Emotional: With the wrong word, he could turn petulant. (5) Change of State: Change from the previous status: The young golfer turned pro this year. Out. According to Tyler and Evans (2003), out designates a spatial relationship in which the F is located external to a G or locating object that is construed as a container. The G is conceptualised as a threedimensional, bounded object which possesses an interior, a boundary and an exterior. Human interaction with bounded Gs has functional consequences, the most prominent one being the notion of containment. The central meaning of out designates a relation in which the F is exterior to a bounded G. While the interactive relation between the F and G associated with in is ‘containment’, out denotes the interactive relation between

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Figure 10.2  Central sense of out (Tyler & Evans, 2003) Table 10.1  Tyler and Evans’s (2003) analysis of out Clusters

Senses

The Location Cluster

(1) Not In Situ Sense: The F is not in its default location where it spends extended periods of time, such as the home or office, e.g. She’s out (for lunch) vs She’s in every afternoon this week. (2) No More Sense: There is no longer any of F in the container so there is no more of the F available, e.g. Do we have any milk? No, we’re out. A micro consequence: when all the F in the container is removed, the act of removal is completed.

The Vantage Point Exterior Cluster

(3) The Visibility Sense: The F is located exterior to the G and the vantage point is also located exterior to the bounded G. Hence, when the F is in an out position, the F becomes visible, e.g. The moon is out. Additionally, when the F is in an out position, the F is often available. The Availability Sense: The waiter set plates out for the customers. (4) The Knowing Sense: The F is visible and as a consequence it becomes known, e.g. They found out what was making the strange sounds when they pulled a kitten out of the bag. They figured out the truth.

the F and G of ‘non-containment’. The central sense for out is illustrated in Figure 10.2. The F or the object in focus is represented by a dot, the square is the bounded G or container. The dot is not inside the square. The various senses of out are classified under clusters of meaning derived from the central sense. Table  10.1 illustrates a select set of the clusters of senses and the distinct senses proposed for out which were used in the analysis of the phrasal verbs in this study; these represent a subset of the senses identified by Tyler and Evans (2003). The examples are from Tyler and Evans (2003). In addition, Tyler and Evans (2003) discuss the extended Reflexive Sense in which the G is also the F and the F comes to be located exterior to its original boundary, as in The puddle spread out across the counter; The peacock spread out its tail. Not In Situ Sense: Entities often remain for extended periods of time in a default container. In this extended meaning, the F is not in the default location. One of the types of containers we interact with most frequently is the house in which we live or the building in which we work. A common example of the Not In Situ Sense is: Someone let the dogs out. The dogs were out, roaming around the neighbourhood. No More Sense and Completion Sense: There is no longer any F in the container so there is no more of the F available, e.g. Is there any

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milk? No, we’re out; We’re out of milk. The emptying of a container regularly involves an intentional action or process by which the container becomes empty. When the container reaches the empty or no more stage, an unavoidable micro consequence is that the action of emptying is complete. Tyler and Evans (2003) provide the example: After unplugging the tub, the water drained out. A consequence of all the water being out, with respect to the tub, is that the process of draining the water is complete. As a result of this recurring consequence, out has developed a sense of completion which is exploited in the Completion Sense of turn out, as in: Much to our relief, the fundraiser turned out to be very successful. The Visibility Sense: If the F is located interior to the container and the vantage point is exterior, the actor is often not able to see the F/contents of the container. In contrast, when the F is located exterior to the G and the vantage point remains located exterior to the container, the F becomes visible, e.g. The sun is out. The Availability Sense: If an entity is located exterior to the container and thus visible, it often becomes available, e.g. The hostess set drinks out for the guests. The Knowing Sense: An experiential correlation of being able to see an object is to know about that object and through pragmatic strengthening the Knowing (about) sense has become associated with out. This sense draws on the well-established primary metaphor ‘seeing is knowing’, which is based on the experiential correlation between being able to see something, such as seeing the sun, and knowing it is the case that the sun is shining. Being located outside the container, the F is visible and as a consequence it becomes known in certain contexts. The correlation of an F being out and knowing has given rise to out having an independent knowing meaning, e.g. The truth will out. The act of outing someone means making private information about that person known to a larger public. The following section presents the analysis for target meanings associated with turn out. Turn out. Mahpeykar (2014) examined six different meanings associated with turn out. The meanings and example sentences from COCA are listed in Table 10.2. Analysis of the multiple meanings of turn out

Central Sense. In its central sense, turn out denotes a spatial meaning of an F (an object) rotated in an outward direction. The meaning of turn is the central Rotate Sense, with an emphasis on changing position; the meaning of the particle is the extended Reflexive Sense in which the F and the G are the same entity and the F comes to be located exterior to its original boundary. Figure 10.3 represents the central sense of turn out

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Table 10.2  Meanings and example sentences for the PVC turn out Meanings of turn out

Example sentences

Central sense

Kneel on your right knee, left leg turned out so your inner thigh is facing forward (context: exercise)

Extended senses Deactivate

Sleep well. I’ll turn the lights out.

Participate

Today, most of New York’s elected officials turned out to support the President.

Discover

I called the phone number by the door and it turned out Mrs Angela was at a café across the street enjoying a beverage.

Produce

This restaurant turns out superb food….

Outcome

The trip turned out great, with plenty of grizzly sightings, spectacular tundra camping and the conception.

Figure 10.3  Central sense of turn out

proposed in this study. The meaning of turn is shown by a hand changing the orientation of the object. The meaning of out is shown by the outer limits of the G extending into its new position, represented by the bolded square. The time element is depicted by an arrow and the bolded objects are profiled in the scene. The meaning of turn out is shown by a hand rotating an object in an outward position or direction. Note that the object itself is optional and represented by dotted lines. Another example of the central sense of the phrasal verb is Turn out your pockets. Extended senses of turn out. Applying the CL tools to the corpus data yielded five distinct, extended senses of the PVC (see Table 10.2). Deactivate. This use denotes that the F object, whose functioning relies on a source of power, has become deactivated. The meaning of the verb participating in this use is the central Rotate Sense and the meaning of the preposition is the extended No More/Completion Sense. The

