Exploring L1-L2 Relationships: The Impact of Individual Differences 9781800411807

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Exploring L1–L2 ­Relationships

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: 155

Exploring L1–L2 Relationships The Impact of Individual Differences

Richard L. Sparks

MULTILINGUAL MATTERS Bristol • Jackson

DOI https://doi.org/10.21832/SPARKS1791 Library of Congress Cataloging in Publication Data A catalog record for this book is available from the Library of Congress. Names: Sparks, Richard L. author. Title: Exploring L1-L2 Relationships: The Impact of Individual Differences / Richard L. Sparks. Description: Bristol; Jackson: Multilingual Matters, [2022] | Series: Second Language Acquisition: 155 | Includes bibliographical references and index. | Summary: ‘This book traces and summarizes the author’s theoretical insights and empirical findings in the field of foreign language education. The volume explores individual differences in L1 ability and their connection to L2 aptitude and L2 achievement, L2 anxiety as an affective or cognitive variable, and the relationship between L1 and L2 reading’ – Provided by publisher. Identifiers: LCCN 2022023608 (print) | LCCN 2022023609 (ebook) | ISBN 9781800411791 (hardback) | ISBN 9781800411807 (pdf) | ISBN 9781800411814 (epub) Subjects: LCSH: Second language acquisition – Psychological aspects. | Individual differences. | Language transfer (Language learning) | Reading comprehension. | LCGFT: Essays. Classification: LCC P118.2 .S66 2022 (print) | LCC P118.2 (ebook) | DDC 401/.93 – dc23/eng/20220531 LC record available at https://lccn.loc.gov/2022023608 LC ebook record available at https://lccn.loc.gov/2022023609 British Library Cataloguing in Publication Data A catalogue entry for this book is available from the British Library. ISBN-13: 978-1-80041-179-1 (hbk) Multilingual Matters UK: St Nicholas House, 31-34 High Street, Bristol, BS1 2AW, UK. USA: Ingram, Jackson, TN, USA. Website: www.multilingual-matters.com Twitter: Multi_Ling_Mat Facebook: https://www.facebook.com/multilingualmatters Blog: www.channelviewpublications.wordpress.com Copyright © 2022 Richard L. Sparks. 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 Riverside Publishing Solutions. Printed and bound in the UK by the CPI Books Group Ltd.

To Leonore, my friend, colleague and mentor. And to Alicia – my wife, my life and my love – without whom I would have accomplished nothing.

Contents

Acknowledgements

xi

Foreword Zhisheng (Edward) Wen and Peter Skehan Introduction and Overview Richard L. Sparks

xiii

1

Part 1: Theoretical Insights into L1–L2 Relationships: IDs in L1 Attainment and the Linguistic Coding Differences Hypothesis (LCDH) 1 Searching for the Cognitive Locus of Foreign Language Learning Difficulties: Linking First and Second Language Learning  Richard L. Sparks and Leonore Ganschow 2 The Impact of Native Language Learning Problems on Foreign Language Learning: Case Study Illustrations of the Linguistic Coding Deficit Hypothesis Richard L. Sparks and Leonore Ganschow 3 Examining the Linguistic Coding Differences Hypothesis to Explain Individual Differences in Foreign Language Learning Richard L. Sparks Part 2: Empirical Support for L1–L2 Relationships and Cross-linguistic Transfer 4 Long-term Cross-linguistic Transfer of Skills from L1 to L2 Richard Sparks, Jon Patton, Leonore Ganschow, Nancy Humbach and James Javorsky 5 Individual Differences in L2 Achievement Mirror Individual Differences in L1 Skills and L2 Aptitude: Cross-linguistic Transfer of L1 Skills to L2 Richard Sparks, Jon Patton and Julie Luebbers vii

15 21

33

45

59 65

82

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6 Do L1 Reading Achievement and L1 Print Exposure Contribute to the Prediction of L2 Proficiency?  Richard Sparks, Jon Patton, Leonore Ganschow and Nancy Humbach

101

Part 3: Relationships Among IDs in L1 Attainment, L2 Aptitude and L2 Proficiency119 7 Profiles of More and Less Successful L2 Learners: A Cluster Analysis Study Richard Sparks, Jon Patton and Leonore Ganschow

127

8 Long-term Relationships among Early First Language Skills, Second Language Aptitude, Second Language Affect and Later Second Language Proficiency Richard Sparks, Jon Patton, Leonore Ganschow and Nancy Humbach

144

9 Subcomponents of Second Language Aptitude and Second Language Proficiency  Richard Sparks, Jon Patton, Leonore Ganschow and Nancy Humbach Part 4: L2 Anxiety: Affective Variable or Cognitive Variable?

163

181

10 Foreign Language Learning Differences: Affective or Native Language Aptitude Differences? Richard Sparks and Leonore Ganschow

187

11 Is the Foreign Language Classroom Anxiety Scale (FLCAS) Measuring Anxiety or Language Skills? Richard Sparks and Leonore Ganschow

201

12 Relationship of L1 Skills and L2 Aptitude to L2 Anxiety on the Foreign Language Classroom Anxiety Scale Richard Sparks and Jon Patton

217

Part 5: Relationships between L1 and L2 Reading Ability

235

13 Language Deficits in Poor L2 Comprehenders: The Simple View Richard L. Sparks

243

14 L2 Reading Comprehension is Hard Because L2 Listening Comprehension is Hard, Too Richard Sparks, Jon Patton and Julie Luebbers

261

Contents ix

15 Identification and Characteristics of Strong, Average and Weak Foreign Language Readers: The Simple View of Reading Model Richard L. Sparks

282

Part 6: Individual Differences in L1 Achievement, L2 Aptitude and L2 Achievement299 16 Explaining Individual Differences in L1 Ability and their Relationship to IDs in L2 Aptitude and L2 Achievement Richard L. Sparks Part 7: Epilogue and Future Directions 17 Conclusion: Toward a Model of Language Aptitude Richard L. Sparks

301

321 323

Appendices338 References345 Index366

Acknowledgements

The publication of my work on L2 learning is a great honor. I was encouraged to pursue this project by my colleague, Dr Edward Wen of the Macao Polytechnic Institute, who graciously included me as a keynote speaker at two language aptitude roundtables held in Macao and Zhuhai, China and who also invited me to collaborate on several volumes. I am very grateful for his confidence in my abilities. My work on L1–L2 relationships was greatly influenced by Dr Keith Stanovich, whose research in L1 reading sparked so many connections between L1 and L2 reading and learning. My work has also been greatly influenced by Peter Skehan and his groundbreaking work on L2 aptitude. I have been immensely fortunate to collaborate with special people, most notably my late colleague, Leonore Ganschow. Leonore and I conducted research for more than 20 years and co-authored 75 manuscripts from 1986 to 2012. I was fortunate to meet Leonore, who was both a mentor and a dear friend. Jon Patton has been a collaborator since 1990. Jon assisted with the most sophisticated analyses and proved to be one of the most patient individuals with whom I have ever worked. I have had the good fortune to work with two very special journals editors, the late David Benseler at The Modern Language Journal and Anne Nerenz at Foreign Language Annals. These two special people provided a forum for our ideas and helped us to publish cutting edge research. I would be remiss if I did not thank Dr Joseph Cresci, a special person and mentor, who encouraged me to pursue my doctoral work and also to open my private practice. His guidance and wisdom helped to make me a better person. Special thanks go to my long-suffering assistant, Janis Hauck, who has typed my manuscripts, assessment reports, disability reviews and assorted minutiae for more than 30 years. She has accepted my messy handwriting with heavy sighs and good cheer. I have also been fortunate to collaborate with Lois Philips, James Javorsky, Nancy Humbach, Julie Luebbers, Marge Artzer, Mark Plageman, David Siebenhar, Karen Miller, and many others. I also am grateful to the many undergraduate and graduate students who volunteered their time to assist with data collection for my studies. Likewise, I am appreciative of the schools and school districts xi

xii Acknowledgements

that agreed to host our studies since 1990. In particular, I thank those schools that allowed me to conduct the longitudinal studies that lasted for several years and the language teachers, guidance counselors and administrators who were so gracious with their time. I am indebted to all these individuals and the organizations that have been a part of my life for so many years. My wife, Alicia, has been my best friend and my love forever. I am grateful that she accepted my proposal so many years ago. Without her, I would have accomplished nothing.

Foreword

It is a privilege for the two of us to have this opportunity to read this book, written by our colleague and collaborator Professor Richard Sparks, and to have the honor to write a foreword. Richard has had a distinguished career and is now Professor Emeritus of Special Education in the Mount St Joseph University’s Department of Graduate Education. His broad research interests straddle foreign language learning, L1 and L2 reading, language aptitude and learning disabilities. Richard has published extensively in all these areas, publishing important papers in applied linguistics, foreign language study, educational psychology and learning disability journals. We have both read and cited his many influential publications on language, education, psychology, dyslexia or hyperlexia and, in particular, language aptitude for many years, and we have enjoyed many stimulating conversations with him in person. The book is a wonderful collection of Richard’s most influential articles, showcasing his insightful thoughts on many central and interlinked theoretical and methodological issues in current research across the disciplines of language, education and psychology. The ideas from the book will surely shed light on central issues and make significant contributions to the broad fields of applied linguistics, language learning and teaching, as well as educational psychology. At its core, the book tackles central issues and debates in current language education and applied linguistics. Integral to this is the role of the native language (L1) in explaining and predicting second language (L2) aptitude, and even ultimate attainment in second or foreign language (L2) in the long term. In other words, the book contributes to our understanding of the intricate relationship between bilingual learners’ native language (L1) skills and their foreign or second language (L2) learning. To address this issue, Richard has conducted numerous empirical studies, many of a (rare) longitudinal nature, over the last 40 years in his remarkable career, culminating in the detailed and comprehensive account provided by this volume. Having received comprehensive training in educational psychology and special education, and by xiii

xiv Foreword

conducting numerous empirical studies in L1 reading and learning disabilities, Richard first laid out his thoughts on the issue of L2 learning in his Linguistic Coding Differences Hypothesis (LCDH; and see Part 1 of this volume). This clarified his proposals for the instrumental role of native language (L1) in L2 aptitude and L2 learning outcomes. To support this hypothesis, Richard has conducted systematic and programmatic studies, gathering evidence from cross-linguistic transfer research (see Part 2). Following this, Richard moved on to explore the relationships among IDs in L1 attainment, L2 aptitude and L2 proficiency (see Part 3). Drawing on this body of work, Richard broadened the scope of his research to investigate L2 learners’ cognitive and affective states, including their anxiety level. He has published convincing evidence to support his challenging claim that L2 anxiety should be considered as a linguistic variable rather than an affective variable as previously held by many scholars in both applied linguistics and educational psychology (see Part 4). Even though the role of the L1 in language education and bilingualism has long been recognized and discussed (e.g. Cummins, 1979), the topic itself has been marginalized in the SLA literature, with only occasional studies investigating this issue. In contrast to this, the topic has never been so thoroughly and systematically investigated and discussed as Richard has done over the years, as demonstrated in the many empirical chapters included in this volume (see Parts 3 and 4). Richard has also investigated the issue of L2 reading and has demonstrated how lessons from L1 reading can be applied to learning to read an L2 (Part 5). In a new essay (Part 6), he provides an overview of the research on IDs in L1 ability and the relationship of IDs to L2 learning, and explains that there is variation – often substantial variation – between groups of learners and between individual learners across multiple characteristics. Richard has presented to us a clear, up-to-date and comprehensive account of the relationships between L1 and L2, buttressed with extensive empirical evidence from systematic research programs, with the most rigorous designs, conducted by himself and colleagues, in particular the late Leonore Ganschow. In this sense, the contributions that this book makes to applied linguistics and language education are unique and extensive! In recent years, we have been extremely fortunate to be able to collaborate with Richard on a number of book and journal article projects related to individual differences in SLA, in general, and language aptitude in particular (Wen et al., 2019; Wen et al., forthcoming; Wen, Skehan & Sparks, 2022). Richard’s empirical background and unique perspective on language aptitude have been integral to our joint projects and publications. Indeed, his prescient insights on language aptitude as couched within his Linguistic Coding Differences Hypothesis (Sparks, 1995; Sparks & Ganschow, 1991, 1993, 1995) have been well thought

Foreword xv

out, well grounded, and well supported by his own studies and those conducted by other scholars applying the model either directly or inspired by it. According to a recent survey covering 60 years of language aptitude research and publications (Chalmers et al., 2021), Richard’s number of empirical papers on the topic of language aptitude published in key journals ranked No. 1 among all language aptitude researchers. Yet even this impressive achievement has considerably underestimated Richard’s actual publication number on this important topic: we later found out that several other papers have been published by Richard but were not included in that list. Generally, then, we can say that Richard’s LCDH constitutes one of the core perspectives to conceptualize and investigate foreign language aptitude (Wen, 2022; Wen, Biedroń & Skehan, 2017). But in this volume, Richard has not just been content to restate his earlier formulation of the LCDH – he has also expanded the LCDH into a much broader conceptual model of language aptitude that subsumes domain-specific components (including phonetic script, vocabulary, grammar, and inductive language ability as measured in the MLAT by Carroll and Sapon, 1959) and domain-general factors (such as motivation, selfregulation, executive functions and emotions or anxiety). This ‘Grand Synthesis’ will undoubtedly exert great impact and influence on the increasingly important topic of language aptitude. Coincidentally, 2023 marks the 30th Anniversary of Richard’s theoretical framework of language aptitude. To celebrate this important language aptitude model and many other landmark contributions made by Richard to the diverse fields of applied linguistics, language education and educational psychology, we are guest editing a special issue of the Language Teaching Quarterly Journal (LTQJ) that is solely dedicated to Richard! Once again, we wish to congratulate Richard on completing this seminal volume on L1–L2 relationships, and to acknowledge sincerely our appreciation and thanks to Richard for his enormous contributions to the fields of applied linguistics and language education. Zhisheng (Edward) Wen and Peter Skehan June 2022 References Carroll, J.B. and Sapon, S. (1959/2000) Modern Language Aptitude Test (MLAT). New York, NY: The Psychological Corporation. (Reprinted in 2002 by Second Language Testing Inc.). Chalmers, J., Eisenchlas, S.A., Munro, A. and Schalley, A.C. (2021) Sixty years of second language aptitude research: A systematic quantitative literature review. Language & Linguistics Compass, e12440. https://doi.org/10.1111/1nc3.12440. Cummins, J. (1979) Linguistic interdependence and the educational development of bilingual children. Review of Educational Research 49, 222–251.

xvi Foreword

Sparks, R. (1995) Examining the Linguistic Coding Differences Hypothesis to explain individual differences in foreign language learning. Annals of Dyslexia 45 (1), 187–214. https://doi.org/10.1007/BF02648218. Sparks, R. and Ganschow, L. (1991) Foreign language learning difficulties: Affective or native language aptitude differences? The Modern Language Journal 75, 3–16. https:// doi.org/10.2307/329830. Sparks, R. and Ganschow, L. (1993) Searching for the cognitive locus of foreign language learning problems: Linking first and second language learning. The Modern Language Journal 77, 289–302. https://doi.org/10.2307/329098. Sparks, R. and Ganschow, L. (1995) A strong inference approach to causal factors in foreign language learning: A response to MacIntyre. The Modern Language Journal 79, 235– 244.  https://doi.org/10.1111/j.1540-4781.1995.tb05436.x. Wen, Z. (2022) Language aptitudes. In T. Gregersen and S. Mercer (eds) The Routledge Handbook of Psychology of Language Learning and Teaching (pp. 389–403). London: Routledge. Wen, Z. and Mohabbi, H. (2022) Introduction to the Special Issue in Honour of Professor Richard Sparks. Language Teaching Quarterly Journal. Wen, Z., Biedroń, A. and Skehan, P. (2017) Foreign language aptitude theory: Yesterday, today, and tomorrow. Language Teaching 50 (1), 1–31. Doi:10.1017/S0261444816000276. Wen Z., Skehan, P. and Sparks, R. (2022 in press) Language Aptitude Theory and Practice. Cambridge: Cambridge University Press (Applied Linguistics Series). Wen, Z., Sparks, R., Biedroń, A. and Teng, F. (2022, forthcoming) Cognitive Individual Differences in Second Language Learning. Berlin: Mouton de Gruyter. Wen Z., Skehan, P., Biedroń, A., Li, S. and Sparks, R. (2019) Language Aptitude: Advancing Theory, Testing, Research and Practice. New York, NY: Routledge.

Introduction and Overview Richard L. Sparks

My study of L2s was serendipitous because I am not a L2 educator and, to my chagrin, do not speak, read or write another language. I studied Latin in the rural US, which, like most of my country, is a monolingual environment. I started my career as a special education teacher for students with academic learning and behavior problems, and as a tutor for students with learning disabilities (LD) and reading disabilities (dyslexia). While earning my doctorate, I was a graduate assistant and then a consultant at Cincinnati Children’s Hospital, where I evaluated children and adolescents with a range of learning and cognitive problems. There, I learned to perform psychoeducational assessments using the standardized measures of achievement and cognitive skills that are ubiquitous in the US. After graduation, I accepted a full-time position as a university professor and opened a private practice as an educational consultant. For 35 years, I taught courses in LDs, reading development and reading disorders, clinical and educational assessment, and also in research. In my private practice and other clinical settings, I assessed children, adolescents and adults referred for LDs, reading difficulties and other learning problems, eventually evaluating more than 4,500 individuals. My private work included consultation with and professional development for school districts and professional agencies. For many years, I have served as a Disability Consultant for medical boards, law boards, and college entrance exam boards, conducting disability reviews for individuals requesting testing accommodations (pursuant to the American with Disabilities Act). More recently, I have traveled the US conducting seminars in reading science for teachers and school administrators. How did that background prepare me to conduct research in L2s? In the US, most monolingual English students do not study L2s, and those who do generally will not become proficient or literate in the target language. (Only 1% of US citizens are fluent or literate in an L2 they learned in school.) My journey began when I received referrals to my private practice of university students who were having difficulty fulfilling their college L2 requirement. Most had earned average to above average grades in college courses but achieved below average 1

2  Exploring L1–L2 Relationships

grades in language courses. These students were referred by a professor at a neighboring university, Dr Leonore Ganschow, with whom I shared expertise in native English (L1) reading, learning disabilities (LD) and dyslexia (reading disabilities). Early on, we speculated that there would be an intimate connection between learning one’s L1 and learning an L2. The idea that both L1 and L2 involve the learning of language and require mastery of the different language components, e.g. phonology, orthography, syntax, vocabulary, etc., has been the inspiration for all our subsequent work. We thought that our contribution to L2 research could be investigating the connections between L1 and L2 skills. Our intuitions about L2 learning and our L2 research started from a basic premise: Since L2 learning is the learning of language, students with stronger L1 skills would be stronger L2 learners and students with L2 learning difficulties would be found to have overt or subtle problems with their L1 learning skills. An important advantage for our L2 work was our extensive knowledge of L1 language and literacy development. In L1, it has been well known for many years that there are extensive individual differences (IDs) in L1 ability that can be identified and measured by preschool age. These early IDs in L1 have been found to affect later L1 literacy and language skills and are related to more and less successful L1 learning many years later. Our work with LD and dyslexic students and individual assessments of individuals with stronger to weaker L1 ability allowed us to observe IDs in students’ language skills on an almost daily basis. We assumed that the IDs that we observed in L1 ability would also be observed in L2 achievement. Ganschow and I began our collaboration by searching the L2 literature for research on L1–L2 connections and language learning problems but found that very little work on this topic had been published. Fortunately, we encountered John Carroll’s extensive work on language aptitude and the Modern Language Aptitude Test (MLAT) and learned that L2 learning outcomes were strongly related to performance on this test, which tapped into individuals’ language abilities. (We found an old, dusty copy of the MLAT in the library of Ganschow’s university, a prize that for years we treated like the pot of gold at the end of the rainbow.) We found Paul Pimsleur’s work on L2 underachievers and his L2 aptitude test, the Pimsleur Language Aptitude Battery (PLAB). We discovered Peter Skehan’s classic work on individual differences (IDs) in L2 learning and the origins of language aptitude, and we learned there were strong relationships between early L1 ability and later L2 aptitude and L2 achievement. We also read Jim Cummins’ work on his Linguistic Interdependence Hypothesis (L1 and L2 have a common underlying proficiency) and Threshold Hypothesis (one’s level of L2 proficiency is moderated by one’s level of ability in L1) and wondered why his hypotheses had not been the subject of extensive empirical investigations on ID differences in L2 achievement. We were encouraged when we

Introduction and Overview  3

found that our ideas about L2 learning were similar to those of these giants in the L2 field. More importantly, the work of Carroll, Pimsleur and Skehan in L2 aptitude introduced us to a whole new dimension of L2 learning, specifically the possibility that students’ L2 aptitude as embodied in aptitude tests might be related to and a reflection of their L1 ability. The work of these researchers and our L1 backgrounds led us to posit that the foundation for ultimate achievement in L2 is the individual’s L1 ability, and that students’ L2 achievement reflects, or is mediated by, their L1 ability. Shortly thereafter, in 1989, we developed and published a theory about L2 learning, the Linguistic Coding Deficit Hypothesis (LCDH), which built on our intuition that L2 learning problems reflect overt or subtle L1 learning problems. In these early years, the notion of deficits in L1 skills reflected our backgrounds in working with students with LD and reading disabilities. However, as our studies expanded from students with L2 learning problems to all L2 learners, including those who were successful in L2, we modified the name of the hypothesis from deficit to differences. Also, our early studies found that although low-achieving L2 learners’ native language (L1) skills were weaker than average- and high-achieving L2 learners, their L1 skills were still in the average range, i.e. they did not exhibit language deficits. The publication of the LCDH in 1989 began a 30-plus years journey of studies with US students enrolled in secondary and postsecondary L2 courses. Leonore and I found that we shared a strength in connecting research in L1 learning to research for learning L2s. One advantage we possessed for the study of L2s was our practical experience as educational diagnosticians and our skill in using standardized measures of L1 ability to assess students’ oral and written language skills. We also became familiar with standardized measures of L2 aptitude, and later with standardized measures of Spanish achievement. Another advantage for our work was that standardized tests to measure L1 cognitive abilities and academic skills, including oral and written language, are readily available in the US. (When we began our collaboration, Ganschow and I assumed that all countries, including those in Europe, had developed a wide array of individually administered, standardized tests of L1 skills, and that aptitude tests such as the MLAT and PLAB had been translated into different languages. However, we soon discovered that we were naïve about the availability of these measures.) Standardized tests include norms by which individuals can be compared to other individuals of the same age (or grade) along a common scale that makes it possible to determine the relative standing of an individual within the group. These tests can also be administered in longitudinal studies to track an individual’s progress over several years. The availability of these tests in the US provides insights into learners’ inter-individual

4  Exploring L1–L2 Relationships

differences (between students) and their intra-individual differences (within a learner) that cannot be readily discerned by traditional, groupadministered tests. The results from our studies beginning in 1991 have supported our early intuitions about L1–L2 connections and found that: (a) L2 learning problems are, first and foremost, language learning problems; (b) L1 learning and L2 learning have a common underlying foundation of language learning ability; (c) L1 ability and L2 aptitude are componential, i.e. comprised of different components each of which contributes to L2 achievement; (d) L2 achievement runs along a continuum of very strong to very weak learners; (e) L2 achievement is constrained by IDs in L1 ability, i.e. L2 learning skills reflect one’s level of L1 learning skills, generally; (f) IDs in L1 ability from preschool to early primary school will constrain L2 achievement several years later; (g) affective differences – e.g. motivation, anxiety – are largely related to one’s level of L1 and L2 skills, that is, those with higher anxiety (lower motivation) about language learning have weaker L2 proficiency and achievement, and vice versa; and (h) IDs in students’ L2 reading skills in alphabetic orthographies reflect IDs in their L1 reading skills. When we introduced the MLAT to the test batteries used in our studies we found that L2 aptitude also runs along a continuum of those with superior to poor aptitude; that students’ scores on L1 skill measures are strongly correlated with their L2 aptitude scores; and there are strong relationships among L1 ability, L2 aptitude and L2 achievement. Figure I.1 provides a visual depiction of the continuum of stronger to weaker L1 skills, L2 aptitude and L2 achievement. For those familiar with standardized test scores, Figure I.2 provides a visual depiction of the continuum of strong to weaker L1 and L2 learners using percentile rank scores. In addition to the tenets of the LCDH, another idea, the Assumption of Specificity (AOS), a concept borrowed from L1 reading research (see Stanovich, 1988), guided our research. In L1 reading, the AOS proposes that students with reading disabilities who have average to superior intelligence have a cognitive deficit reasonably specific to the reading task. Since reading is a language-based task, the deficit is thus language-related. According to the AOS, the cognitive deficit does not extend very far into other domains of cognitive functioning. If it were to do so, then these additional cognitive deficits would depress the constellation of abilities called intelligence, reduce the gap between IQ

Introduction and Overview  5

Figure I.1  Continuum of stronger to weaker L1 skills, L2 aptitude and L2 ­achievement

and reading, and the student would no longer be considered to have an unexpected reading problem – his/her reading problem would be predictable based on deficits in other cognitive domains and s/he would simply have low intelligence and no other explanation for the reading deficit would be needed. When applied to L2 learning, we proposed that the logic of the AOS was straightforward. The student with, at minimum, average intelligence who has L2 difficulties has a cognitive problem specific to the L2 learning task. Since L2 learning is the learning of language, the primary cognitive problem for learning a language is language related and does not extend very far into other domains of cognitive functioning. Ganschow and I proposed that many L2 learning theories that purported to explain L2 problems were not compatible with the AOS because they focused on global language learning skills/ strategies, e.g. learning strategies, learning styles, metacognition, or affective differences, rather than specific language-related variables. We labeled our proposal a ‘strong inference’ (see Platt, 1964), positing that language-related variables would be found to be the primary causal factors in more and less success L2 learning outcomes, and suggested ways that our hypothesis could be falsified (Sparks & Ganschow, 1995a). Yet another basic premise that has formed the foundation of our work is that IDs in L1 ability are universal and apparent at an early age.

Figure I.2  Normal distribution of stronger to weaker L1 skills, L2 aptitude and L2 achievement (percentile ranks)

6  Exploring L1–L2 Relationships

At first, the lack of investigations by L2/SLA researchers on IDs in L1 ability and their relationship to L2 aptitude and L2 achievement was puzzling. We were surprised when L2/SLA educators referenced Chomsky (1986), who claimed that variations in language acquisition are ‘marginal’ and could be ‘safely ignored.’ Likewise, we were confused when L2/SLA researchers commented that although children will vary in their rate of [L1] acquisition, ‘…all, except in the case of severe environmental deprivation, achieve full linguistic competence in their mother tongue’ (Ellis, 2004). Instead, we knew from our extensive experiences with L1 learners that there were substantial IDs in those with ‘full linguistic competence’, i.e. those who can speak and comprehend, in their first language. Contrary to the views of L2/SLA scholars, it has been well known for many years that individuals exhibit differences in L1 ability and that these differences can be measured, even before entry into school. Until recently, IDs in L1 ability have largely been ignored by L2 researchers, a problem that Dabrowska (2016) has labeled a ‘deadly sin’ in cognitive research. She acknowledges that IDs in L1 ability are ‘pervasive’ and claims that SLA researchers tend to ignore them when they are found. The evidence from our studies examining L1–L2 connections using the LCDH as a framework has converged to support the ideas proposed by Skehan and Cummins by showing that not only do L1 and L2 skills have a common underlying proficiency but also that IDs in early L1 ability are related to later L2 aptitude and L2 achievement. Moreover, IDs in L2 achievement appear to be moderated, and constrained, by one’s L1 ability. Our early publications about L1 ability and the relationships among L1 skills, L2 aptitude and L2 achievement caught the attention of L2 researchers. Several years ago, an anonymous reviewer remarked that our research studies appeared to follow a trajectory. The reviewer indicated that s/he had followed our work for several years and found that findings from an investment of time and resources in one study led to new research projects that yielded more detailed findings, and that these findings would lead to additional studies examining L1– L2 connections, and so on. At the time, Ganschow and I were busy teaching classes, testing students, conducting studies and writing papers and it is only with hindsight while writing this book that I have been able to consider the reviewer’s remarks. We began our research with case studies involving at-risk (low-achieving) L2 learners, studies that provided the impetus for theory development, i.e. the LCDH, in the early 1990s. We realized that our theory about L1–L2 relationships would require empirical support, so we embarked on a series of investigations comparing high- and low-achieving L2 learners in secondary and postsecondary classrooms. The results of these comparison studies led us to develop new projects with larger numbers of participants and increasingly complex and detailed statistical analyses used in prediction,

Introduction and Overview  7

factor analysis, cluster analysis and cross-linguistic investigations. The aforementioned studies included several longitudinal investigations lasting from 1 to 3 years. Even so, we understood that support for proposed causal connections among early L1 ability, L2 aptitude and later L2 achievement necessitated a more difficult path: a longitudinal study that followed students from elementary school to the time at which they completed L2 courses. In our case, that would mean following students for at least 10 years because US students generally do not begin L2 courses until high school. But here we encountered a problem: we assumed that L2 educators had designed readily available tests to measure students’ L2 reading, writing, spelling, speaking and language comprehension skills, e.g. in Spanish, French, German, etc., at the completion of L2 courses. However, we were wrong and realized that we would need to develop our own assessments of L2 achievement. Fortunately, we were assisted by three established L2 educators, who designed measures of L2 proficiency for our studies using guidelines from the American Council on the Teaching of Foreign Languages (ACTFL). The development of these measures changed the course of our research agenda because we now had L2 proficiency measures by which we could measure learners’ L2 oral (listening, speaking) and written (reading, writing, spelling) skills, assign quantitative outcomes to students’ performance, and observe both inter- and intra-individual differences in their L2 skills. Our 10-year longitudinal investigation produced a wealth of evidence which showed that L1 skills in early elementary school were strongly related to students’ L2 aptitude and their L2 outcomes many years later. Figure I.3 depicts the trajectory of our studies from 1986 to 2021, showing how findings in one area (comparison studies) led to new research projects (prediction, factor analysis, cluster analysis studies) and that findings from these new research projects led to additional projects that examined L1–L2 connections in different types of investigations (cross-linguistic, print exposure studies) and to more sophisticated statistical analyses (path analysis and regression, multiple and hierarchical regression) that examined L1–L2 connections. We made certain to conduct studies with different participants that replicated our previous investigations. Currently, the trajectory includes re-examining (replicating) some of our earlier studies using structural equation modeling (SEM) and mediation analysis. Figure I.3 also depicts four additional areas of research – L2 anxiety, L2 reading, L2s and learning disabilities (LD), and teaching L2 – two of which, L2 anxiety and L2 reading, are covered in this book. (I have published extensively on both LD and L2s and teaching L2s, but these topics warrant a separate publication. For example, see Sparks, 2006a, 2016.) At first glance, L2 reading and L2 anxiety may seem to be diversions from the central issue of our research agenda, i.e.