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meaning of the PVC in this use is related to our experience with switches or knobs by which we control the functioning of devices, particularly lights. Turning the knob in a certain direction deactivates the power. This sense is likely related to historical activities of turning water gates or steam valves which could stop the flow of water or steam (and thus the flow of energy). The corpus data for this PVC shows that present-day instances of turn out in the Deactivate Sense involve only lights as the F. The following example demonstrates this sense of turn out: Go into the kids’ room, turn the lights out and wait there until I come get you. Participate. This sense denotes that the F (actor) is changing from a routine activity by joining an event outside of their default locations (including their homes or workplaces). The meaning of the verb is the extended Become/Change (Change from Routine) sense and the meaning of the particle is the extended Not in Situ Sense. As previously noted, in the Not in Situ Sense, the F is not in its default location where it usually spends time. The combination of Change (Change from Routine) + Not in the Normal Location produces the meaning of involvement in a nonroutine activity outside the home. In most cases, the F is a mass or group of people intentionally showing up at a particular location in order to participate in an event. The following example demonstrates this use of turn out: Thousands of people turned out for the Pope’s visit. Be in a New Knowledge State/Discover. In this use, the meaning of turn is the extended Become/Change (State of Knowledge) Sense and the meaning of out is the extended Knowing Sense. The meaning of turn in this use is related to our embodied experience of physically rotating our bodies or heads and the micro consequence of learning something new. When we turn around, a new visual field becomes available to us, and consequently our knowledge of the environment increases. We go from a state of not having knowledge to a state of knowing. In addition, the experience of physically turning the soil (digging in the soil such that the lower layer is moved to the surface) and finding previously hidden objects seems to motivate this use of turn. As discussed above, an experiential correlation of being able to see an object (for instance, when an object is in an out position) is to know about that object and the Knowing Sense has become associated with out. The combination of the verb and the particle subsumes the overall meaning of discovering some information about an entity or a situation. In the corpus, most uses of turn out appeared in cleft constructions with ‘it’, as evident in the following example: It turned out that the management was trying to integrate the apartments. The speaker is indicating discovery or going from a state of not knowing to a state of knowing about the management’s actions. Produce. The meaning of the verb in this use is the extended Become/ Change (Physical State) Sense and the meaning of the preposition is the

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extended Availability Sense. Here, the change has to do with changing raw materials into a finished product. The combination of the meaning of the verb and the preposition subsumes the overall meaning of creating an entity which is available for public use. As noted before, a consequence of the F being out of the G is that it can become available and accessible. This type of experience has given rise to the Availability Sense of out. Turn out denotes a sense of the F changing state and becoming accessible to the user, as in the following example: The factory turns out shoes at an extraordinary rate. Outcome. This use denotes a sense of outcome or result associated with an F (event or object), after the F has gone though some process. This use draws on the extended Become/Change of State Sense of turn and the extended Availability Sense of out. We hypothesise that this sense arises through a frequent micro consequence of the action of turning. Many times, our experience with rotating objects involves reaching a particular result such as opening or closing, tightening or loosening. Examples of this use include: Turn the lid or He turned the key and opened the door. In such cases, a consequence of turning the object results in achieving an outcome. This meaning combines with the Availability sense of out, which includes accessibility to knowledge, to create a composite meaning of achieving an outcome and a new knowledge state resulting from that outcome. The following example demonstrates this sense of turn out: When the first piece turned out amazingly well, I continued to buy dryer duct and other home improvement items. The Pedagogical Treatment Overview

We find Mahpeykar’s analysis, which highlights the systematic, compositional nature of the semantics of PVCs, compelling. In this section, we consider an attempt to apply this analysis to a pedagogical treatment. We used the insights stemming from embodied experience and compositionality to present the multiple meanings of a select set of phrasal verbs, especially turn out, turn off, take out and take off. We represented all subtypes of ‘change’ associated with turn as Become/Change. In addition, the network for turn out was represented as a flat structure with all five extended meanings related to the central sense. We did not attempt to motivate this aspect of the presentation. Traditional textbooks present the meanings of PVCs as arbitrary and best mastered through memorisation. Our overarching goal was to create an effective, engaging pedagogical treatment which presents a systematic, motivated analysis of the multiple meanings of PVCs. The idea was that if learners became more aware of the motivation behind the polysemy of verbs, prepositions and PVCs, they would be better able to retain the

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meanings when they encountered various uses of PVCs. In accomplishing this, our first goal was to introduce the link between embodied experiences and multiple meanings associated with lexical units. We sought to represent polysemy as a systematic product of human interactions with the world. We adapted the diagrams developed by Mahpeykar (2014) for the verbs and by Tyler and Evans (2003) for the particles. We were also committed to the Vygotskian notions of scaffolded learning and introducing complex information in small increments. In line with scaffolded presentations, our materials start by investigating the multiple meanings associated with the targeted verbs, then the targeted prepositions. Next, explicit explanations and examples of the multiple meanings of two phrasal verbs are presented. The subsequent materials introduce the multiple meanings of the two other phrasal verbs. We determined that this sequencing would have the effect of first highlighting the independent meanings of out, off, turn and take. Later, the independent contributions of the components are re-emphasised as the multiple meanings of the phrasal verbs are explained. For the purposes of this chapter, we will only consider the materials developed for turn out. The pedagogical presentation: Converting the theory into a pedagogical presentation

The materials on out focus on human experiences of containment and non-containment. We explore how the experiential correlations concerning non-containment support the multiple uses of out. We begin with containers and the important consequences of objects being in an ‘out’ relationship versus an ‘in’ relationship. Pedagogical materials for out: Component/concept to be presented:

What is a preposition? Lead to meaning 1: Out of location

Explanation:

In English, we have prepositions. They are a special language feature that describes spatial relations between a Focus object and a Grounding or locating object. There are two key English prepositions we use to talk about spatial situations when the locating object is a container – in and out.

Demonstration:

Quick manipulation of a small purse (container) holding money. ‘The dollar is in the purse. In this example, the dollar is the focus object. It’s what we are more interested in. The purse is the locating object, and it is a container. The purse is holding the dollar’. Instructor removes the dollar. ‘I took the dollar out of the purse. The dollar is still the focus object, and the purse is the locating object. But now the dollar is not held by the purse. Out signals that the focus object is NOT contained by the locating object’.

Component/concept to be presented:

One word/form with many meanings. Experiential correlation and micro consequences. How do the many meanings develop? Lead to meaning 2: Visible and Available

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Explanation:

Containers are useful for humans. For instance, they help us hold things and carry things. There are many additional consequences that go along with a focus object being contained and other consequences that go along with a focus object not being contained. When things are in a container, they are generally hidden from view. Since we don’t have x-ray vision, we can’t see the things inside the container. For instance, looking at the purse doesn’t tell us for sure what is in it. Even if we guessed there is money in the purse, we couldn’t know how much money there is. (Take out some other small object.) You often do not know with certainty what is inside the container. In addition, the contents are usually not immediately available. For instance, we can’t spend the money if it’s in the purse. In contrast, when the entities are in an ‘out’ position, they are visible and the observer knows that these particular entities exist. So, knowing about the contents is one important consequence of being out. A second consequence is that the contents are more available. For instance, if we want to pay for something at the store, we have to take the money out of the purse.

Demonstration:

The instructor holds up a colourful metal container in front of the room and asks if the students know what is in it. No one knows what the contents are. Then the container is opened and passed around. Everyone is encouraged to take out a chocolate. Emphasise that the chocolate, being in an ‘out’ position, is now available to them. They are invited to eat it.

Follow-up explanation:

Because there is such a strong association between the contents (say the chocolate) being in an out position and the contents being available, out has developed a special meaning of ‘be available’. For instance, ‘The Black Panther movie is finally out’. This means that the movie is now available for people to watch.

Component/concept to be presented:

Lead to meaning 3: No more/Completion

Explanation:

There are other important, everyday consequences for us when we interact with objects in an out position. There is an important link between emptying out all the contents, and the end of the act of emptying.

Demonstration:

Instructor drinks from a water bottle until the bottle is emptied. A second instructor asks if there was more water and the reply is, ‘Sorry, we’re out. There is no more water’. Note when all the water (contents) is in an ‘out’ position, there is no more water in the bottle. Also, when all the contents are in an out position, the emptying process is completed. The instructor asks (the rhetorical question), ‘Is X still drinking?’ and replies, ‘No, the drinking is completed’. The demonstration is repeated with a box of cereal, ‘Sorry, there is no more cereal. We are out’, ‘Is X still pouring out the cereal? No, the pouring is completed’.