8  Exploring L1–L2 Relationships

Figure I.3  Trajectory of Sparks et al.’s studies from 1986 to 2021

relationships between IDs in L1 skills and subsequent IDs in L2 aptitude and L2 achievement. But, viewing these topics in this manner would be a narrow view of L2 research because they have the same focus as our other studies – the investigation of students’ language skills and the relationships between L1 ability and L2 learning. The ideas for these studies drew from the knowledge of our L1 backgrounds and each topic had many unanswered questions. For L2 anxiety, Ganschow and I had always been perplexed by the special place that affective factors, including anxiety, hold among L2 educators and researchers, particularly because there are no viable theories in L1 research which have shown that affective variables are causal factors in learning to read, write, speak, and comprehend language. Our paper most frequently referenced by scholars (Sparks & Ganschow, 1991) hypothesized that anxiety about L2 learning was related to students’ levels of language ability in L1 and to their L2 aptitude and L2 (language) achievement, i.e. students with lower anxiety would exhibit higher L2 aptitude and stronger L2 achievement, and vice versa. However, researchers had neither posed the question of anxiety and language relationships nor investigated our hypothesis. For L2 reading, L1 reading researchers have generated voluminous evidence that reading is a language-based skill, and they have provided strong support for the Simple View of Reading model, a model that is comprised of language skills that explain the bulk of the variance in L1 reading

Introduction and Overview  9

ability. My reading of the literature suggested that SLA/L2 researchers have not settled on a model that connected learners’ oral language skills with their written language ability and that explained L2 reading acquisition in alphabetic orthographies. All the aforementioned topics were comprised of a number of open questions that invited empirical investigations. Rather than distracting from our research agenda about L1–L2 connections, our work on these topics has generated strong evidence supporting the basic premises of the LCDH. The findings from our L2 anxiety and L2 reading research are applicable to L2 learners in different countries and different contexts. For example, L2 reading researchers in Europe and elsewhere are investigating how to identify language skills in weak and strong L2 readers (Alderson et al., 2016; Kahn-Horwitz et al., 2005, 2006), and researchers in most countries have studied anxiety in L2 learners (Teimouri et al., 2019). This volume traces our research group’s investigations over 30 years in several areas related to connections between L1 skills and L2 learning. The volume is comprised of seven parts, six of which represent different strands of research. The sections are arranged in a rough chronological order, although most of the topics were pursued in parallel, a common approach in a scientific program. I have attempted to choose representative examples from more than 140 publications from 1986 to 2021. In some cases, a paper was selected on the basis of the number of Social Sciences Criterion Index citations it received. In other cases, I chose more recent papers for contemporary relevance and/ or to respond to ongoing or new debates in the field. Five of the six parts contain introductions that both conceptualize the topic of that part and also review other work we have published. The last section is a free-standing essay that reviews the extensive literature on ID in L1 ability and provides a tutorial on how to understand IDs in, and the connections between, L1–L2 skills. Because of space constraints, papers have been abbreviated, but the content has not been changed. In some cases, figures and tables presenting statistical analyses have not been included and the reader is referred to the original paper. Because of the large number of L1 and L2 instruments included in our studies, these measures are listed in the text of the paper but are more fully described in the three Appendices. Part 1 presents papers covering the history and development of the LCDH and explains the bases for the theory. An introduction outlines the foundational premises of the theory and focuses on how IDs in L1 ability are related to IDs in L2 aptitude and L2 achievement. Part 1 includes two key publications, Chapters 1 and 2, which explain the theory and examine its development. The papers describe how two L1 educators’ thinking about L2 learning evolved and was influenced by our studies and also by L1 and L2 researchers. Chapter 3 is a highly cited paper that examines the profiles of five L2 student ‘prototypes’ with

10  Exploring L1–L2 Relationships

linguistic coding (language) differences and explains how the different student profiles are related to more and less successful L2 learning. This chapter highlights the inter-individual differences among and the intraindividual differences within the five students and explains how the administration of individually administered, standardized tests of L1 skills and L2 aptitude can identify a student’s strengths and weaknesses in the components of language important for L2 acquisition and have the potential to direct L2 instruction. Part 2 presents the results of three studies based on the theoretical insights described in Part 1 that provided empirical support for connections between L1 and L2 skills and for cross-linguistic transfer from L1 to L2. Two of the papers, both longitudinal studies published 10 years apart, tackle the notion of long-term cross-linguistic transfer of L1 skills to L2. The study in Chapter 4 was part of our 10-year longitudinal investigation that followed students from 1st to 10th grades and showed that differences in L1 ability in primary school are strongly related to L2 aptitude and L2 achievement 9–10 years later in high school. Because replication lends credibility to the results of scientific research, we conducted a second longitudinal study over three years of L2 courses. The second study, in Chapter 5, used a test battery similar to the L1 and L2 aptitude variables in our 10-year study, but also included measures of L1 working memory, L1 phonological memory, L1 metalinguistic ability and L1 reader attitudes. The findings showed that students’ levels of L2 achievement after 2–3 years of L2 courses reflected their levels of L1 achievement and L2 aptitude, that is, students who scored higher in a L1 skill such as reading also scored higher in the same L2 skill, and vice versa. The findings provided additional evidence for cross-linguistic transfer of L1 to L2. The third study, in Chapter 6, was also part of our 10-year longitudinal study and examined the effects of a heretofore unexamined variable in L2 research: L1 print exposure (reading volume), and its potential effects on later L2 achievement. The purpose of this study was to determine whether an environmental variable, i.e. reading, and its well-known impact on the development of language skills would make unique contributions to L2 achievement even after controlling for the effects of early L1 skills, L1 cognitive ability and L2 aptitude. The results revealed the importance of prior reading volume in L1 for ability in both oral and written L2. Part 3 brings together findings related to L1–L2 associations and L2 aptitude. What sets Part 3 apart from Part 2 is the focus on IDs in L1 development and ability and how these differences are related to L2 aptitude and L2 achievement. Readers from an L2/SLA perspective may find it surprising that there are substantial differences in early L1 ability upon entry into school (5–6 years of age) and that those differences are important for later L2 aptitude and L2 achievement. All the studies in Part 3 show that IDs in L1 are observable (and measurable)

Introduction and Overview  11

prior to the variation found in L2 aptitude and L2 achievement from a longitudinal perspective. In our view, the longitudinal nature of the studies strengthens arguments that L2 may be causally determined by L1. Chapter 7 presents a study that approached the topic of IDs in L1 and their relationship to later L2 aptitude and L2 achievement by using cluster analysis, the findings of which showed that high-, average- and low-achievers’ levels of L1 achievement developed prior to L2 exposure are consistent with their levels of L2 aptitude and L2 achievement several years later, i.e. strong L1 skills, strong L2 aptitude, strong L2 achievement, and vice versa. The findings from the cluster analysis also support our position that L2 learning runs along a continuum of stronger to weaker L2 learners (see Figures I.1 and I.2). Chapter 8 presents another study from our 10-year longitudinal investigation that determined the best predictors of L2 achievement from among L1 skills, MLAT, and affective (anxiety, motivation) measures. These findings showed that the MLAT was the strongest predictor of L2 achievement. For the first time, we were able to hypothesize that L2 aptitude tests such as the MLAT may ‘cut out’ the variance explained by L1 skills for predicting L2 achievement because L1 achievement and L2 aptitude tests are measuring similar language components, e.g. phonology, orthography, syntax, vocabulary, etc. Chapter 9 presents a factor analysis of the test battery used in our 10-year longitudinal study, the first time (to our knowledge) that such a study was performed with a battery that included L1 skills, L1 cognitive ability, L2 aptitude (MLAT) and affective variables. This seminal study revealed that subtests included in L1 achievement and L2 aptitude batteries that measured the same skill, e.g. phonetic coding, loaded on the same factor, suggesting that language aptitude is comprised of different components, i.e. language is componential, each of which taps into specific skills required for L2 learning. The findings supported our intuition that the MLAT may indeed replace the variance explained by L1 skills for predicting L2 achievement. Part 4 presents our research on L2 anxiety that has challenged the conventional wisdom about whether affective variables, in this case anxiety, are causal factors in L2 outcomes. In 1991, we introduced the idea that L2 anxiety instruments may be proxies for students’ L1 ability and measure (accurately) students’ self-perceptions of their L1 ability and L2 achievement. There is strong interest in the SLA/L2 community about language anxiety and our papers on this topic have been received with some interest. This section begins with Chapter 10, our most highly cited paper (from 1991) on the topic of L2 anxiety in which we reviewed Horwitz et al.’s (1986) Foreign Language Classroom Anxiety Scale (FLCAS) and concluded that the items on the survey are likely to be measuring students’ oral and written language skills rather than language anxiety, and that students’ anxiety for L2 learning is likely to

12  Exploring L1–L2 Relationships

be related to their language ability, i.e. those with stronger L1 skills and higher L2 aptitude will exhibit lower anxiety, and vice versa. In order to provide support for our hypothesis, we conducted a series of studies using the FLCAS and, later, Saito et al.’s (1999) Foreign Language Reading Anxiety Scale (FLRAS). Chapter 11 is taken from our 10-year longitudinal study that followed US students over 10 years, from 1st to 10th grades. This study found that students’ level of L2 anxiety measured in high school was strongly related to their L1 ability several years earlier in 2nd grade and to L2 aptitude measured before they began L2 courses, and also that the FLCAS was negatively correlated with L1 skills in 1st grade. We suggested that there would be no a priori reason that anxiety for an L2 in high school should be negatively correlated with L1 skills measured many years earlier in elementary school and L2 aptitude before engagement with L2 courses. The third study, in Chapter 12, found that L2 anxiety measured in high school predicted significant unique variance in L1 skills in elementary school several years prior to L2 exposure, and it also predicted growth in L1 skills from 1st to 5th grades and from 5th to 10th grades. Our more recent studies with the FLRAS have yielded similar findings (Sparks, Luebbers, Castaneda & Patton, 2018; Sparks, Patton et al., 2018a). These studies have supported our hypothesis that language skills play a confounding role in theories about anxiety in L2 learning and have suggested that those who promote L2 anxiety as a causal variable for more and less successful L2 learning have been presented with a classic confounding (third) variable problem, an issue that they have yet to resolve, and with questions about the role of L2 anxiety in L2 learning and about the validity of L2 anxiety instruments they have yet to address. Part 5 presents our research on L2 reading and literacy. The findings that there were strong relationships among L1 reading skills and L2 reading achievement encouraged us to pursue the question of whether there are similarities in L1 and L2 reading development for alphabetic orthographies. Likewise, our earlier findings that students with low scores on the MLAT Phonetic Script subtest also achieved lower scores in L1 and L2 reading provided evidence of connections among L1 literacy, L2 aptitude and L2 literacy. The voluminous evidence from L1 research showing that reading is a language-based skill pushed our agenda forward. In Part 5, I introduce the Simple View of Reading (SVR) model (Gough & Tunmer, 1986), a well-established model in L1 research that details the skills necessary for learning to read alphabetic orthographies, but which may be a new model for L2 educators. The SVR model postulates that reading comprehension is the product of word decoding and oral language (listening) comprehension. Word decoding is comprised of phonological/orthographic (speech sounds and letter-sound correspondence) skills, and oral language comprehension is comprised of syntactic (grammar) and semantic

Introduction and Overview  13

(vocabulary, meaning) skills. Research over many years has found that reading skill is related to the strengths and weaknesses (IDs) in these components of language. The SVR model also posits that there are good readers (good decoding, good comprehension) and three types of poor readers: dyslexic (poor decoding, good comprehension), hyperlexic (good decoding, poor comprehension) and garden variety (poor decoding, poor comprehension), who exhibit different profiles of strengths and/or deficits in word decoding and language comprehension. The introduction summarizes findings from L1 reading research and describes results from our studies using the SVR model to investigate L1–L2 reading connections. Two important studies that preceded my investigations into L2 reading using the SVR model are reviewed. The results of these studies motivated me to delve more deeply into L1–L2 connections with alphabetic orthographies. Chapter 13 presents my first study using the SVR model with US L2 learners in high school. The findings demonstrated that students’ intra-individual differences in their L2 reading skills fit the SVR reader profiles proposed by Gough and Tunmer. The second paper, in Chapter 14, with a larger group of L2 learners shows how students who had previously learned to decode an alphabetic orthography (English) easily learned to decode words in another alphabetic orthography (Spanish) but, even after three years of Spanish courses, continued to exhibit severe reading comprehension and listening (oral language) comprehension difficulties largely because of their poor Spanish vocabulary acquisition. This study also showed that Spanish word decoding and listening comprehension made independent contributions to Spanish reading comprehension. These studies, and others (see Sparks & Luebbers, 2018; Sparks & Patton, 2016), provided support for speculation that the SVR model can be used to explain reading in L2 alphabetic orthographies by showing that L2 word decoding and L2 oral language comprehension are separate, independent variables for explaining L2 reading comprehension and that L2 readers fit the profiles of good and poor readers proposed by the SVR’s authors. The third paper, in Chapter 15, explains how the SVR model can be used diagnostically to identify strong, average and weak L2 readers and to identify their reading-related strengths and weaknesses (IDs). Specific examples of standardized cognitive and linguistic measures for Spanish and English used to assess word decoding and language comprehension skills are cited and implications of the SVR model for assessment and pedagogy are presented. Part 6 is a new, free-standing essay that reviews the extensive literature on ID in L1 ability and provides a tutorial on how to understand IDs in, and the connections between, L1–L2 skills. As described in the book, I have learned that L2/SLA researchers believe that IDs in L1 are largely unimportant for considering IDs in L2 achievement. Although these views may be changing (see Andringa

14  Exploring L1–L2 Relationships

& Dabrowska, 2019; Dabrowska, 2019), this perspective ignores the voluminous evidence of early and extensive IDs in L1 ability. In addition, these beliefs overlook findings over 30 years showing that students with IDs in later L2 achievement demonstrate wide-ranging IDs in L1 ability as early as primary school. In the essay, I provide an overview of research on IDs in L1 ability and on the relationship of IDs to L2 learning. I include a tutorial that explains how inter-individual (between groups and individuals) and intra-individual (within an individual) differences are manifested in students’ L1 skills, L2 aptitude and L2 achievement. In the tutorial, I speculate how, and where, L1 working memory and L2 affective differences in motivation and anxiety could make a difference in advanced learners’ L2 achievement outcomes. I conclude with the commonsense observation that there is variation – often substantial variation – in most human characteristics. Moreover, in addition to the inter-individual variation in human characteristics, there is substantial intra-individual variation in individual profiles across multiple characteristics. In the case of L2 acquisition and development, researchers may ultimately find that the answers to more and less successful L2 acquisition and development might be in the places they have been the least likely to look. Part 7, Epilogue and Future Directions, concludes with a summary of the main concepts presented in each of the six preceding parts of the book. Next, given the book’s emphasis on L1–L2 relationships, I review theoretical insights for L2 learning by confirming the facts of IDs in L1 ability and how these differences impact L2 learning. Finally, I present my theoretical model of L2 aptitude and summarize my recommendations for investigating the skills involved in L2 acquisition.