Follow-up explanation:

Because consequences (the act of emptying being completed when all the contents are out of the container) are so strongly linked to all the contents being in an out position, the word out has developed an additional meaning of ‘no more’ or ‘completion’. For instance, ‘The store is out of my favourite cereal’.

Supportive materials: Provide additional examples through PowerPoint slides. For example, one slide emphasises the Completion Sense (Figure 10.4).

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Figure 10.4  PowerPoint slide illustrating the Completion Sense

The presentation includes the following meanings of out, all of which arise from the consequences of objects being in an out position: (1) Be outside the home or usual place: One of the most common types of containers we interact with is a house or place of work. Out has developed a meaning of being outside the home or workplace. Example: See you later. I’m going out! Let’s go out for a change. (2) Available: The new Hunger Games movie is out now. (We wanted to see the movie last week, but it wasn’t available. Now it is available, and we can see it in the theatre.) (3) No more: When all the contents have been removed, they are all out of the container and there are no more contents. We’re out of milk. This sense is further extended to imply the completion of a process, when the milk is all poured out, the process of pouring is completed too. Supportive materials: To reinforce the notion that out has developed several meanings, the PowerPoint slideshow used diagrams of the meaning network (Figure 10.5). Pedagogical materials for turn: Component/concept A number of actions are labelled by the verb turn. Understanding to be presented: the word turn through our embodied experience and the micro consequences of change connected to the movement of rotating. Explanation:

People can turn in several ways: (1) movement of the whole body, Turn around. I want to show you something; (2) rotating a lid, I turned the lid of the jar to open it; and (3) moving an object to an upside-down position, I turned the bottle in my hand.

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Demonstration:

Ask the students to participate in the various acts of turning. For each act of turning, discuss the (micro) consequences of turning. For instance, ask the students to stand up and face the front of the room. Then ask, what do you see? Next, give the command ‘Turn around’ and ask, ‘What do you see?’ Students respond with a range of observations, noting that they were seeing something different after they turned around. Emphasise that these embodied experiences of turning result not just in rotating their bodies or their heads, but also a change in perspective and a change in knowledge. As they change their perspective, they gather new information about the room and the other people in the room.

Follow-up explanation:

This kind of experience, which links humans turning to change of perspective and knowledge state, has resulted in turn developing the meaning of Change or Become. For instance, ‘Her hair turned white from fright’.

Demonstration:

Turn the lid on a jar. Once the lid is loosened, remove it. The teacher says, ‘Now we can open the jar’. The container went from being closed to being open. Turning the lid results in a change in the state of the jar. There is a change in accessibility to inside the jar. Ask a student to come to the front of the room, turn the lid and open the jar (which contains cookies). When they take off the lid, the teacher says, ‘Look in. What’s in the jar? Take one out and help yourself!’ There is an important link between turning the lid and a change in availability of the contents of the jar. What is inside the jar has changed to become available.

Figure 10.5  PowerPoint slide of the meaning network for out

Supportive materials: Follow the demonstrations by a slide show which presents the meaning network for turn using slides with lots of example sentences and supporting visuals. The presentation includes the diagram shown in Figure 10.6. Accompany the diagrams and visuals with the following remarks: ‘There are many kinds of turning. All involve rotating around an axis’. ‘Turning a pancake results in change. Before you turn a pancake, it is only cooked on one side. Turning the pancake allows it to be cooked on both sides. It changes from uncooked batter to a cooked pancake’. The link between ‘turning’ and ‘change’ results in turn developing a meaning

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Figure 10.6  Slide showing the meaning network of turn

of change that no longer involves physical rotation. Here are some uses of turn which mean different types of change: ‘The change of state of the object from state A to state B: The water turned to ice. This is an example of a meaning that is different from the physical act of revolving or turning. Here, the water goes from the state of being a liquid to the state of being a solid object. There are many types of change. When the water turns to ice, we’re talking about change of a physical state; when the man’s face turns angry, we’re talking about a change of emotional state; and when we say “The tennis player turned pro”, we’re talking about a change from the status quo (or from previous routine) to a new status or routine’. Pedagogical materials for turn out: Component/concept to be presented:

(1) When we bring a verb and a preposition together, a new form is created, a phrasal verb. The phrasal verb combines information from both the verb and the preposition. (2) Often the information or meaning comes from an extended meaning of the verb and an extended meaning of the preposition.

Explanation:

When a verb and a preposition are put together, they can form a new construction called a phrasal verb, such as turn out. We’ve just talked about several meanings associated with the verb turn and with the preposition out. Any one of the meanings from the verb can combine with a meaning from the preposition to make up meanings for turn out. For instance, ‘Many people turned out to see the royal baby’. This means something like, many people left their homes or workplaces to go to a special area to see the royal baby. The people participated in a special event. Here, turn out gets its meaning from an extended meaning of turn, which means ‘Change from the routine’ and an extended meaning of out, which means ‘Be outside the home or workplace’. The context is a special occasion. Most phrasal verbs have several meanings. We just saw that turn out has a ‘participate’ meaning. Let’s think about another meaning for turn out. Consider the use of turn out in the sentence, The three identical strangers turned out to be triplets who were separated at birth. This sentence means something like, The three strangers who looked alike discovered they were brothers who were separated at birth. New knowledge (that they were brothers) became available to them. This meaning comes from an extended meaning of turn meaning change of state (here a knowledge state) and an extended meaning of out, meaning available. The combined meaning is ‘have new knowledge available’ or ‘discover’

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Figure 10.7  Slide showing the meaning contributions of turn and out to the Discover Sense

Figure 10.8  Meaning network for turn out

Supportive materials: The diagram shows how turn and out contribute to this meaning (Figure 10.7). To reinforce the multiple meanings for turn out, a PowerPoint slide shows the meaning network for turn out (Figure 10.8). An Exploratory Study Overview

The materials that we developed present a very different approach to teaching PVCs than found in standard English as a second language (ESL) textbooks. To begin to consider the hypothesis that theory-based materials could provide effective instruction, we carried out an exploratory study. The intervention took place over three consecutive days, with each session lasting 75 minutes, for a total of a little over 3 hours of instruction. On Day 1, the participants took a short pre-test; on Day 3 the participants took a short post-test. Three weeks later, the participants took a delayed post-test. The instructors were the first and second authors of this chapter.