Part 1: Theoretical Insights into L1–L2 Relationships: IDs in L1 Attainment and the Linguistic Coding Differences Hypothesis (LCDH)

Introduction

At 19 years of age, while working my way through college, I was ‘promoted’ from Athletic Director to the position of Education Director at a local Boy’s Club of America. I had no qualifications for the position but was expected to organize tutoring programs and also to tutor children. The local schools that referred children to our program requested that they be tutored in reading. I was always a good, even voracious, reader and never considered that others could not read well. I was shocked by my first encounters with young children in the elementary grades who read poorly, or not at all. How could they not perform a task that was so easy? These encounters were the beginning of my 50-year journey spent in the study of language and reading, both of which have been integral to my career, and even more so in L2 research. When speaking at conferences, Ganschow and I were often asked why two L1 educators who could not speak, read or write an L2 were studying L2 learning. We responded sincerely that we had fallen into a ‘black hole,’ an endlessly interesting place from which we could not escape, because we quickly realized that L2 learning problems were much like the L1 reading, spelling and writing problems with which we were familiar – they were largely language learning problems. Our early case study research (Ganschow & Sparks, 1986) showed that college students with L2 learning problems displayed subtle or overt L1 learning problems in one or more components of language. In 1989, we published our first paper, which examined the cases of 22 university students who had received waivers for the college L2 requirement after failing L2 courses (Sparks et al., 1989). When these individuals were assessed with IQ and L1 achievement tests, the results revealed language difficulties (but not deficits) in their L1 phonology (sound–symbol coding), 15

16  Part 1: Theoretical Insights into L1–L2 Relationships

syntactic (grammar), and/or semantic (vocabulary, inferencing, etc.) skills. These findings reinforced our intuition that, similar to L1 learning, linguistic coding abilities (language skills) would positively or negatively affect L2 learning. When combined with our experiences as language educators, our case study findings led us to propose a hypothesis that explained more and less successful L2 learning. Given our backgrounds in LDs and reading disabilities, the Linguistic Coding Deficit Hypothesis (LCDH) initially focused on students with L2 learning problems, largely because those are the students we encountered. The term, linguistic coding, was derived from Vellutino and Scanlon (1986), who proposed three types of linguistic coding problems in poor readers: phonological (sound) and phonological/orthographic (letter–sound) difficulties; syntactic (grammar) difficulties; and semantic (meaning) difficulties. In our case studies, we found that the most common problems of poor L2 learners were phonological and phonological/orthographic difficulties. These individuals, who displayed subtle problems with L1 word decoding and spelling, experienced almost immediate problems in introductory L2 classes because of basic problems with L2 word decoding and spelling. For example, they exhibited problems converting letters to speech sounds to decode (read) and spell words in the target language, e.g. in Spanish, learning that the letter a corresponded to the speech sound /ŏ/ to read and spell casa. Other students had no difficulty with the phonology and orthography of the L2 but instead displayed problems with syntax and semantics. These students generally achieved above average grades in introductory L2 courses but began to struggle in intermediate level courses as the demands increased for grammar, e.g. with verb changes such as hablo, hablas, habla, etc., or with nouns and articles such as el chico or la chica, los chicos or las chicas, and for semantics, e.g. vocabulary growth affecting reading and spoken language comprehension. From time, to time, we encountered poor L2 learners who struggled with all three language components. The development and publication of the LCDH in 1989 encouraged us to conduct our first empirical investigations, all of which were ‘tests’ of the theory. If our theory was viable, then good and poor L2 learners should exhibit significantly different levels of L1 ability in the language components and in L2 aptitude (MLAT). On the other hand, if good and poor L2 learners exhibited similar (nonsignificant) levels of L1 ability in the language components and in L2 aptitude, then the problems experienced by poor L2 learners would be likely to lie elsewhere, outside their language abilities. These investigations with secondary and postsecondary L2 learners from 1990 to 1993 found that there were significant differences between good (successful, high- and averageachieving) and poor (less successful, low-achieving) L2 learners in their L1 literacy skills (reading, spelling, grammar) and L2 aptitude. The

Part 1: Theoretical Insights into L1–L2 Relationships  17

bulk of between-group differences was apparent on L1 phonological, phonological/orthographic and syntactic measures. Importantly, these studies led us to revise the term ‘deficit’ in the LCDH to ‘differences’ because the L1 skills of the poor L2 learners were not deficient but instead were in the average to low average range. The studies also provided support for our hypothesis that students’ L1 skills reflected their levels of L2 aptitude and L2 achievement, i.e. those with stronger L1 ability also displayed higher L2 aptitude and L2 achievement, and vice versa. With the insights obtained from these studies, we were prepared to further develop our theory. The chapters presented in this section include our most frequently referenced papers about the LCDH and are intended to highlight and explain the development and progression of the theory that was the foundation for our future studies, many of which have been included in Parts 2–5. Chapter 1, ‘Searching for the Cognitive Locus of Foreign Language Learning Difficulties,’ was modeled on papers by L1 researcher Keith Stanovich (1986a, 1988) in which he introduced the term, Assumption of Specificity (AOS). For L1 reading disability (dyslexia), the premise of the AOS is that the cognitive problems of an individual with a severe reading disability are reasonably specific to the reading task and do not implicate broader domains of cognitive functioning, e.g. intelligence. For our paper, we used the AOS to hypothesize that the cognitive problems of individuals with L2 learning problems, both oral and written, are reasonably specific to the task of learning language; thus, the problems with L2 learning are language-related and do not extend too far into other domains, e.g. affective characteristics, intelligence, learning strategies. (I discuss the AOS when applied to L2 learning in more detail in the Epilogue and elsewhere.) We proposed that one candidate for identifying L2 learning problems is the phonological component of language because this skill had been found in our studies to distinguish good from poor L2 learners. We also used the concept of modularity to show how (like L1 learning) a deficit in one language component (phonology) could lead, over time via Matthew Effects, i.e. rich get richer and poor get poorer effects in education (Stanovich, 1986b), to problems in other language skills such as syntax and semantics. The reasoning involved in the development of this paper led to an important advancement in our thinking about L2 learning by leading us to focus on language differences, not language deficits. The second chapter in Part 1, ‘The Impact of Native Language Learning Problems on Foreign Language Learning,’ was presented to L2 educators and researchers as an example of students who displayed individual differences (IDs) in L1 skills, and the relationship of these IDs in L1 skills to the IDs displayed by the students in their L2 aptitude and L2 achievement. For this paper, we used our diagnostic expertise and knowledge of L1 cognitive and L1 achievement tests as well as the MLAT

18  Part 1: Theoretical Insights into L1–L2 Relationships

to showcase five L2 ‘prototypes’ of more and less successful L2 learners with distinct IDs in their linguistic coding (language) profiles. Given the dearth of research on the relationship between L1 and L2 learning, we surmised that L2 educators may not be aware that, like L1 learners, L2 learners will display measurable inter-individual (between learners) and intra-individual (within a learner) differences. In retrospect, the paper highlighted several challenges faced in bringing IDs in L1 attainment to the attention of L2/SLA researchers. The primary challenge is that while SLA researchers may acknowledge IDs in L1 attainment, they have rarely attempted to study L1 differences in relation to L2 learning (see Dabrowska, 2016). A second challenge is that L2/SLA researchers may not be aware that L1 skills can be measured using individually administered, standardized tests that compare individuals to others of the same age (or grade) so that even subtle differences in language components are revealed, even by preschool age. A third, and related, challenge is that individually administered, standardized tests of L1 achievement, e.g. in French, Spanish, German, that are able to detect IDs in language skills may not be generally available in languages other than English. (Group-administered measures are not diagnostic and are unlikely to reveal subtle, and sometimes overt, differences in students’ language skills.) A fourth challenge is the difference between the US and European contexts for studying L2s. In the US, most students do not begin L2 courses until 9th grade and study the language in a largely monolingual English environment to fulfill a graduation requirement, not to become fluent or literate in the language, whereas other countries begin L2 study in the elementary grades, sometimes in bilingual or multilingual environments. Nonetheless when tested, we contend that younger students in bilingual or multilingual environments will also display distinct inter- and intra-individual differences in their language skills. The third chapter in Part 1, ‘Examining the Linguistic Coding Differences Hypothesis to Explain Individual Differences in Foreign Language Learning,’ holds special memories for me because I wrote the first draft on three separate airplane flights. For this theoretical manuscript, I expanded on the ‘Impact’ and ‘Cognitive Locus’ papers by reinforcing the notion of the AOS and arguing that conceptualization of L2 learning as a language-based undertaking would allow researchers to more clearly identify IDs in the language skills necessary for successful L2 learning and to develop research-based methodologies for teaching L2s. By that time, our research agenda was well under way and several studies had found that more and less successful L2 learners displayed significant differences in their L1 skills and L2 aptitude. In addition, we had just published our first empirical investigation on L2 anxiety, which found that postsecondary students with higher levels of anxiety displayed significantly lower levels of L1 achievement, L2 aptitude and

Part 1: Theoretical Insights into L1–L2 Relationships  19

L2 outcomes than students with lower levels of anxiety (Ganschow et al., 1994). As a result, I felt confident in proposing several ways that L2 researchers could either challenge, or falsify, the basic premises of the LCDH, specifically the notion that L2 learning is primarily a languagebased task and that differences in L2 achievement would be related to differences in L1 ability. Although L2 researchers have challenged the LCDH, its basic premises have not been falsified. The three chapters in Part 1 illustrate for the reader how we developed the LCDH and the insights gained from our early empirical studies. The papers provide a model for developing and supporting a hypothesis and how to modify one’s theoretical position when the data warrant such refinement. The papers also demonstrate how case studies can help researchers to develop a hypothesis but illuminate how empirical investigations are necessary to support the hypothesis. Because of space constraints, I have been unable to include an important paper, our rejoinder to Peter MacIntyre’s (1995) response to our ‘Cognitive Locus’ essay (both of which were published in The Modern Language Journal). In this case, the conversation about the centrality of language to L2 learning and MacIntyre’s discussion of L2 anxiety encouraged us to expand our investigations on the relationship between language skills and the L2 anxiety hypothesis, a research project that has now covered 25 years and is still ongoing (see Part 4). The discussion with MacIntyre verified our decision to modify the LCDH from ‘deficit’ to ‘differences,’ persuaded us that our focus on the phonological component of language was too narrow and should be expanded to include all components of language, and it encouraged us to investigate connections between L1 skills and the skills measured by L2 aptitude subtests. The three chapters included in Part 1 prepare the reader to appreciate the foundational assumptions of our research – that L2 learning is the learning of language and there are strong relationships between IDs in early L1 ability and IDs in later L2 aptitude and L2 achievement – and to understand our approach to investigations.

1 Searching for the Cognitive Locus of Foreign Language Learning Difficulties: Linking First and Second Language Learning Richard L. Sparks and Leonore Ganschow

Over the past few years foreign language (FL) educators have offered new explanations for FL failure in traditional classroom formats. These explanations have included affective variables, e.g. lack of motivation and high levels of anxiety, and, more recently, learning style differences and inefficient language learning strategies. In an article published in the 1991 Modern Language Journal (Sparks & Ganschow, 1991), we proposed an alternative to affective explanations for FL learning problems. The alternative, the FL Linguistic Coding Deficit Hypothesis (LCDH), posits native language difficulties as a possible cause of FL difficulties. The connection between L1 and L2 learning, though inferred in the FL research literature of the 1950s and 1960s (Carroll, 1958, 1990; Pimsleur, 1963, 1966a, 1968), has not been emphasized in recent years, nor have difficulties with L1 explicitly been stated as a cause of L2 learning problems. The LCDH derives from native language research on reading disabilities by Vellutino and Scanlon (1986), who examined the role of the linguistic ‘codes’ – phonology, syntax and semantics – among good and poor readers. They found that poor readers had difficulties with both phonology and syntax, although phonological coding was particularly weak. Considerable empirical evidence has supported the importance of phonological coding for efficient reading (Bradley & Bryant, 1985; Wagner & Torgeson, 1987), and poor readers have been found to lack ‘phonological awareness,’ or ability to segment 21

22  Part 1: Theoretical Insights into L1–L2 Relationships

phonemes within words (phoneme segmentation). In our research on high school and college FL learners, we have found that difficulty using a phonological code, in particular, seems to be the most common problem among unsuccessful FL learners who are otherwise successful in school. Our research evidence does not suggest that the FL problem learner has global, or general, language problems. The LCDH, which attempts to explain FL learning difficulties, is similar to recent models of reading because it acknowledges the importance of both ‘top down’ and ‘bottom up’ cognitive processes. That is, the LCDH speculates that FL learning difficulties might result from difficulties with phonology, syntax or semantics (or all three) (Sparks & Ganschow, 1993a). While the LCDH acknowledges the contribution of both ‘bottom up’ and ‘top down’ processes for FL learning, evidence suggests that the majority of poor FL learners are distinguished from good FL learners by phonological coding difficulties, which corresponds with findings in the reading literature on the problems of poor readers. In this theoretical paper, we explore further the view that FL learning difficulties are based on native language difficulties – the LCDH – and that the phonological code is the locus of learning difficulties for most poor FL learners. We draw heavily upon current native language research, in particular the literature in reading disabilities and speech perception. New to the present discussion are two concepts that heretofore have not been examined extensively in relation to FL learning: the assumption of specificity and modularity. Both further support our position that FL learning difficulties, like native language learning problems, are likely to result from a specific deficit in phonological processing. This chapter opens with a discussion of the theoretical basis for L1/ L2 linkages. We examine the assumption of specificity and modularity in the context of native language research on reading and speech perception and show how both relate to FL learning. We also explain why current global theories of language (e.g. auditory learning style, language learning strategies) and affective views of FL learning (e.g. motivation, anxiety) are incomplete. We then discuss implications for FL methodology and instruction for students with FL learning problems. Theoretical Basis for L1/L2 Link

The theoretical assumption underlying our position is that individuals who have difficulties in the rule systems of their first language are likely to have related problems as they begin to learn a second language. For example, if a student has poor phonological skill in the native language, concomitant difficulties will be experienced with the phonology of the FL. Skehan (1986) argues that there is a direct relationship between native language and FL learning and suggests that FL aptitude is ‘the second or FL equivalent of a first language learning

Searching for the Cognitive Locus of Foreign Language Learning Difficulties   23

capacity’ (1986: 200–201). Our view is that subtle or overt difficulties in the understanding of or inability to use the language codes are a likely cause of FL learning difficulties, whereas affective differences are a likely consequence of these language learning difficulties. Researchers have studied the effect of language aptitude on second language learning. In the 1960s John Carroll and Paul Pimsleur conducted extensive research on the language rule systems. Carroll, co-author of the Modern Language Aptitude Test (MLAT) (Carroll & Sapon, 1959), found that four variables – phonetic coding, grammatical sensitivity, inductive language learning ability, and rote memory – accounted for success or failure in FL learning in traditional classroom formats. Likewise, Pimsleur, who authored the Language Aptitude Battery (LAB) (Pimsleur, 1966b), found ‘auditory ability’ – which he defined as sound/symbol learning and sound discrimination – to be the factor that distinguished individuals with high intelligence who had FL problems but did well in their other subjects. In her research with adults in Canadian Public Service language training programs, Wesche (1981) found language aptitude tests such as the MLAT and LAB to be valid indicators of potential problems and special capabilities of students. Although their primary research was attitudes and motivation in L2 learning, Gardner and Lambert (1972: 56) concluded that ‘in general, our findings support Carroll’s way of conceptualizing language aptitude’. In our research, we have found both native language and FL aptitude differences among high school and college students who have failed or are struggling in FL courses. Initially, our interest in FL learning was generated by the difficulties of students with histories of native language problems, students with learning disabilities (LD). However, we quickly encountered students at the secondary and postsecondary levels struggling in FL courses but who were not LD. When these students were evaluated, most exhibited subtle or overt differences in oral or written native language skills but were not LD. Relative weaknesses were usually found in phonology while semantic skills generally remained unaffected. These students also scored poorly on the MLAT. Our findings with these students and our experiences in LD and reading disabilities resulted in empirical investigations supporting the hypothesis that native language learning difficulties play an important role in FL learning problems. Two concepts – the assumption of specificity and modularity – may help to explain a cause of FL learning problems and lend support to the LCDH. Assumption of Specificity