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Design of the study

The participants were enrolled in two, low intermediate classes in an intensive English programme at a major US university. The participants were placed in the classes based on internal placement exams. Eleven participants received CL-based instruction on the multiple meanings of the four PVCs; 14 received non-cognitive instruction. All participants took a pre-test, immediate post-test and delayed post-test; each test item included a ‘guessed’/’didn’t guess’ confidence rating. The tests each included 24 multiple-choice items: 16 target items and 8 filler items. Each item consisted of a short passage followed by four possible choices. Three versions of the test were constructed. No participant saw any version more than once. The three tests were counterbalanced so that one-third of the participants saw Version A as the pre-test, Version B as the immediate post-test and one-third Version C as the delayed post-test and so forth. The pedagogical sequence was as follows: Day 1: Pre-test; Out, Off, Turn Day 2: Take, Turn out, Turn off Day 3: Take out, Take off; Post-test Three weeks later: Delayed post-test Results

The participant pools were too small to perform reliable inferential statistics. Accuracy results showed that both groups improved, with the CL group having a slight advantage (CL average gain scores were 1.27 points, non-cognitive were 0.9) (Table 10.3). The ‘sureness’ scores also showed an increase, with the non-cognitive group having a gain of 22.60% from pre-test to post-test and the cognitive group having a gain of 61.57%. While the gain score for the cognitive group might appear particularly impressive, it is important to note that the cognitive group started with a much lower score. We do not know why this score was so much lower for the cognitive group. The gain for the cognitive group was maintained with a slight increase on the delayed post-test; the gain for the non-cognitive group dipped slightly (Table 10.4). In sum, the results generally went in the hypothesised direction, but the accuracy differences between the two groups were not as robust as we anticipated. Table 10.3  Mean test accuracy scores Group

n

Pre-test

Post-test

Delayed post-test

Non-cognitive

14

11.85 (1.70)

11.43 (2.90)

12.79 (1.37)

Cognitive

11

10.82 (3.22)

11.82 (3.12)

12.09 (2.21)

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Table 10.4  Percentage of sure/did not guess answers Group

n

Pre-test

Post-test

Delayed post-test

Control

14

56.65 (35.35)

79.25 (15.95)

76.86 (24.86)

Cognitive

11

13.34 (17.68)

74.91 (33.28)

75.37 (34.12)

Thoughts for Future Directions

We think there may be a number of factors contributing to the weak results. The amount of time spent on the intervention was less than 3 hours of instruction. The CL group had many new concepts to learn and the 3 hours of concentrated instruction may not have been sufficient. Perhaps shorter, less concentrated instruction, spread over several weeks would have been more effective. Alternatively, one could argue that PVCs are sufficiently complex that learners will only be able to make them part of their language use if they are presented within a fully developed, CLbased instructional programme. In such a programme, tenets such as the embodied nature of meaning and polysemy would be continually recycled and PVC instruction would be an integrated part of this overall perspective. The learning of PVCs would be gradual and highly scaffolded. We can imagine that this would be an ideal learning environment. Of course, such a CL-inspired programme would only be possible with a well-informed group of instructors, supported by a carefully developed curriculum and appropriate materials. However, in the absence of the ideal, we would argue that exploring the effectiveness of CL-based instruction that is spread over several weeks, or even an entire semester, is a reasonable next step. Several CL-inspired studies show that learners can make measurable progress in their understanding and use of complex language, even when the particular target phenomena are the only ones presented from a CL perspective. Tyler (2012) reports numerous, successful CL-based studies tackling the polysemy of prepositions, English modal verbs and dative alternations. These interventions all consisted of longer periods of instruction than the present study. Dolgova-Jacobsen (2016) successfully taught complex conditional structures, widely recognised as a particularly difficult area of English, to university-level learners using cognitive blending theory. The instruction was spread over several weeks. It represented the only CL-based component of the curriculum. At the end of the intervention, students were able to demonstrate substantially increased accuracy in their use of conditional constructions. Kissling et  al. (2018) successfully applied Tyler and Evans’ principled polysemy model to analyse and teach the notoriously difficult polysemy networks of Spanish por/para. The materials consisted of PowerPoint slideshow presentations, rather similar to those used in the present study, which used engaging visuals to illustrate the multiple meanings of the prepositions, as well as visual representations of the polysemy networks. The instruction was delivered in short mini-units spread over an entire

246  Usage-Based Dynamics in Second Language Development

semester. The students showed robust improvement in their recognition and accurate use of the multiple meanings of both prepositions. Indeed, this research represents the only successful teaching intervention of Spanish por/para reported in the literature. Both these studies demonstrate that CL-inspired instruction of complex linguistic phenomena, even in the absence of other CL-based instructional units, can be successful in a less concentrated, more longitudinal format. At least one explanation for the facilitative effect of longitudinal intervention is that the learning of these more complex structures is dynamic and non-linear in nature (Langacker, this volume; Verspoor, 2017). Liamkina and Ryshina-Pankova (2012) also demonstrated the effectiveness of CL-consistent/functional explanations for polysemous German forms. They discuss a set of instructional guidelines quite similar to the methods implemented in the present study, such as introducing the central or prototypical meaning first and then progressing to the less central meaning and consistently explaining the link between the different meanings or functions. Additionally, they advocate using authentic language to demonstrate the motivated links between the various meanings; our study was based on authentic language drawn from the COCA corpus. Liamkina and Ryshina-Pankova also suggest extensive scaffolding, which includes opportunities for the learners to discover new meanings facilitated by metalinguistic discussions about the target form and related meanings. The time constraints of our study precluded this degree of scaffolding, but we recognise that the study would have benefited from more scaffolding and discovery opportunities. Upon reviewing the materials, we have determined that presenting the network of the PVC for turn out in a flat configuration might have masked the contributions of the polysemy network of the verb. We adopted this non-proliferated analysis of change as it was part of Mahpeykar’s (2014) original analysis. Developing the materials and explaining the several submeanings of change to the participants, we more fully realised the distinctions among the types of change. The result of representing the multiple types of change as one sense may have been that participants fell back on the strategy of memorising the multiple meanings associated with each PVC rather than developing a more compositional approach. Finally, a major point was to use the CL analysis to create effective teaching materials. In carefully examining the materials, we noticed that the key diagrams for turn (and therefore for representations of the phrasal verb meanings) and turn out are potentially confusing. We assumed that the diagrams would be a major boon for the students. However, if they did not make sense to them, they may have experienced an additional learning burden as they sorted through the information from the explanations and how that connected to the diagrams. If this were the case, the systematicity that we were stressing may have been masked. In other words, the participants may have had to rely on memorisation more than we expected. One way this concern could be examined would be by going