Attempts to explain FL learning problems have created the following paradox. Traditional explanations for FL learning problems, such as poor attitudes, low motivation, high levels of anxiety and inefficient language learning strategies, seem logical. Students with FL learning

24  Part 1: Theoretical Insights into L1–L2 Relationships

difficulties often seem unmotivated, exhibit inappropriate behavior, do not complete homework, fail tests and express embarrassment about talking in the FL. The paradox, however, is that although these traditional explanations make sense, they are likely to be consequences of a student’s basic difficulties with language rather than a cause of the FL learning problem. In our view, most classroom FL learning problems are language based. Our belief rests on what has been called in the reading disability literature the ‘assumption of specificity’ (AOS) (Stanovich, 1986a, 1988). The AOS proposes that students with reading disabilities who have average to superior intelligence have a cognitive deficit reasonably specific to the reading task, and which is thus language-related. According to the AOS, the cognitive deficit does not extend very far into other domains of cognitive functioning. If it were to do so, then these additional cognitive deficits would depress the constellation of abilities called intelligence, reduce the gap between IQ and reading, and the student would no longer be considered to have an unexpected reading problem – his/her reading problem would be predictable based on deficits in other cognitive domains and s/he would simply have low intelligence. When applied to FL learning, the logic of the AOS is straightforward. The student with average to superior intelligence who has FL difficulties has a deficit specific to the FL learning task which is language related and does not extend very far into other domains of cognitive functioning. Current views of FL learning are not compatible with the AOS in that most FL research has focused on global language learning skills/ strategies rather than specific cognitive variables. For example, Oxford (1990a) has suggested that inefficient language learning strategies are largely responsible for success or failure in learning a FL. In fact, researchers suggest that metacognitive awareness of available (learning) strategies, or metalinguistic awareness, is an important aspect of intelligence (Sternberg, 1985). Oxford herself alludes to this relationship when she states that ‘one of the most important sets of strategies, known as metacognitive strategies, involves noticing, evaluating, and improving one’s own performance, so metacognitive strategy use by definition embodies “intelligent behavior” …’ (1990a: 108). Linking FL learning problems to inefficient language learning strategies is likewise problematic because it infers that students with FL learning problems are generally deficient in dealing with cognitive tasks of all types. Yet research has shown that the overall cognitive abilities of FL problem learners are relatively intact. Affective theories present some special problems for the AOS. One is that these theories rely on self-report instruments for surveying affective differences. However, self-report instruments generally suffer from measurement problems and typically have the lowest validity of any testing instruments (Oller, 1981). Learning style instruments,

Searching for the Cognitive Locus of Foreign Language Learning Difficulties   25

in particular, have been found to have such problems (Kavale & Forness, 1987), and modality testing (and modality teaching) have been found in native language research to be neither reliable nor effective (e.g. Kampwirth & Bates, 1980; Tarver & Dawson, 1978). Oller has speculated that self-reported, affective instruments may well be unintentionally assessing language proficiency. Explanations that address affective and metacognitive functioning, conflict with the AOS. They are paradoxical because they intuitively make sense but do not provide adequate causal explanations. We propose that inefficient metacognitive strategies and affective differences are not the best places to look for the source of FL learning problems. Neither of these theories fulfills the AOS, which implies that the deficit underlying the FL learning problems is specific to language learning and does not disrupt a number of other cognitive skills. Modularity and FL Learning

If affective and metacognitive differences are not the best places to look for the cognitive locus of FL learning problems, what are the alternatives? The main premise of our argument is that the cognitive processing mechanisms underlying FL learning problems are likely to be modular in nature. Fodor (1983) has described modular systems as those that are fast, automatic and informationally encapsulated. For a mechanism to be ‘informationally encapsulated,’ it must operate autonomously, rather than under the direction of higher-level cognitive structures. The module is automatic in that it does not require conscious attention. It is fast in that it happens naturally and effortlessly. For FL learning, the important point is that modular processes are not strongly interactive with central processes. This means that a modular system may fail or function inefficiently without disrupting the operations of those central processes; likewise, efficiently functioning central processes will not remediate a deficient module. An example of the modularity concept in native language learning is the role of phonology in reading disability. A considerable body of evidence exists linking reading disability to a specific deficit in phonological processing, i.e. phonological module. This difficulty with phonology causes decoding difficulties, or problems with the sound– symbol system of the language, so that students cannot rapidly and efficiently decode words. In keeping with Fodor’s notion of ‘informationally encapsulated’ systems, reading-disabled students are not characterized by metacognitive or global language deficits: rather, they have a specific deficit localized in the ‘phonological core’ of language. Coincidentally, similar findings on phonological processing have appeared in the FL literature. Carroll (1962, 1981) and others (Gardner & Lambert, 1972; Wesche, 1981) have shown that FL aptitude tests

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measure abilities, such as phonetic coding, that are not tested by IQ tests but make unique contributions to FL learning. In a more recent article, Carroll (1990) referred to the association of poor phonetic coding ability with dyslexia (i.e. reading disability) and reiterated his earlier belief that phonetic coding and a ‘special type of memory for phonetic coding material’ (1990: 18) are important for FL learning. Phonological processing meets the criteria for both the modularity and AOS concepts. The readingdisabled student has a cognitive deficit that is specific to the reading task, which depresses reading ability but not other global language skills (AOS), and it neither directs nor is dependent upon global language skills (modularity). Likewise, the student with FL learning problems is likely to have a cognitive deficit that is specific to the FL learning task but does not affect overall cognitive functioning, thereby meeting the criteria for the AOS. The cognitive deficit is assumed to be modular – if it were not, the deficient module would depress the student’s overall cognitive functioning, causing language learning difficulties in many areas. If the deficient module were dependent upon efficiently functioning global language skills, it would not be deficient in the first place. So far we have described two concepts – the AOS and modularity – which we hypothesize are related to FL learning, and we have also hypothesized that the phonological module is largely responsible for FL learning problems. We turn now to research on native language learning problems in reading and listening/speaking and research on FL learning to support our hypothesis. Phonological Processing and Reading Disability

In the 1970s poor readers were thought to have visual or auditory processing deficits related to sensory modalities, creating specific ‘learning styles.’ However, research has neither supported the efficacy of these models nor have their recommended instructional procedures shown positive results (Kavale & Forness, 1990; Liberman, 1985). Since then, considerable research has shown that reading is a language-based skill (Adams, 1990) and pointed to lack of ‘phonological awareness’ as the primary problem of children who fail to learn to read (Liberman & Shankweiler, 1985; Stanovich, 1988). The relationship between phonological awareness and reading failure has been supported by studies in English and several other alphabetic orthographies. Much evidence exists to indicate that phoneme segmentation – the ability to separate a word into its constituent phonemes – is strongly linked to reading disability and plays a primary role in the speed of initial reading acquisition. More recent studies have shown that students who have phonological difficulties in their native language also have FL learning problems. We have conducted several studies with college and high school FL learners

Searching for the Cognitive Locus of Foreign Language Learning Difficulties   27

and all have yielded results supporting the LCDH, in particular the role of the phonological code. In early case study analyses of college students in FL courses, we found that many of these poor FL learners had a common deficit – a history of, and current difficulty with, reading and phonological difficulties. All the college students with phonological problems failed FL courses in the first or second semester (Sparks et al., 1989). In an empirical investigation at the postsecondary level, we found statistically significant differences in the phonological skills of successful/unsuccessful FL learners (Ganschow et al., 1991) but no significant differences on semantic measures (vocabulary). Significant differences were also found on all MLAT subtests. We obtained similar results in studies at the high school level. An empirical study with low-risk (LR) (A/B grades) and high-risk (HR) (D/F grades) FL learners in college preparatory courses and a first-year high school FL course found significant differences on both phonological and syntactic measures as well as all MLAT subtests and its Long Form (Sparks et al., 1992a). Again, no significant differences were found on semantic measures. In a related study we added a group of students with identified LD enrolled in first-year FL courses and compared them to the HR and LR groups on tests of native language and FL aptitude (Sparks et al., 1992b). No significant differences between the HR (non-LD) and LD groups were found on measures of phonology (phoneme segmentation, word decoding), syntax, and semantics (vocabulary, reading comprehension), and on the five subtests of the MLAT. Significant differences were found between the LR/HR groups on almost all measures of phonology and syntax and the MLAT. However, no significant differences were found between the LR/HR or the LR/LD groups on any of the semantic (global language) measures. A more recently completed study of high-, moderate- and low-anxiety college FL learners, identified through Horwitz’s Foreign Language Classroom Anxiety Scale (Horwitz et al., 1986), showed significant group differences on measures of phonology, reading, listening comprehension and FL aptitude (Ganschow et al., 1994). The groups performed similarly on the ACT/SAT college entrance exams; yet, highly and moderately anxious students scored significantly lower on the measures, and showed relative differences on subsequent FL grades (high anxious GPAs (grade point average) = 2.4; moderate anxious GPAs = 2.8; low anxious GPAs = 3.4). Results suggested that students with higher levels of anxiety have relatively weaker language skills, supporting our position that affective differences (low motivation, high anxiety) may be a result of, rather than the cause of, FL learning problems (Sparks & Ganschow, 1991). These findings with FL learners are consistent with research on good and poor readers and support our speculation that students with FL learning problems exhibit language problems similar to those displayed

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by students with reading disabilities and that the problems lie primarily in the phonological component of language but may be paired with concomitant difficulties in the syntactic code. Semantic difficulties, or language comprehension problems, do not seem to be the primary ‘core’ of most FL learners’ difficulties, although the LCDH speculates that there are students with FL learning problems with other types of linguistic coding problems, e.g. strong phonology/weak or strong syntax/ and weak semantics; weak phonology/weak syntax/weak semantics; or strong phonology/strong syntax/strong semantics. Phonological impairments may have an impact on learning to speak and listen to the FL. In native language literature, there is speculation of a strong correlation between reading/writing and listening/speaking skills. Effects of Phonological Deficits on Listening and Speaking

The relationship of oral language proficiency to subsequent native language academic deficits in written language is well documented (Wallach & Butler, 1984). Evidence indicates that preschool language impairments often result in later reading difficulties and that students who are poor readers often exhibit deficits related to speech perception. Brady et al. (1983) found that poor readers did not differ in the perception of nonspeech environmental sounds, but poor readers exhibited a deficit specific to speech perception and required a higher quality of signal than good readers for error-free performance in speech. Poor readers have been found to have difficulty with the comprehension of spoken sentences and to have problems with complex syntactic structures in both oral and written language (Byrne, 1981). In addition, poor readers make significantly more speech production errors than good readers and display verbal naming difficulties (Catts, 1986). This evidence shows that poor readers, most of whom have phonological deficits, also have difficulty with speech perception and production, and that earlier oral language difficulties may affect reading skills. One could hypothesize, however, that students with speech processing and production difficulties are those who exhibit affective differences, who fail to use efficient language learning strategies, or have global language deficits. Again, a paradox presents itself. Most students who are recommended for FL instruction appear to perceive (listen) and produce (speak) their native language so well that it seems logical to assume that FL learning difficulties are due to affective differences or inefficient language learning strategies. How can this paradox be resolved? More recently, native language researchers have speculated that the speech processing and production deficits of poor readers are due to phonological coding problems. Shankweiler and Crain (1986) hypothesize that poor readers have a ‘double handicap: poor decoding

Searching for the Cognitive Locus of Foreign Language Learning Difficulties   29

abilities and unusually constrained immediate memory. The handicap would be expected to show in processing spoken language …’; and they further speculate that ‘verbal working memory uses a phonological output code’ (Shankweiler & Crain, 1986: 163). Crain (1989) conducted research supporting the view that the spoken language comprehension failures of poor readers arise from limitations in phonological processing involving working memory. Mann and her colleagues (1984) found that the use of a phonetic memory code is important to sentence comprehension, and that poor readers misperceived spoken sentences which exploited prosodic cues but their misperception was due to processing limitations of phonological working memory capacity, not insufficient knowledge of syntax. Along this line of research, Liberman and Mattingly (1985) developed a theory of speech perception in which they make two claims: (1) speech perception and production are intimately and innately linked – that is, ‘what people hear when they listen to speech is what they do when they speak …’ (1985: 3) – and the link requires only exposure to speech to become solidified; and (2) objects of speech perception are the intended phonetic gestures of the speaker – that is, they call for movement of the articulators (lips, teeth, tongue, palates) through certain linguistically significant configurations. Liberman and Mattingly maintain their theory does not necessarily apply outside the speech domain and that it differs from ‘auditory’ theories which hypothesize there is no need to invoke a further specialization for language because ordinary auditory processes themselves are sufficient to explain the perception of speech. They view their theory as ‘radically different’ from auditory theories in that for them speech production is not explained by principles that apply to the perception of sounds in general, but is felt to be specialized for phonetic gestures. This specialization ‘prevents listeners from hearing the signal as an ordinary sound, but enables them to use the systematic, yet special, relation between signal and gesture to perceive the gesture’ (1985: 6). Liberman and Mattingly state that the relationship between signal and gesture is special because it occurs only in speech and not in nonspeech sounds. It is also systematic because of the process of coarticulation – overlapping and merging sounds – that is peculiar to speech. Liberman and Mattingly also relate their theory to the modularity concept developed by Fodor. They argue that their hypothesized phonetic module meets the criteria for modularity in several ways, primarily because it is domain relevant (to language), specialized, fast, mandatory, and informationally encapsulated. Crain (1989) extended the modularity concept and subdivided language into autonomous subcomponents: the lexicon, phonology, syntax, and semantics. Following Liberman and Mattingly’s theory and the supportive evidence to a logical conclusion, the solution to the paradox of why students who

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apparently listen to and speak their own language so well have difficulties with speech processing and the production of a FL is straightforward. Research has shown that children learn to listen to and to speak their native language to varying degrees. Their level of efficiency may be dependent upon a module specialized for speech processing and production that is related to reading acquisition. If both native oral (listening and speaking) and written (reading and writing) skills are dependent upon the efficient functioning of a phonetic module, it follows that listening to and speaking a second language will be difficult for students who have relatively weak phonological skills. Thus, a range of difficulties in both oral and written language may be linked to weaknesses in processing the phonological structure of language. Conclusions and Implications

Having reviewed literature on reading disability, the relationship between L1 and L2 learning, and the importance of phonological processing in oral and written language, we come to the central point of this chapter. If phonological problems cause difficulties with L1 learning, both oral and written, it seems plausible to speculate that phonological difficulties are likely to cause oral and written language problems in L2. Thus, we infer that an inefficiently functioning phonetic module that causes overt or subtle difficulties with the oral and written aspects of one’s native language could be responsible for FL listening and speaking problems, and we extend our hypothesis to include FL reading and writing. If there are subtle linguistic coding deficits in one’s first language system, it is reasonable to expect a second language system to suffer from similar deficits. This conceptualization of a phonological module deficit provides a useful framework within which to consider implications for FL instruction. We recommend three ways for students with phonological deficits to learn a FL. All three methodologies involve direct and explicit teaching of phonology in an attempt to remedy the inefficiently functioning phonetic module. They are suggested only for students who exhibit phonological difficulties. The methods are: (1) teaching the phonology of the FL when the student begins instruction; (2) teaching the phonology of the student’s native language before FL instruction begins; or (3) making certain that students learn the phonology of their native language in the primary grades during reading instruction. The first methodological approach has been described in several more recent publications (see Sparks et al., 1991). The approach – the Orton–Gillingham (O–G) method – has traditionally been used to teach disabled readers to read and write their native language. The O–G method subscribes to the direct and explicit teaching of phonology in a

Searching for the Cognitive Locus of Foreign Language Learning Difficulties   31

systematic, step-by-step manner. The student learns only a small amount of material at one time with frequent review and practice until mastery is demonstrated. The method also uses a multisensory approach, i.e. simultaneous listening + speaking + reading + writing. The second approach, teaching the phonology of the student’s native language before FL instruction, has been developed and implemented by Demuth and Smith (1987) at Boston University. They identified students with language problems through a process that included administration of the MLAT, and then offered an alternative sequence of courses designed to help the students achieve success in FL courses. The initial alternative course provided instruction in ‘articulatory phonics’ (practice in perception and production of English sounds), the ‘phonological process,’ morphology and syntax. The course was based on the assumption that ‘students with strong grounding in the structures of their native language will be more successful at transferring those skills to the learning of another language’ (1987: 77). A final recommendation is that the FL profession could support explicit teaching of native language phonology and phonemic awareness during reading instruction in the primary grades. The benefits of such instruction are obvious: young children will not only learn the phonological system of their native language but will learn to read their language more easily and efficiently. If a child learns to read well in the primary grades, the probability increases that s/he will read more frequently. Evidence shows that an efficiently functioning phonetic module has positive effects on speech perception and production, increasing the probability of transfer to FL learning. The drawbacks of not learning to read well in grades K-3 should also be apparent: poor readers will not have an efficiently functioning phonetic module. Thus, they will not read as much as good readers and they may have poorer speech perception and production, thereby increasing the probability of later problems in FL learning. Evidence of the need for early explicit instruction in phonology comes from the reading literature and has been described as ‘Matthew effects’ (Stanovich, 1986b). The term Matthew effects comes from the Gospel according to Matthew: ‘For unto every one that hath shall be given, and he shall have abundance; but from him that hath not shall be taken away even that which he hath,’ and is used to describe rich-get-richer and poor-get-poorer effects in education. In reading, the concept of Matthew effects has been used by Stanovich (1988, 1991) to illustrate how early success in phonological processing leads to faster reading achievement and independence. Higher levels of independent reading spawn further growth in reading comprehension with positive consequences for growth in vocabulary, syntactic knowledge, general information and general linguistic awareness. Poor readers who lack phonological processing skills cannot decode words effectively or efficiently. Because of slow and labored reading, they do

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not read as much and are not exposed to the greater number of words that good readers encounter. Stanovich (1988) has reviewed studies that show the large differences in word exposure of good and poor readers. Likewise, Juel (1988) has found that poor readers with phonological processing deficits made no gains in listening comprehension after second grade. These findings should concern FL educators. Poor phonological processing apparently may initiate Matthew effects to begin. If students do not have sufficient phonological skills in the primary grades, they will neither learn to read well nor will they read very much. The lack of reading experience, in turn, deters growth in the skills needed for success in FL learning–syntactic knowledge, vocabulary, listening comprehension and general linguistic awareness. The presence of Matthew effects helps to explain why students with FL learning difficulties who have phonological processing problems may not use the efficient language learning strategies employed by ‘good’ language learners. Stanovich and others have pointed to the need for successful early development of reading skills to avoid the cascade of interacting achievement and motivational side effects that are the result of reading failure. Likewise, the motivational and attitudinal side effects of being placed in an FL classroom without the prerequisite skills necessary for success when learning a new language can be overwhelming for some students. Many new FL learners undoubtedly suffer from anxiety in the FL classroom. Affective strategies which lessen anxiety and create a more positive attitude may be a comfort to many of these students. Instructional approaches such as the use of language learning strategies, or metacognitive training, may help some students function more effectively on a day-to-day basis. However, the persistent failure of the phonetic module will have a negative and sometimes debilitating effect on students’ attempts to master the FL. On the other hand, identification of native language deficits may result in a more appropriate matching of students with methodological approaches that have the potential to increase FL proficiency. Acknowledgement

A version of this chapter was published as: Sparks, R. and Ganschow, L. (1993) Searching for the cognitive locus of foreign language learning difficulties: Linking first and second language learning. Modern Language Journal 77 (3), 289–302.

2 The Impact of Native Language Learning Problems on Foreign Language Learning: Case Study Illustrations of the Linguistic Coding Deficit Hypothesis Richard L. Sparks and Leonore Ganschow

Introduction

The LCDH was initially proposed as a plausible explanation for the FL learning problems of students with LD (Sparks et al., 1989). Since then, the authors have encountered large numbers of students not diagnosed as having LD but exhibiting FL learning difficulties. Like Pimsleur’s FL ‘underachievers,’ these students achieve average and above average grades in their other subjects, yet struggle in FL courses (Pimsleur et al., 1964). The term ‘linguistic coding’ was selected by the authors of the LCDH to refer to the deficiencies of students with LD who display subtle or overt difficulties with the oral and written aspects of language. The authors of the LCDH speculate that inefficiency in the language components – phonological, syntactic, semantic – rather than affective variables (attitude, motivation) causes individual differences in FL learning. Instead, affective differences result from native language learning difficulties and further impact FL learning. Rote memory difficulties also seem to exacerbate FL learning problems. More recent studies find that both LD and non-LD students exhibit similar linguistic coding problems, and that their native language skills significantly differ from successful FL learners in both high school and college (e.g. see Ganschow et al., 1991). 33

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Initially, case studies showed that there might be a native language basis for FL learning problems. In 1986 Ganschow and Sparks described case studies of four college students unable to fulfill the FL requirement. Each student was interviewed to obtain background, family history, developmental and academic histories, and self-reports about FL learning difficulties, then administered an extensive psychoeducational evaluation that included reading, spelling, writing, and oral language measures. Findings suggested that all four students had problems with listening comprehension and concomitant difficulties with an audiolingual teaching approach. Interviews also revealed histories of native language learning problems (reading, spelling, early speech/ language problems) extending beyond FL learning. These findings supported Dinklage’s (1971) observations of students at Harvard who had FL learning problems. In 1989, Sparks, Ganschow and Pohlman analyzed the profiles of 22 college students who received a waiver from their university’s FL requirement. Each student was administered a battery of psychoeducational instruments, including an IQ test. Results indicated that although the IQs of the students were in the average to superior range, they displayed subtle phonological, syntactic, and/or semantic coding difficulties. Of the 22 students, 14 had difficulties with all three linguistic codes, but 2 students had difficulty only with semantic coding. When each student’s FL course failure history was compared to his/her psychoeducational test profile, a pattern emerged suggesting phonological coding problems had an immediate impact on the student’s performance in the FLs. Of the 14 students who evidenced phonological difficulties, all but one was unable to pass second semester FL courses, and 7 were unable to pass the first semester. However, 7/8 students with only syntactic and semantic difficulties were able to pass both first and second semester FLs before failing in the first semester of the second year. Although not all 22 students were diagnosed LD, each exhibited a testing profile reminiscent of students who receive this diagnosis. FL educators have speculated about the language-based nature of FL learning and FL learning problems. Carroll (1962, 1968) suggested that native and FL learning are similar in that they require the capacity to reproduce and remember sounds and use grammatical rules. Oller (1981) speculated that similarities between native and FL learning outweigh the differences between the two. Carroll and Sapon (1959) developed a FL aptitude test, the Modern Language Aptitude Test (MLAT), which identifies four language-based components of FL learning: (1) phonetic coding; (2) grammatical sensitivity; (3) inductive language learning ability; and (4) rote memory. Pimsleur also developed a test of FL aptitude: the Language Aptitude Battery (LAB) (1966b). One component of his test, auditory ability, or the ability to perform sound–symbol and sound discrimination tasks, is similar to Carroll’s phonetic coding

The Impact of Native Language Learning Problems on Foreign Language Learning  35

component and phonological coding for decoding words described in native language reading research. Pimsleur also found auditory ability to be the component accounting for difficulties in FL learning not explained by low intelligence, poor verbal skills or lack of motivation. Empirical studies on the LCDH construct have revealed language differences between good and poor FL learners. In one study Ganschow et al. (1991) compared college students who earned A/B in two semesters of college-level FL courses with unsuccessful students who failed and received a waiver from the college’s FL requirement. No significant differences between the groups were found on intelligence, reading comprehension and vocabulary (semantic) measures, but significant differences were found on measures of phonology (word decoding, spelling) and syntax (grammar, writing). Significant differences were also found on the MLAT and its five subtests, supporting a study by Gajar (1987) with LD and non-LD students in college FL courses. The results of this study supported the LCDH and corroborated speculations that students with FL learning difficulties exhibit deficiencies primarily in the phonological and syntactic, but not semantic, codes of their native language. In order to test their hypothesis that affective factors in FL learning (low motivation, poor attitude, high anxiety) are the result of languagebased learning difficulties, Javorsky, Sparks and Ganschow (1992) surveyed the self-reports of students with/without LD about their FL skills and attitudes. Results showed that college students with LD perceive themselves as less capable and possessing fewer skills to master the oral and written language requirements of FL courses. However, no differences in motivation to learn a FL were found between the two groups. The findings supported the authors’ speculation that the FL difficulties of students with documented language learning problems may stem from difficulties with their native oral and written language, and that affective differences may be a natural consequence of being asked to perform language tasks in a new and unfamiliar linguistic coding system. Several studies with high school at-risk FL populations corroborate findings on college learners. For example, Sparks et al. (1992a) compared low risk (LR; A/B in first quarter) and high risk (HR; D/F in first quarter) learners in first-year high school FL courses identified by an informal screening instrument (Ganschow & Sparks, 1991). Both groups were administered measures of oral and written native language, the MLAT, and an IQ measure. Significant differences between the groups were found on all measures of native language phonology, most measures of syntax, and the MLAT, but no differences were found on any of the native language measures of semantics (e.g. vocabulary). Another study compared three populations of FL learners on native and FL measures and a cognitive ability test (Sparks et al., 1992b). The populations

36  Part 1: Theoretical Insights into L1–L2 Relationships

included HR and LR students as well as students with LD identified by their school based on state guidelines for this diagnosis. All the students were enrolled in a college preparatory level of courses and a first-year FL course. Significant differences between the LR and HR students were found on most measures of phonology and syntax but not on semantic measures. Significant differences between the LR and LD groups were found on all measures of phonology and most measures of syntax; however, no differences were found on semantic measures of reading comprehension and vocabulary. Importantly, only spelling and word recognition tests, both phonological tasks, distinguished the HR and LD groups. On the MLAT, significant differences between the LR/HR and LR/LD groups were found, but no differences were found between the HR and LD groups. In a more recently completed study (Sparks, Ganschow, Pohlman et al., 1992c), pre- and post-tests of native language and FL aptitude were administered to three classes of students identified as HR (both LD and non-LD) for FL learning by their schools and enrolled in separate sections of first-year Spanish. Many of these students had been identified as LD and all had experienced difficulties in reading, spelling and writing their native language. Two classes were taught Spanish with an approach used to teach dyslexic/LD students to read and write their native language: the Orton–Gillingham (O–G) method (Gillingham & Stillman, 1960) that directly and explicitly teaches the sound–symbol system (phonology) and grammar (syntax) of Spanish. The third class used a more traditional approach to FL learning, focusing on a ‘natural communication’ methodology. Results showed that the groups taught using the O–G approach made significant pre-post-test gains on most of the phonological tasks, thus improving their English word and pseudoword decoding and phoneme segmentation skills, and their vocabulary and verbal memory skills. Significant pre-post gains also were made by the O–G group on the MLAT. The group that had been taught using a more conventional approach to FL learning showed no significant pre-post-test differences on any of the native language (English) measures or the MLAT. The studies described here provide emerging support for the LCDH and are provocative for several reasons. First, they suggest that difficulties with the semantic code may not be primarily responsible for the FL learning difficulties of HR and LD students. Second, results suggest that HR students not diagnosed as LD and a group of students with LD perform similarly on native language and FL aptitude measures. Third, efficiency of the linguistic codes, rather than affective variables, may be responsible for success or failure in FL courses. Fourth, consistent with native language (L1) reading research, findings implicate the phonological and syntactic codes as potential causal factors in the FL learning difficulties of HR and LD students. Fifth, phonological

The Impact of Native Language Learning Problems on Foreign Language Learning  37

measures such as spelling, phoneme segmentation and pseudoword recognition appear to be strong native language discriminators of potential FL difficulties. Last, preliminary evidence supports a position that direct instruction of the FL’s phonology and syntax might benefit students with difficulties in these linguistic codes. Case Studies

Through their interviews of more than 200 good and poor FL learners, the authors have observed students with distinct linguistic coding profiles. Applying the ideas underlying the LCDH to these individuals, we infer that language learning runs along a continuum from very good to very poor, FL problems run on a continuum from mild to severe, and that linguistic coding problems will affect both native and FL learning. For example, a student with FL learning problems might display a broad range of linguistic coding deficits (phonology + syntax + semantics) while another student might have a very specific deficit (phonology only). Both students will exhibit FL learning difficulties; however, the severity depends on the degree to which the linguistic codes are affected. The most successful FL learners are those who have strong skills in all the linguistic codes. Through analyses of these 200 individuals, five ‘prototypes’ of FL learners have emerged: (1) the LR student with high phonology, high syntax and high semantics; (2) the HR student with low phonology, average syntax and high semantics; (3) the HR student with high phonology, high syntax, and low semantics; (4) the HR student with low phonology, low syntax and low semantics; and (5) the unmotivated (or anxious) student with average to high skills in phonology, syntax and semantics. These ‘prototypes’ are presented here. Each contains a short history of the students and their test scores on oral and written native language measures, the MLAT, and an IQ test. The testing measures are described in Appendices A and B. Dave: High phonology, high syntax, high semantics

Dave was a 20-year-old junior majoring in FL and English Literature at a competitive US university. He earned As and Bs throughout his schooling, and excelled in reading, spelling and math. Dave’s SAT (college entrance) scores were above average in both Verbal and Math. Both parents had doctorates and had done well in FL courses (Latin and

38  Part 1: Theoretical Insights into L1–L2 Relationships

German). Dave had an older sister in graduate school who had also done well in FL study. Dave’s full scale IQ score was in the upper end of the average range (Standard Score, or SS = 107). The results of native language measures showed strong skills in all linguistic coding areas. On phonological measures (spelling, word and pseudoword decoding), Dave achieved in the above average to superior range (SS range = 109–133). On syntactic measures (grammar, writing), he achieved in the average to above average range (SS range = 109–116). On semantic measures (reading comprehension, vocabulary, oral expression, listening comprehension), he achieved in the above average to superior range (SS range = 107–131). Dave displayed above average skills on a test of rote memory (SS = 123), and FL aptitude testing on the MLAT revealed average to superior scores (SS = 105–138). Table 2.1 depicts Dave’s standardized testing profile. Dave’s profile is that of a strong FL learner with no linguistic coding deficits. He had achieved grades of A and B in all college-level FL courses. Nick: Low phonology, average syntax, high semantics

Nick was evaluated for persistent difficulties with written language and problems with FL learning. He was 14 years old and a freshman in high school Spanish, which he was failing despite peer tutoring. A learning history revealed that he had earned Bs and Cs in all elementary and middle school subjects. Nick received tutoring for reading in the intermediate grades and had persistent difficulty with spelling. He excelled in science and won prizes at science fairs. He understood mathematical concepts easily. He said that Spanish courses ‘did too much at one time.’ His father had a postgraduate degree in the sciences and his mother completed college for nursing. Neither of his older siblings experienced difficulties with FL learning. Nick’s full-scale IQ was in the superior range (SS = 123) with strengths on oral vocabulary and visual–spatial (nonverbal) ability. On phonological measures, Nick demonstrated average to below average skills (SS range = 75–98) with specific difficulties in spelling and pseudoword recognition. On syntactic measures, Nick achieved in the lower to upper end of the average range (SS range = 90–109). His scores on semantic measures were in the above average to superior range (SS range = 118–127), and his rote memory skills (SS = 119) were also above average. FL aptitude testing (MLAT) yielded average to low average scores on the Long (SS = 92) and Short (SS = 89) Forms, and below average scores on the two subtests measuring phonological skills (Phonetic Script, SS = 78 and Spelling Clues, SS = 73). Nick’s profile is similar to most students with FL learning problems described in the literature to date. He exhibited a specific deficit in the phonological code with average syntactic and strong semantic skills.