Getting Out the Word on Phrasal Verbs  247

through the materials with individual learners and gathering information on their interpretation of the figures and explanations. Stimulated recalls after each test might also yield valuable insights. References Bolinger, D. (1971) The Phrasal Verb in English. Cambridge, MA: Harvard University Press. Brugman, C. and Lakoff, G. (1988) Cognitive typology and lexical networks. In S. Small, G. Cottrell and M.T. Tanenhaus (eds) Lexical Ambiguity Resolution (pp. 477–507). Palo Alto, CA: Morgan Kaufman. Bybee, J., Perkins, R. and Pagliuca, W. (1994) The Evolution of Grammar: Tense, Aspect and Modality in the Languages of the World. Chicago, IL: University of Chicago Press. Celce-Murcia, M. and Larsen-Freeman, D. (1999) The Grammar Book: An ESL/EFL Teacher’s Course. Boston, MA: Heinle & Heinle. COCA (online) See http://corpus.byu.edu/coca/ (accessed 21 March 2012). Deane, P. (2005) Multimodal spatial representations: On the semantic unity of over. In B. Hampe (ed.) From Perception or Meaning: Image Schemas in Cognitive Linguistics (pp. 235–82). Berlin: Mouten de Gruyter. Dirven, R. (2001) English phrasal verbs: Theory and didactic application. In M. Putz, S. Niemeier and R. Dirven (eds) Applied Cognitive Linguistics (Vol. II): Language Pedagogy (pp. 3–28). Berlin/New York: Mouton de Gruyter. Dolgova-Jacobsen, N. (2016) The best of both worlds: Combining cognitive linguistics and pedagogic tasks to teach English conditionals. Applied Linguistics 39 (5), 668– 693. doi: 10.1093 /applin/amw030 Evans, V. and Green, M. (2006) Cognitive Linguistics: An Introduction. Edinburgh: Edinburgh University Press. Fraser, B. (1976) The Verb-Particle Combination in English. New York: Academic Press. Gibbs, R. (1994) Poetics of the Mind. Cambridge: Cambridge University Press. Goldberg, A. (1995) Constructions: A Construction Grammar Approach to Argument Structure. Chicago, IL: University of Chicago Press. Goldberg, A. (2006) Constructions at Work: The Nature of Generalization in Language. Oxford: Oxford University Press. Grady, J. (1997) Foundations of meaning: Primary metaphors and primary scenes. Unpublished doctoral dissertation, University of California, Berkeley. Grady, J. (1999) A typology of motivation for conceptual metaphor: Correlation versus resemblance. In R. Gibbs and G. Steen (eds) Metaphor in Cognitive Linguistics (pp. 79–100). Philadelphia, PA: John Benjamins. Hopper, P.J. and Traugott, E.C. (1993) Grammaticalization (2nd edn). Cambridge: Cambridge University Press. Johnson, M. (1987) The Body in Mind: The Bodily Basis of Meaning, Imagination, and Reason. Chicago, IL/London: University of Chicago Press. Johnson, C. (1999) Metaphor versus conflation in the acquisition of polysemy: The case of SEE. In M.H. Hiraga, C. Sinha and S. Wilcox (eds) Cultural, Psychological and Typological Issues in Cognitive Linguistics (pp. 155–169). Amsterdam: John Benjamins. Kennedy, A.G. (1920) The Modern English Verb–Adverb Combination. Stanford, CA: Stanford University Press. Kissling, E., Tyler, A., Warren, L. and Negrete, L. (2018) Reexamining por and para in the Spanish foreign language intermediate classroom: A usage-based, cognitive linguistic approach. In A. Tyler, L. Huang and H. Jan (eds) What is Applied Cognitive Linguistics? Answers from Current SLA Research (pp. 229–256). Berlin: Mouton de Gruyter. Lakoff, G. (1987) Women, Fire and Dangerous Things: What Categories Reveal about the Mind. Chicago, IL/London: University of Chicago Press. Lakoff, G. and Johnson, M. (1980) Metaphors We Live By. Chicago, IL/London: University of Chicago Press.

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Langacker, R. (1987) Foundations of Cognitive Grammar (Vol. I): Theoretical Prerequisites. Stanford, CT: Stanford University Press. Langacker, R. (2008) Cognitive Grammar: A Basic Introduction. Oxford/New York: Oxford University Press. Liamkina, O. and Ryshina-Pankova, M. (2012) The grammar dilemma: Teaching grammar as a resource for making meaning. The Modern Language Journal 96 (2), 270–289. doi:10.1111/j.1540-4781.2012.0133_1.x Lipka, L. (1972) Semantic Structure and Word-Formation: Verb-Particle Constructions in Contemporary English. Munich: Wilhelm Fink Verlag. Linder, S. (1981) A lexico-semantic analysis of English verb-particle constructions with UP, and OUT. Unpublished doctoral dissertation, University of California, San Diego. Live, A. (1965) The discontinuous verb in English. Word 21, 428–451. Mahpeykar, N. (2014) A principled cognitive linguistics account of English phrasal verbs. Unpublished doctoral dissertation, Georgetown University. Mahpeykar, N. and Tyler, A. (2014) Figuring out the gaps: A principled cognitive linguistic account of the semantics of English phrasal verbs. Language and Cognition 7, 1–35. Mandler, J. (1992) How to build a baby II: Conceptual primitives. Psychological Review 99, 587–604. Newman, J. (1996) Give: A Cognitive Linguistics Study. New York: Mouton de Gruyter. Online Etymology Dictionary (online) See http://www.etymonline.com/ (accessed 20 April 2012). Ortega, L., Tyler, A., Uno, M. and Park, H. (eds) (2016) The Usage-Based Study of Language Learning and Multilingualism. Washington, DC: Georgetown University Press. Rudzka-Ostyn, B. (2003) Word Power: Phrasal Verbs and Compounds: A Cognitive Approach. Berlin/New York: Mouton de Gruyter. Sinclair, J. et  al. (eds) (1994) Collins COBUILD Dictionary of Phrasal Verbs. London. Harper Collins Publishers. Sweetser, E. (1990) From Etymology to Pragmatics: Metaphorical and Cultural Aspects of Semantic Structure. Cambridge: Cambridge University Press. Talmy, L. (2000) Toward a Cognitive Semantics (Vol. II). Cambridge, MA: MIT Press. Taylor, J. (2002) Cognitive Grammar. Oxford: Oxford University Press. Traugott, E.C. (1989) On the rise of epistemic meanings in English: An example of subjectification in semantic change. Language 65 (1), 31–55. Tyler, A. (2012) Cognitive Linguistics and Second Language Learning: Theoretical Basics and Experimental Evidence. New York: Routledge. Tyler, A. and Evans, V. (2001) Reconsidering prepositional polysemy networks: The case of over. Language 77, 724–765. Tyler, A. and Evans, V. (2003) The Semantics of English Prepositions: Spatial Scenes, Embodied Meaning and Cognition. Cambridge: Cambridge University Press. Tyler, A., Huang, L. and Jan, H. (eds) (2018a) What is Applied Cognitive Linguistics? Answers from Current SLA Research. Berlin: Mouton de Gruyter. Tyler, A., Ortega, L., Park, L. and Uno, M. (eds) (2018b) Usage-Based Inspired L2 Instruction: Researched Pedagogy. New York: John Benjamins. Vandeloise, C. (1991) Spatial Prepositions: A Case Study in French. Chicago: University of Chicago Press. Verspoor, M. (2017) Complex Dynamic Systems Theory and L2 pedagogy. In L. Ortega and Z. Han (eds) Complexity Theory and Language Development. In Celebration of Diane Larsen-Freeman (pp. 143–162). Amsterdam: John Benjamins. https://doi.org/ 10.1075 /lllt.48.08ver. Verspoor, M. and Tyler, A. (2009) Cognitive linguistics and its application to second language teaching. In W. Ritchie and T. Bhatia (eds) New Handbook of Second Language Acquisition (2nd edn, pp. 160–77). Oxford: Elsevier.