The Impact of Native Language Learning Problems on Foreign Language Learning  39 Table 2.1  Summary of test scoresa Intelligence

Dave

Nick

Ed

Ken

Amy

Verbal

105

123

123

90

118

Performance

111

118

105

90

120

Full Scale

107

123

117

89

121

WRMT Word Identification

109

96

105

80

100

WJPB Word Identification

111

98

113

81

108

WRMT Word Attack

123

90

104

92

106

WJPB Word Attack

114

91

119

85

122

WRAT–R Spelling

119

90

109

88

111

GFW Spelling of Sounds

133

88

102

92

106

WJPB Dictation

113

89

109

84

123

WJPB Spelling

113

75

120

87

125

WJPB Written Language

116

90

119

91

125

WJPB Proofing

109

99

128

94

116

WJPB Punctuation

110

109

114

94

108

WJPB Usage

109

98

133

103

109

TOWL–2 (Total Test)

114

106

116

83

106

TLC–E Listening Comprehension

115

127

103

73

103

TLC–E Oral Expression

131

118

88

73

109

WRMT–R Word Comprehension

121

124

109

85

120

WRMT–R Passage Comprehension

125

120

114

84

114

WJPB Passage Comprehension

107

122

114

81

109

PPVT–R (Vocabulary)

117

126

106

83

121

WJPB Antonyms–Synonyms

112

121

115

85

122

123

119

98

98

112

MLAT Long

120

92

79

80

110

MLAT Short

120

89

83

90

114

MLAT–I (Number Learning)

126

103

91

76

120

MLAT–II (Phonetic Script)

124

78

74

72

112

MLAT–III (Spelling Clues)

138

73

79

120

98

MLAT–IV (Words in Sentences)

120

98

85

76

90

MLAT–V (Paired Associates)

105

91

73

96

100

WAIS–R/WISC–R

Phonological

Syntactic

Semantics

Memory WJPEB Memory Cluster Foreign Language Aptitude

All scores reported in standard scores (SS), M = 100, SD = 15 (Average range SS = 85–115).

a

40  Part 1: Theoretical Insights into L1–L2 Relationships

The LCDH speculates that deficiency in the phonological code will have an immediate negative impact on FL learning, even when syntactic and semantic codes are functioning efficiently. Nick eventually failed the first-year Spanish course. He re-took the course in summer school and passed. When contacted for follow-up, he was failing second-year Spanish. Ed: High phonology, high syntax, low semantics

Ed was a 15-year-old sophomore in a public high school who had failed the first quarter of first-year Spanish and was currently failing the second quarter. Ed’s early speech had been delayed, he had difficulty learning to read, and was tested by an educational specialist in the first grade. Ed received tutoring during elementary school and achieved average grades, although he still struggled in math and grammar. In a private elementary school where study of French was required, he ‘always flunked.’ Additional testing in the fifth grade showed that reading skills had improved, but Ed’s listening comprehension and oral expression skills were below average. Language therapy and continued tutoring were recommended. Ed exhibited strengths mostly in non-academic areas such as art. His father, a medical professional, was a good reader but a self-described poor speller. His mother, also a professional, had few academic difficulties in high school and college. His younger sister was doing well academically. Ed’s full-scale IQ was in the above average range (SS = 117) with superior social judgment and verbal reasoning. On phonological measures, Ed demonstrated average to above average skills (SS range = 104–20) with strong spelling. He obtained above average to superior scores on written syntax tests (SS range = 114–33). On semantic tasks, Ed displayed a varied profile, with above average skills on vocabulary (SS range = 106–15) and reading comprehension tasks (SS = 114) but average to low average skills on oral language tasks such as listening comprehension (SS = 103) and oral expression (SS = 88). Further assessment of oral language skills revealed difficulties in listening comprehension (SS = 76). Testing records from the fifth grade revealed problems in both listening comprehension (SS = 91) and oral expression (SS = 87). FL aptitude testing yielded low scores on all MLAT subtests (SS range = 74–91) and both the Short (SS = 83) and Long (SS = 79) Forms. Ed’s profile depicts a student with strong phonological and syntactic skills but with semantic weaknesses in specific language areas – listening comprehension and oral expression. A closer investigation of the semantic measures revealed stronger skills on tests of reading comprehension, written language, and single word vocabulary tasks but weaker skills on measures of oral expression. Ed’s strong vocabulary skills did not appear to compensate for his difficulties with extended

The Impact of Native Language Learning Problems on Foreign Language Learning  41

listening and speaking. When interviewed about his performance on the MLAT, Ed stated that the test was hard because ‘it took me a while to figure out the directions … the guy spoke too fast’ and there was ‘no time to think about what he said.’ Because of his stronger phonological skills, Ed could understand and pronounce single words in the FL. His self-reported problems in the FL classroom were with listening comprehension and oral expression. In the reading and LD literature, Ed’s profile is representative of a minority of students who exhibit no difficulty with phonology but have difficulty with oral expression and language comprehension. To date, the authors have found few students with FL learning difficulties who exhibit this profile. Ken: Low phonology, low syntax, low semantics

Ken graduated from a public high school and decided not to attend college after graduation. He had been working for a year but now wanted to attend college. Because Ken had experienced academic difficulties in both elementary and high school, he requested assessment before enrolling in school. He obtained average grades in elementary and middle school but received tutoring in reading each year and speech therapy for one year. His overall high school GPA was in the D range in a general track of courses. He had failed English I and Spanish I in his junior year. Ken’s college entrance scores were well below the lower end of the average range. He described himself as a ‘poor’ reader and speller, but he did ‘fine’ in arithmetic. His strengths were in athletic and social skills. Both parents had associate (2-year) college degrees. Neither parent recalled taking a FL in high school or college. All his siblings were earning average grades in school. Ken’s full-scale IQ was in the low end of the average range (SS = 89). On phonological measures, Ken achieved scores in the below average to low average range (SS range = 80–92). His scores on syntactic measures were in the average to below average range (SS range = 83–103). Semantic skills were weak and in the below average range on most measures (SS range = 73–85), with deficits in listening comprehension and oral expression. Rote memory skills were in the average range (SS = 98). FL aptitude testing revealed low average to below average scores on both the Long (SS = 80) and Short (SS = 90) Forms. Ken’s profile reveals poor skills in all three linguistic codes and is reminiscent of other high school students evaluated by the authors. His native language test scores were relatively consistent across the linguistic codes, i.e. low average range. For this type of poor FL learner, the LCDH would predict FL learning difficulties based on low to below average performance in cognitive ability and native language linguistic coding skills.

42  Part 1: Theoretical Insights into L1–L2 Relationships

Amy: High phonology, high syntax, high semantics, low motivation

Amy was evaluated because of academic problems in school. She was a 15-year-old freshman earning mostly Cs, Ds and Fs, and her lowest grades were in first-year Spanish. Her learning history revealed that she had received mostly Bs and Cs in elementary and junior high school. Her parents indicated that she was placed in low-achieving groups because she would not complete homework and in-class assignments or would finish work ‘at the last minute.’ She exhibited her best performance in English courses and enjoyed reading and creative writing but disliked math. She exhibited significant strengths in individual athletics. Amy’s father was a professional who had not done well in FL study. Her mother was a college graduate with no FL learning difficulties. Amy’s three siblings were good students. An older sister had done well in FL courses. Amy’s full-scale IQ was in the above average range (SS = 121). The results of the testing showed strengths in all native language skills. On phonological measures, Amy exhibited average to superior skills (SS range = 100–125) and exhibited strengths in spelling and the phonetic analysis of words. On measures of syntax, she achieved scores in the average to superior range (SS range = 106–125). Semantic skills also were in the average to superior range (SS range = 103–122), with strengths in reading comprehension and vocabulary. Rote memory skills were in the high average range (SS = 112). FL aptitude testing revealed average to above average scores on the MLAT Long (SS = 110) and Short (SS = 114) Forms. Amy’s test profile is one seldom observed by the authors, who would call her an ‘unmotivated learner.’ She is reminiscent of the type of students with low motivation and poor attitudes described by FL educators (Gardner, 1985a). While Amy might be a student with the type of anxiety described by Horwitz et al. (1986), she did not have problems specific to FL learning; instead, Amy achieved low grades in all courses. This academic profile suggests that any anxiety would be generalized across subjects not specific to FL learning. Most students with Amy’s linguistic coding profile typically perform well in FL courses. Students like Amy, with strong phonological, syntactic, semantic and rote memory skills, combined with average to above average FL aptitude, who are not doing well in a FL course generally are not performing well in most of their other high school or college courses. Like Amy, most exhibit low motivation and a negative attitude about school. Amy eventually passed the Spanish course with a grade of D. Her final grades that year were all Cs and Ds. Summary and Implications

We have examined research supporting the idea that linguistic coding differences (phonology, syntax and semantics) are a plausible cause of

The Impact of Native Language Learning Problems on Foreign Language Learning  43

FL learning difficulties, i.e. the Linguistic Coding Deficit Hypothesis (LCDH). Case studies illustrating five prototypes of FL learners who exhibit varying profiles in these codes were presented. What are some of the implications of this prototype analysis for FL educators? One implication is that FL educators should consider cognitive explanations, rather than focusing primarily on motivational and attitudinal explanations, for students with inordinate difficulty mastering FL skills in their classrooms. These cognitive explanations relate to basic language skills and include possible problems with the phonology, syntax and/or semantics of the language. Second, FL educators should examine closely poor FL learners’ phonological skills. Asking the student to repeat FL words and noting the way s/he pronounces them is one informal diagnostic indicator. Asking the student to count the number of phonemes in a native language word (phoneme segmentation) or say a word without an initial, final or medial phoneme (phoneme deletion) are other diagnostic techniques. Having the student read native language pseudowords is also an indicator of phonological skill. If the student has difficulties with these tasks, s/he may need more specific instruction to learn the FL. Third, if the student has phonological problems, the FL teacher should consider using teaching methodologies that emphasize instruction beginning with the sounds and symbols of the target language. Direct teaching of phonology may enhance a student’s ability to learn the FL just as direct teaching of the sound/symbol system improves reading ability. Fourth, FL teachers should be aware of the subtypes (prototypes) of at-risk FL learners reviewed in this chapter. Though most poor FL learners will likely have difficulties at the phonological level, there are some who have difficulties in the other linguistic codes with intact phonology. For learners with rather specific processing difficulties that do not involve phonology, compensatory strategies may prove beneficial. For example, had Ed been allowed to slow his pace of learning to compensate for his weaker listening and speaking abilities, he might have been able to improve his FL performance. Some students have been able to pass several semesters of the language if allowed to use compensatory strategies, e.g. reading instead of speaking the language. Last, FL teachers should utilize existing tools for identifying at-risk learners. A battery of tests for identifying potential FL difficulties has been described in the literature (Sparks et al., 1989). A typical battery should include measures of phonology (pseudoword recognition, spelling, phoneme segmentation), syntax (written grammar), semantics (vocabulary, reading comprehension, oral language), and FL aptitude. The results of the MLAT should be analyzed not only by the total score but also by its subtests in order to identify a learner’s linguistic coding strengths and weaknesses.

44  Part 1: Theoretical Insights into L1–L2 Relationships

Investigations with good and poor FL learners have led the authors to conclude that they are a heterogeneous group with language skills running along a continuum from very strong to very weak. Poor FL learners will have some degree of linguistic coding ‘inefficiency’ in their native language that contributes to the difficulties in a FL. Some are likely simply to show low overall cognitive ability, in which case their FL performance is commensurate with their performance in other academic areas. A few are likely to demonstrate low motivation and/or high levels of anxiety which may interfere with their FL performance. FL educators should consider possible language-based causes of FL learning difficulties. Hopefully, recognition of student differences in performance in the linguistic codes will enhance educators’ understanding of FL failure and assist them in their teaching. Acknowledgement

A version of this chapter was previously published as Sparks, R. and Ganschow, L. (1993) The impact of native language learning problems on foreign language learning: Case study illustrations of the Linguistic Coding Deficit Hypothesis. Modern Language Journal 77, 58–74.

3 Examining the Linguistic Coding Differences Hypothesis to Explain Individual Differences in Foreign Language Learning Richard L. Sparks

Introduction

In the 1960s Paul Pimsleur (1968: 102) suggested that ‘auditory ability’ distinguished ‘... students who achieved normally from those who were underachievers’ in foreign language learning and that this factor was ‘...often responsible for differences in people’s ability to learn foreign languages which could not be explained by [low] intelligence or motivation’. He included auditory ability in his test of FL aptitude: the Language Aptitude Battery (LAB) (Pimsleur, 1966b). The LAB measures auditory ability through sound discrimination and sound–symbol association tasks. John Carroll, too, recognized the importance of the sound system of language. Through factor analytic studies, Carroll found four independent variables, one of which was ‘phonetic coding,’ that were predictive of FL learning aptitude (Carroll, 1962). On the Modern Language Aptitude Test (MLAT) (Carroll & Sapon, 1959), phonetic coding skill is measured by a subtest, Phonetic Script, which requires the student to identify relationships between English sounds presented aloud in nonsense symbols and the phonetic transcription of a new language. These hypotheses about individual differences in the phonological aspects of language were not investigated vigorously by FL researchers in the 1970s or 1980s. Instead, they focused on affective variables in FL learning. For example, Gardner and his colleagues (Gardner, 1985a; 45

46  Part 1: Theoretical Insights into L1–L2 Relationships

Gardner & Lambert, 1972) hypothesize that learners’ motivation for and attitude toward FL study plays a causal role in FL learning success or failure. Horwitz and others (Horwitz et al., 1986; MacIntyre & Gardner, 1991) speculate that an anxiety specific to FL learning hinders acquisition of the FL. Krashen (1982) hypothesizes that an ‘affective filter’ makes an individual less responsive to language input, making the learning of a FL difficult. Ehrman (1990) suggests that personality type variables (e.g. learning styles, Myers-Briggs Indicators) are partially responsible for successful/ unsuccessful FL learning, and Oxford (1990a) focuses on students’ failure to use effective language learning strategies and the role of cognitive styles. While FL researchers have demonstrated that correlational linkages between these affective variables and successful FL learning are stronger than others, no single variable, or variables, have been found to account for successful/unsuccessful FL learning. In addition to affective variables, FL researchers, especially those trained in linguistics, have generally downplayed the role of language aptitude differences for learning a FL. For example, Gass and Selinker (1994: 233) write: ‘... linguists are uncomfortable with any claim of significant differences in native language ability’. They recognize that some individuals are better than others in certain language skills but report that linguists tend not to search for individual differences in language skills because they believe ‘all normal children learn language in roughly the same way and within the same time frame and because there is equipotentiality in language’ (1994: 234). They also suggest that individual differences in language aptitude may be the result of ‘social and societal backgrounds.’ Largely because of lack of focus on language aptitude differences and the idea that FL aptitude tests are associated with intelligence, these tests have fallen out of favor with FL educators. More recently, Leonore Ganschow and I have revived the speculations of Pimsleur, Carroll and others about the importance of native language skill and language aptitude differences in FL learning, through the Linguistic Coding Differences Hypothesis (LCDH) (Sparks & Ganschow, 1991, 1993a; Sparks et al., 1989). The hypothesis derives its name from native language research in reading (Vellutino & Scanlon, 1986) showing that students with reading problems exhibited deficits primarily in the phonological and syntactic components of language. In the LCDH, we hypothesize that FL learning is built upon native language skills; that is, an individual’s skill in the native language components – phonological, syntactic, semantic – serve as the foundation for successful FL learning. Further, we posit that both native and FL learning depend on basic language learning mechanisms and that problems with one language skill, e.g. phonological processing, will have a negative effect on both language systems. The focus of the LCDH is on language variables because FL learning is the learning of language.