11 The Icing On the Cake? Effects of Explicit Form-Focused Instruction after Two Years of Implicit EFL Learning Leslie Piggott, Elena Tribushinina and Rick de Graaff

This study is part of a larger project in which explicit form-focused instruction (FFI) and practice concerning grammar was reduced and delayed for two years in the foreign language (FL) classroom. Participants are two cohorts of secondary school children learning English as a foreign language (EFL) (n = 393). In the present study, we investigated if reducing and delaying explicit FFI would affect performance on a common grammar test. One cohort received traditional explicit FFI with metalinguistic information and grammar exercises (the explicit group). According to the participating teachers’ self-report, approximately 37% of classroom time was spent on grammar instruction and practice. The other cohort (the implicit group) received predominantly implicit FFI without any metalinguistic information and all grammar exercises were removed from the course book materials. In the last seven weeks of the second school year, the implicit group received seven classes of explicit grammar instruction and practice (total of approximately 6% of classroom time). Grammar tests were administered in a pre-, immediate, post and delayed post-test design. The implicit group was tested before the grammar course, then both groups were tested at the end of the second year and again four months later. The results of multilevel modelling (MLM) showed that the implicit group improved significantly between the pre-test and the immediate post-test. The implicit and explicit groups scored equally well on the immediate and delayed post-test. This study shows that after a (longer) period of implicit FFI only, minimal explicitness and practice are sufficient to score well on a common grammar test. 249

250  Usage-Based Dynamics in Second Language Development

Introduction

Explicit grammar teaching and testing holds a central position in many mainstream foreign language (FL) classrooms. Commonly, a language teacher explains grammar rules after which the students make assignments practicing these rules and eventually the students are expected to be able to use the grammatical structures in language production. This teaching approach is in stark contrast with the fundaments of dynamic usage-based (DUB) theory. From a DUB perspective, grammar is not the foundation upon which the remainder of the language is built, nor does it drive the language (Verspoor, 2017). A DUB-inspired approach requires frequent and repeated exposure to authentic FL input and any focus on grammar is ideally implicit (Lightbown & Spada, 2013). Developments in language pedagogy align with these ideas behind DUB language learning, such as content language integrated learning (CLIL) and task-based language teaching (TBLT). Also Verspoor and Hong’s (2013) DUB-inspired film and language integrated learning (FLIL) approach draws on the principles of DUB language learning (see also Kassenberg et al., this volume). All three of these pedagogical approaches may have gained popularity over the recent years, but true implementation in the mainstream classroom has not yet been widely observed (Van den Branden, 2016; Verspoor et al., 2015). A frequently encountered explanation for the lack of true implicit language learning approaches is the belief that grammar instruction is essential in language learning. Language teachers have often been shown to prefer a more explicit grammar-oriented approach. Graus and Coppen (2017: 658) investigated the attitudes of pre-service and in-service secondary school teachers in the Netherlands and found that there was a ‘marked preference for explicitly teaching declarative grammatical knowledge in a systematic manner, often relatively decontextualized and isolated from skills work or communicative tasks’. This finding is also reflected in what we see in language course book materials, which are commonly centred on grammatical features (Hinkel, 2017; Maijala & Tammenga-Helmantel, 2017; McCarthy, 2016; Ur, 2011, 2017). The role of grammar in the FL classroom might have been reduced over the years, but its explicit approach still seems to be the mainstay in many FL curricula both in the Netherlands and internationally (De Bot & Maljers, 2009; Richards & Rodgers, 2014; West & Verspoor, 2016). Larsen-Freeman (2015) also offers a possible explanation as to why explicit grammar teaching is still prominent in language classrooms. She attributes this to ‘learner security’, which is described as students’ preference for being given explicit rules, because they want ‘the security of knowing what is right, which they believe rules give them’ (LarsenFreeman, 2015: 271). Explicit grammar instruction is a kind of classroom management tool that provides this feeling of ‘learner security’ and gives

The Icing On the Cake?  251

the impression that true instruction and learning is taking place (Borg, 2003; Larsen-Freeman, 2015), which fits best in an educational setting where knowledge is transmitted. Determining the optimal way of learning a FL in an instructional setting has often been on the continuum of how implicit or how explicit the focus on (grammatical) form should be. Explicit form-focused instruction (FFI) characterises itself by being predetermined and planned, directing attention to a target form in isolation, often with metalinguistic information, whereas implicit FFI attracts attention to form but is generally spontaneous, communication oriented, unobtrusive and without use of metalinguistic language (Housen & Pierrard, 2005; Long & Robinson, 2004). Explicit FFI has been shown to be more effective for tests targeting grammatical features (Goo et al., 2015; Norris & Ortega, 2009; Spada & Tomita, 2010). But when it comes to oral fluency, willingness to communicate, written complexity, lexical diversity and reading comprehension, approaches without explicit FFI also prove successful (see Kang et  al., 2019). It depends on the outcome measure on which language proficiency is gauged. Several studies have experimented with the amount and type of FFI with and without transferring explicit metalinguistic information. Goo et al.’s (2015) meta-analysis combined data from 34 studies on the effects of implicit and explicit teaching approaches. Overall, explicit teaching approaches yielded a larger effect than implicit teaching approaches; however, it depended on the way language performance was tested. The largest effect was for selected response measures (such as a grammaticality judgement task), where the participants had to choose a correct answer out of a list of options. In the studies that used free-constructed response measures, usually writing assignments, the differences in the effectiveness between the implicit and explicit condition were less notable. This was also apparent in Kang et al.’s (2018) meta-analysis on the effects of second language (L2) instruction. They aimed at identifying factors that could modulate the efficacy of language instruction. They concluded that type of instruction was the most significant moderator where both implicit and explicit instruction had a large effect on L2 learning but that implicit instruction appeared to have a significantly longer-lasting impact (Kang et  al., 2019: 13). The authors relate this finding to the inclusion of more diverse outcome measures compared to previous meta-analyses where explicit FFI yielded larger effect sizes. If we view language development as a complex and dynamic system then preferably studies would not only observe language development with different outcome measures, but they would also collect data over a longer period of time. But longitudinal studies investigating the effects of implicit language teaching approaches in authentic settings are rare (De Bot & Maljers, 2009). The few that are emerging show some overlap in their results. For instance, Rousse-Malpat and Verspoor’s (2012) study

252  Usage-Based Dynamics in Second Language Development

evaluated the oral performance of secondary school children learning French over 21 months at an initial proficiency level. One group followed FL classes with explicit FFI and grammar rules and the other group followed an accelerative integrated methodology (AIM) approach with more implicit FFI. Their results showed that the implicit group significantly outperformed the explicit group on general proficiency holistic scores. Also Piggott’s (2019) larger project of which we present a subset in this chapter, found positive effects of a more implicit teaching approach in the mainstream English as a foreign language (EFL) classroom at this initial proficiency level. In her study, 463 students were divided over two cohorts in which one received the regular explicit FFI including grammar rules (explicit group) and the other cohort received implicit FFI without explicit grammar rules (implicit group). For the implicit group, all of the grammar assignments were removed from the course book materials. After two years of secondary education, the implicit group outperformed the explicit group on measures such as fluency, reading comprehension, willingness to write and speak and initial lexical diversity. The explicit group, on the other hand, outperformed the implicit group on a few accuracy measures, mainly the ones concerning verb formation. At this stage of language development in an instructed setting, explicit grammar instruction seemed to only be beneficial for accurate language production and then mainly concerning verb forms, but at the cost of fluency and willingness to speak and write. In this light, an important issue would be determining when and how much explicit FFI is preferable in an instructed setting. In first language (L1) development, a child first develops intuitive awareness of grammaticality and can indicate that a sentence is wrong, but metalinguistic awareness arises later and is evident when a child is able to indicate why a sentence is incorrect (Karmiloff et  al., 2009). It has been proposed that this also holds for L2 acquisition in a naturalistic setting (Bialystok, 2001). If time is first provided to develop intuitive awareness through a more implicit approach, then explicit FFI and grammar rules might be (more) effective at a later stage, as learners become developmentally ready to incorporate metalinguistic knowledge into their emerging language awareness. Several studies have experimented with the timing of explicit FFI within a shorter time span. For instance, Shintani (2017) examined to what extent the timing of explicit FFI affected the development of explicit knowledge and accuracy in subsequent writing. The participants received either pre-writing explicit FFI, post-writing explicit FFI or pre- and during-writing explicit FFI. The study took into account the participants’ prior knowledge of the target structure (conditional clause). Shintani used an error correction test and a written text reconstruction to evaluate the effects of explicit FFI. The findings indicated that for the development of accuracy, the prewriting explicit FFI was most effective for students with no prior knowledge of the conditional clause. For the group with prior knowledge of the conditional clause it was the other way around:

The Icing On the Cake?  253

the post-writing explicit FFI resulted in the most improvement. Hence, explicit FFI followed by revision facilitated L2 learning more if the learners were already able to use the conditional clause noticing the gap between their output and the correct form. In other words, waiting until students were developmentally ready made explicit FFI more effective. This also seems in line with findings in Vyn et al. (2019), where teachers’ reported level of agreement with teaching explicit grammar correlated negatively with language gains at lower proficiency levels, but positively at higher levels of language proficiency. Combining implicit and explicit types of FFI differently in the FL classroom might bring the best of both sides, where explicit FFI can be the icing on the cake. So starting with an extensive period of implicit FFI and providing isolated explicit FFI after a basic level of proficiency is acquired. To date, no work has explored effects of delayed and reduced explicit FFI. If this approach proves effective then perhaps teachers will be confident to try implementing more pure forms of implicit FFI approaches knowing that explicit knowledge of grammar can be obtained later on in the learning process with less explicit FFI. Therefore this study sets out to answer the following research question: What are the effects of delaying and reducing the amount of explicit FFI with metalinguistic information and practice until the end of the second year of secondary education on the learners’ performance on a grammar test? Whereas most contributions to this volume focus on measures of complexity development from a DUB perspective, the current study takes a complementary accuracy focus. In a longitudinal setting, it investigates how development of explicit knowledge as a result of explicit FFI is affected by the stage of L2 development in which explicit FFI is provided. The study is both longitudinal and large scale: We incorporated two complete cohorts of pupils from a secondary school and studied complexity, accuracy and fluency in their language development over a period of two years. As such, we aim at being able to uncover how the emergence of explicit knowledge of language may relate to timing of explicit FFI and to L2 proficiency development. Method Participants

Participants in this research originally included a total of 463 Dutch secondary school students (Piggott, 2019). For the analysis in this study, students were only included if they completed all three tests and were in three consecutive years of secondary education. Groups were formed over two different cohorts. The first cohort was the explicit group and started in 2014 (n = 184); the second cohort was the implicit group and started in 2015 (n = 209). All students starting their first year of secondary

254  Usage-Based Dynamics in Second Language Development

Table 11.1  Number of students per educational level Explicit

Prevocational

Implicit

Test 1, 2 (n = 184)

Test 3 (n = 141)

Test 1, 2 (n = 209)

Test 3 (n = 120)

31

28

 43

15

General secondary

85

59

103

74

Pre-university

68

54

 63

31

education in 2014 and 2015 were included in the study. The age at entry varied between 11 and 13 years old and the average age at entry was 12.6. All levels of education (prevocational secondary education, general secondary education and pre-university education) were represented in the sample (see Table 11.1). The school was located in the Netherlands and for all students Dutch was their L1 or their dominant language. According to school protocol, parents received a curriculum and testing overview at the beginning of each school year. Parents were given the option to exclude their child from sharing data for analyses through a letter of informed consent. Forming two groups from two different cohorts as opposed to selecting students from the same cohort or two different schools gave the opportunity to control for possible school, socio-demographic and teacher differences and made it possible for students to be unaware of any specific intervention as all their peers were exposed to the same teaching procedure and testing. Teachers

Eight teachers were involved in this study, one of whom was the first author. Table 11.2 shows the years of experience and the total number of Table 11.2  Participating teachers , their years of teaching experience and number of implicit and explicit classes they taught Years of teaching experience

Explicit classes

Implicit classes

Year 1

Year 2

Year 1

Year 2

Teacher 1

18

2

1

0

1

Teacher 2

11

3

1

3

2

Teacher 3

 2

0

0

2

0

Teacher 4

11

2

3

1

2

Teacher 5

 7

1

1

1

0

Teacher 6 (first author)

11

1

0

1

1

Teacher 7

11

0

3

1

3

Teacher 8

 9

1

0

1

0

The Icing On the Cake?  255

classes taught during the study. The first author of this chapter instructed each participating teacher on the teaching procedures for the implicit group. Because the first author was employed at the participating school as an English teacher, the department meetings were used to discuss the daily proceedings and any difficulties that were encountered. All participating teachers, including the first author, were interviewed and observed to evaluate treatment fidelity (see Piggott, 2019). Teaching approach

In this study, both groups incorporated specific types of FFI, which we will define as ‘any pedagogical effort which is used to draw the learners’ attention to language form’ (Spada, 1997: 73). The explicit group received explicit FFI, which consisted of extensive grammar instruction including metalinguistic information. According to teachers’ self-reported estimates, 37% of the classroom time was spent on explicit FFI of grammar rules and grammar exercises. After two school years this totalled up to 86 hours of explicit FFI spent on grammar teaching and practice, out of a total of 233 hours of English classroom time. The rest of the classroom time (63%) was spent on reading, listening, speaking, writing and vocabulary exercises. The implicit group received the same number of classroom hours but these hours were predominantly spent on reading, listening, speaking, writing and vocabulary exercises that focused on meaning and implicitly on form. All of the explicit grammar exercises that required explicit FFI were removed from the course book materials and teachers were not allowed to explain grammar rules or use metalinguistic language. Preferably all types of FFI were implicit; however, teachers were allowed to use any type of pedagogical approach in their lessons they felt comfortable with as long as it did not involve grammar rules. Therefore, according to teachers’ self-reports and classroom observations, there were certain types of explicit feedback present in the classes, but these did not involve metalinguistic information. In the last seven weeks of the second school year, the students in the implicit group received a ‘grammar crash course’ that involved all of the grammatical subjects that had initially been removed from the course book materials. One of the three classes a week was spent on these grammatical subjects and included grammar rules. In total, the implicit group spent approximately 6 hours out of the total 233 hours of classroom time on explicit FFI and grammar exercises (2.5% of classroom time) as compared to the explicit group who, according to the teachers’ selfreport, spent approximately 86 hours out of 233 hours on explicit FFI and grammar exercises (37% of classroom time over two years). The explicit group did not receive any more explicit FFI during these last seven weeks than they were used to in their weekly lessons.

256  Usage-Based Dynamics in Second Language Development

Teaching materials

In the first year, both groups worked with the course book More! (Puchta & Stranks, 2008), which is a four-level course for lower-secondary students. In the second year, the prevocational level continued with More!’s Level 2 book. The general secondary and pre-university levels used Activate! A2 (Boyd & Barraclough, 2010). Both course books are internationally oriented for L2 learners of English, so no L1 (Dutch) is used in the course books. The books are form focused and each chapter has listening, reading and vocabulary assignments that are used to attract students’ attention to specific language features followed by a grammar section in which explicit attention is directed to form. During this section, the explicit group received explicit FFI and this was followed by grammar exercises. For the implicit group, the pages with grammar explanations and exercises were removed. Teachers’ self-report and classroom observations

Teachers received a questionnaire to gain insight into their activities in class (see Piggott, 2019). The answers to the questions were discussed with an independent interviewer in Years 1 and 2. According to estimates from the teachers’ self-reports, the time that was not spent on grammar in the implicit group was spent on extra reading (+7%), listening (+6%), writing (+14%) and speaking (+5%) exercises as compared to the explicit group. During the interview, several teachers mentioned that a considerable amount of extra time was spent on vocabulary but that this was integrated into the reading, listening, writing and speaking exercises. In the interviews, it also became apparent that teachers either spent more time on the exercises in the course book or they developed their own exercises to use in class. Classroom observations that focused on feedback showed that, overall, the explicit group received more feedback, which mainly consisted of recasts, repetitions and explicit corrections. The implicit group received less feedback, but when they did, it mostly consisted of recasts and explicit corrections (without metalinguistic information). Grammar test

The grammar test consisted of gap-filling exercises on multiple grammatical features: verb forms (14 questions), degrees of comparison (5 questions), indefinite pronouns (4 questions about some and any), quantifiers (4 questions about much and many) and word order (11 questions) (see Appendix). The test was designed by Schoonen et al. (2011) based on the content analysis of common EFL textbooks in the Netherlands. The fill-in-the-blank items with a prompt between brackets made it possible to assess knowledge of grammatical forms without the need to search for the intended lexical item. The tests were administered digitally, graded in an online testing system and checked by a research assistant.

The Icing On the Cake?  257

The test was administered three times within nine months in the participants’ second and third year of secondary education. The first time was seven weeks before the end of the second school year, just before the implicit group would receive explicit grammar instruction. At this time, the implicit group received the test digitally whereas the explicit group received the same test on paper, due to organisational limitations. For this reason, the results of the explicit group’s first test were not included in the analyses. After the implicit group had received six hours of explicit FFI with grammar rules and practice divided over seven lessons, the same test was administered digitally to both groups. For the explicit group, the results of this second test were used for both Time 1 and Time 2 in the analyses. As the explicit group did not receive any (extra) explicit FFI or practice on the selected test items, we predicted that differences in scores between the explicit group’s (unchecked) Time 1 and Time 2 test would be minimal. The fact that also the explicit group did see and make the test at Time 1 ensured that there would not be a test bias in favour of the implicit group. A delayed post-test was administered to both groups digitally at the beginning of the third school year. At this time, no extra formal instruction concerning the test items had taken place for both the implicit and explicit group. Not all of the participants completed this third test, but the sample was still considered to be representative for comparison because only a small number of students per class in each cohort did not complete the delayed post-test (see Table 11.1). Analysis

This study implemented multilevel modelling (MLM). MLMs provide a way of analysing data that has a hierarchical structure; in this model, students are nested into different classes. MLMs take into account that individuals who share the same environment must have more in common than those who do not (Hox et al., 2017). Additionally, an advantage of MLM over a repeated measures approach is that the MLM combines random factors, subjects and items into a single full analysis (Quené & Van den Bergh, 2004). The fixed occasion multilevel model design tested if being in either the explicit or implicit group had an effect on the grammar test at Time 1 (before the implicit group received any explicit FFI), at Time 2 (after the implicit group received the grammar crash course) and at Time 3 (4 months after Time 2 in the third year of secondary education). • The first model, the null model, was an intercept only model in which class was added as a random intercept allowing the intercepts for the different classes to vary. • In Model 1, Time was added as a repeated fixed effect. • In Model 2, Group (explicit vs implicit) was added to determine the main effect of being in either the explicit or the implicit group.

258  Usage-Based Dynamics in Second Language Development

• In Model 3, an interaction effect was added between Time*Group to determine if the effect of group varied over Time 1, Time 2, Time 3. If Model 3 was significant then contrast tests were carried out to determine if there was a significant interaction between Time 1 and Time 2 or between Time 2 and Time 3 or from Time 1 to Time 3. The models were evaluated with likelihood ratio tests by comparing the test model with the null model. The p-values reported are based on this likelihood ratio tests. The models were fit using SPSS 24.0. Results

Table 11.3 shows the means and standard deviations of the total number of correct responses and of the number of correct responses per category. Note that for the explicit group, the test scores for Time 2 were also used as dummy test scores for Time 1. Total score

For the total scores, the model showed a significant interaction between Time and Group (χ2 (2) = 180.4; p < 0.001). Contrast tests revealed the difference to be significant between Time 1 and Time 2 (t = 15.1; df = 393; p < 0.001). At Time 1, when there had been no explicit FFI for the implicit group, the difference between the implicit and explicit group was significant (t = 3.37; df = 20.9; p < 0.01), as compared to the explicit group’s Time 2 scores. During the other tests, no significant differences in total scores appeared (see Figure 11.1). Table 11.3  Means and standard deviation of the correct items on the grammar test Explicit Time 1* (n = 184)

Implicit Time 2 (n = 184)

Time 3 (n = 141)

Time 1 (n = 209)

Time 2 (n = 209)

Time 3 (n = 120)

Total (38 items)

–

28.3 (6)

30.0 (6)

23.2 (7)

28.3 (6)

27.6 (9)

Verb form (14 items)

–

9.0 (3.0)

9.7 (3.2)

5.7 (3.5)

8.4 (3.4)

9.3 (2.8)

Degrees of comparison (5 items)

–

4.1 (0.93)

4.3 (0.97)

3.6 (1.2)

4.2 (1.1)

4.1 (0.98)

Indefinite pronouns (4 items)

–

3.7 (0.59)

3.8 (0.45)

3.6 (0.76)

3.7 (0.71)

3.7 (0.68)

Quantifiers (4 items)

–

3.3 (1.0)

3.4 (0.87)

3.1 (1.1)

3.7 (0.81)

3.5 (1.1)

Word order (11 items)

–

8.3 (1.8)

9.0 (1.7)

7.3 (2.3)

8.4 (2.1)

8.7 (2.9)

* For the explicit group the scores at Time 2 were also used in the analysis for Time 1.

The Icing On the Cake?  259

Figure 11.1 Means of the number of correct items, SE 80% CI. IM: implicit group; EX: explicit group

Verb form

The performance on the feature verb form also showed a significant interaction between Time and Group (χ2 (2) = 133.7; p < 0.001). The interaction was significant between Time 1 and Time 2 (t = 12.5; df = 393; p < 0.001). Especially at Time 1, when there had been no explicit instruction for the implicit group, the implicit group scored significantly lower as compared to Time 2 in the explicit group (t = –4.6; df = 20.7; p