Examining the Linguistic Coding Differences Hypothesis to Explain Individual Differences  47

In this chapter, I further develop views that: (1) most students with FL learning problems generally have academic problems specific to FL courses rather than with all academic courses; (2) FL learning problems are based on overt or subtle difficulties with native language learning; and (3) problems with native language phonological processing could be a locus of FL learning problems for some poor learners. First, I review evidence supporting the positions that FL learning problems result from language-related deficits and that an important language difference between good and poor FL learners, phonological processing, can contribute to FL learning problems. Then, I review research supporting the LCDH. Last, I posit that some FL learning theories are in conflict with the LCDH because their proposed causal mechanisms are not specifically language related and I present several arguments showing how FL theorists could invalidate the LCDH. I conclude with implications for researchers investigating reasons for FL learning problems. Relating the LCDH to Problems with Native Language Learning

Research supports the importance of native language learning skills for FL learning and the concept of language aptitude differences. For example, Humes-Bartlo (1989) finds that poor FL learners show mild deficits in native language skills compared to good FL learners and suggests that their ‘low but not pathologically low scores on L1 tasks suggest a language processing system which is adequate for L1 but is overloaded by L2’ (1989: 51). In a study conducted in England, Skehan (1986: 196) reports that children who ‘make more rapid progress in their first language tend to do better in foreign language learning at school’. Skehan also supports the concept of language aptitude differences and suggests that one effect of linguistics on FL theory has been that educators question the language aptitude concept developed by Carroll in his Model of School Learning (Carroll, 1963). The model proposes that FL learning is affected by individual differences in language abilities and instructional variables (time, teaching methodologies). Skehan speculates that more recent emphases on universals of language processing (how all learners are alike) and communicative approaches to language instruction (global techniques of language instruction) have reduced the importance of individual differences in language learning. He argues that hypothesizing aptitude to be important only for formal (classroom) learning contexts is misconceived and that aptitude is important in both formal and informal learning situations. The LCDH was originally conceived to explain problems that students with learning disabilities (LD) encounter in FL learning (Ganschow & Sparks, 1986). Students with LD have subtle/overt deficits

48  Part 1: Theoretical Insights into L1–L2 Relationships

in native language oral and written skills and exhibit a discrepancy between their IQ and specific academic skills (e.g. reading, writing). However, research by the author and his colleagues has shown that more students without LD experience significant problems in FL learning, and that successful/unsuccessful FL learners in secondary and postsecondary education exhibit differences in native language skills (Ganschow et al., 1991, 1994; Sparks & Ganschow, 1993b, 1993c, 1995b; Sparks et al., 1992a, 1992b, 1992c) In these studies, differences have been found in students’ abilities on phonological processing skills, e.g. reading and spelling words, reading pseudowords, manipulating sound segments in words. Generally, good and poor FL learners do equally well on semantic and IQ measures, but students with phonological problems are likely to experience immediate difficulty in the FL (Sparks & Ganschow, 1991, 1993b; Sparks et al., 1989); students with intact phonological processing skills but weaker semantic ability experience difficulty with later FL learning (Sparks & Ganschow, 1993a; Sparks et al., 1989). We have suggested that language learning occurs along a continuum from very good to very poor language learners, and that there is not a discrete entity such as a ‘foreign language learning disability’ (see Sparks & Ganschow, 1995a). Relating the LCDH to the Phonological Deficit Hypothesis in Reading

Much native language research has shown that poor readers and students with reading disabilities display specific deficits in the phonological domain of language (see reviews Stanovich 1986a, 1988). In the native language literature on reading, there is a growing emphasis on the impact of individual differences in basic phonological processing (see Liberman et al., 1989; Wagner & Torgesen, 1987). For example, Stanovich (1988) reviews evidence showing that phonological processing measures predict reading ability better than intelligence tests, and that phonological processing skill is relatively dissociated from IQ. In addition, more recent research has not supported the validity of discrepancy-based models of reading disability (Stanovich, 1991). Fletcher et al. (1994) find that phonological measures are ‘robust indicators’ of differences between reading-impaired children, and are significant predictors of differences between children with/without impaired reading no matter how reading disability was defined. Stanovich and Siegel (1994) find that reading-disabled children with and without IQ- achievement discrepancies do not differ in the skills that determine word decoding, the primary deficit in reading disability. There is also evidence showing that children with reading problems have deficits in speech perception and production (Butler, 1988; Catts, 1986), and that these deficits are due to phonological processing problems.

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In more recent years Stanovich (1986b) has used the concept of ‘Matthew effects’ to show how early success in phonological processing leads to stronger reading achievement. He finds that higher levels of reading achievement encourage higher levels of independent reading, which leads to further growth in reading comprehension. In turn, stronger reading comprehension has positive consequences for growth in syntactic knowledge, vocabulary, general knowledge and overall linguistic awareness. Poor readers with phonological deficits cannot effectively decode words, and thus do not read as much as good readers. Because poor readers are not exposed to large numbers of words, they eventually become poorer in those language skills typically enhanced by reading (and necessary for FL learning). We speculate that phonological processing deficits similar to those that cause reading disability may be responsible for problems experienced by many poor FL learners and we have drawn parallels between the LCDH and native language reading research in three areas: (1) the apparent disassociation of phonological processing from intelligence (IQ); (2) the potential that phonological processing problems might account for syntactic and oral language problems over time; and (3) the probability that phonological problems could have an indirect effect on other language skills (Matthew effects) (see Sparks & Ganschow, 1993a, 1995a). Our research suggests that one cognitive difference between good/poor FL learners is their efficiency of phonological processing (sound awareness, learning sound–symbol codes). In our studies, poor FL learners exhibited significantly poorer phonological processing skills than good FL learners, but poor phonological processing does not disrupt overall cognitive functioning (IQ, semantics). We also speculate that phonological processes are taxed in FL learning, which makes extra demands on speech perception, production and phonological memory. Moreover, we speculate that Matthew effects may explain how early problems in phonological processing might lead to difficulties with listening comprehension and oral expression in FL learning. More recent reading research suggests that an early deficit in phonological processing might lead to a ‘cascade of interacting cognitive skill deficits that become more pervasive as schooling progresses’ (Stanovich, 1988: 161). These differences in certain cognitive skills (vocabulary, syntax, general knowledge) appear to be related to differences in individuals’ reading volume. In more recently completed studies, we found that poor FL learners with significantly weaker phonological processing skills than good FL learners achieved lower grades in FL courses and lower levels of oral and written FL proficiency than did students with stronger phonological processing (Sparks et al., 1992a, 1992b, 1992c). This research suggests that phonological processing problems may have long-term, indirect effects on language skills important for FL learning.

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Research with Good and Poor FL Learners

Like Pimsleur, Sundland and McIntyre’s (1964) underachievers, we have found that secondary/postsecondary level students with FL learning problems generally do well in their other academic courses (Ganschow & Sparks, 1986; Ganschow et al., 1991, 1994; Sparks et al., 1989, 1992a, 1992b). We described five ‘prototypes’ of good/poor FL learners exhibiting distinct language processing differences (Sparks & Ganschow, 1993b). The first prototype is a poor FL learner with weak phonological processing but average to strong syntactic and semantic skills. The second prototype is a poor FL learner with strong phonological processing but weak syntactic and/or semantic skills. The third prototype is a poor FL learner with weak phonological, syntactic and semantic skills. The fourth and fifth prototypes have strong phonological, syntactic and semantic skills, but one is a strong FL learner while the other is a poor FL learner with affective intrusions (low motivation, high anxiety for all learning). We have found that FL learning problems are likely to be related to native language learning difficulties and suggest that the FL learning problems are language related because FL learning is a language task (Sparks & Ganschow, 1995a). By conceptualizing FL learning problems in the context of a language problem, the cognitive deficits of poor FL learners can be more carefully specified. In our studies, we administer a battery of tests that includes phonological, syntactic and semantic measures of language and a FL aptitude test (MLAT). Poor FL learners consistently are those with native language learning differences or deficits. Some of our studies have found that good and poor FL learners in secondary/postsecondary education exhibit significant differences generally in their native language skills and FL aptitude (Ganschow et al., 1994; Sparks & Ganschow, 1995b, 1996). Other studies have shown that good and poor FL learners exhibit significant differences primarily on measures of native language phonological processing and syntax, but not semantics, and also on the MLAT (Ganschow et al., 1991, 1994; Sparks et al., 1992a, 1992b). Studies with at-risk learners in FL classes have shown their phonological processing skills are generally one-half standard deviation, or more, below their syntactic (grammar) and semantic (vocabulary) skills (Sparks & Ganschow, 1993c; Sparks, Ganschow et al., 1992c). A 2-year study with high school students completing second-year FL courses found significant differences on native language phonology, syntax, semantics, verbal memory and FL aptitude measures between high/low FL proficiency students (Ganschow & Sparks, 1995). Finally, studies have found that students with significantly stronger native language skills achieve higher end-of-year FL grades than students with weaker native language skills (Ganschow et al., 1994; Sparks & Ganschow, 1995b).

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There is also support for the hypothesis that affective differences of good/poor FL learners may be the consequence of differences in native language learning skills (Sparks & Ganschow, 1991). A study with low-, average- and high-anxiety college students identified through Horwitz’s Foreign Language Classroom Anxiety Scale (FLCAS) (Horwitz et al., 1986) showed significant overall differences on native language phonology, overall reading, and FL aptitude measures (Ganschow et al., 1994). High-anxiety students scored significantly lower than low-anxiety students on these measures, and they achieved relatively lower FL grades than average-anxiety and low-anxiety students. Similar language skill differences among students with different levels of anxiety were found using the FLCAS in a comprehensive study of high school women in an academically competitive school program (Ganschow & Sparks, 1996). In a more recent study, examination of teachers’ perceptions of their students’ levels of anxiety, motivation, and attitudes in relation to the students’ native language skills and FL aptitude, indicated that students whom teachers perceived to have higher motivation, more positive attitudes and lower anxiety for FL learning had significantly stronger skills on native language measures and the MLAT than students perceived by their FL teachers as having lower motivation, less positive attitudes and higher anxiety for FL learning (Sparks & Ganschow, 1996). Support for the hypothesis that native language skills and FL aptitude are important for FL learning was found in a study in which we conducted two experiments examining the best predictors of FL grades among two populations of secondary school students in first-year FL courses (Sparks et al., 1995). The first experiment involved females attending a single-sex suburban school; the second experiment involved a co-educational population of students in a suburban public school. Predictor variables included measures of FL aptitude (MLAT), native language phonological processing and semantic skills, and their eighthgrade English grade. The best predictors in both experiments were the MLAT and the eighth-grade English grade; native language spelling was a significant predictor among the single-sex population. We suggested that the MLAT and eighth-grade English grade were strong predictors of FL grades because both involve oral and written language skills, and that the MLAT is a good predictor because it requires students to make metalinguistic judgments. Skehan (1991) hypothesizes that FL aptitude tests predict FL achievement because FL learning in a conventional classroom setting is based on both language capacities and decontextualization skills (i.e. the ability to understand and use contextdisembedded language). These new findings help to explain why FL educators have been puzzled by otherwise average to above average students having FL learning problems, especially those with more difficulty with FL learning than other school subjects. The evidence suggests that poor FL learners

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have difficulty with native language skills. Their processing problems are subtle and can be detected through direct testing (Sparks & Ganschow, 1993b). Studies also suggest that affective differences in some poor FL learners may be related to their lower levels of native language skill and FL aptitude. If overt or subtle native language learning difficulties are related to FL learning problems, then it may be difficult for students who have learned to speak and comprehend their own language to become proficient in a FL. The Advantage of the LCDH over Other Explanations of FL Learning Problems

Our research presents FL educators and researchers with a paradoxical situation. The majority of poor FL learners generally achieve average to above-average grades in all courses except FLs. Their overall native language skills are generally average to above-average, yet they may not possess a commensurate level of ability in specific native language skills. FL educators and researchers have advanced several theories about these students and have focused on many different variables over the last 20 years. But, why have FL researchers not consistently found a set of variables that predict successful or unsuccessful FL learning? In my view, one major reason is that more recent theories advanced by FL educators do not focus on language variables as the primary cause of variance in FL learning. Although previously mentioned theories (motivation, anxiety, learning strategies, cognitive styles) are hypothesized to be specific to FL learning, evidence has not demonstrated that their suggested causal mechanism disrupts only FL learning and not performance in other school subjects. An inference of the LCDH is that students with FL learning problems have a cognitive deficit reasonably specific to the FL learning task; thus, the deficit is assumed to be related to language because learning a FL is the learning of language. There are several arguments that FL educators might make to invalidate the LCDH. First, they could attribute some proportion of a poor FL learner’s outlier status to measurement error and speculate that if the student were re-tested, they would score higher on the native language and FL aptitude tests, or score lower on an IQ test. In our studies, however, we have demonstrated through a large battery of native language and FL aptitude tests that most poor FL learners consistently score lower than good FL learners on these measures. These standardized measures are statistically reliable, and it is doubtful that re-testing would change the poor FL learners’ profiles. Second, FL educators could suggest that FL learning problems are due to causes other than weak language skills, e.g. affective

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differences, misuse/failure to use language learning strategies. However, this tendency to link difficulties in FL learning with causes not directly related to language is problematic because these explanations might be used to explain a host of cognitive and learning problems, not just poor FL learning. Language learning strategy research suggests that failure to use a number of strategies (memory, cognitive, compensatory, metacognitive, affective, social) can interfere with language learning (Oxford, 1990a). To invalidate the LCDH, strategy researchers would have to find that students with phonological processing problems could be taught to use specific language learning strategies and become as proficient in a FL as a good language learner without improving their native language skills. Another way to invalidate the LCDH would be for strategy researchers to offer evidence that failure to use learning strategies could impair one FL skill (reading) but not another FL skill (listening), a finding that would mirror native language research. Third, FL educators could hypothesize that FL learning problems are due to the different cognitive styles of FL learners. Oxford (1990a) reviews cognitive styles and suggests that styles may be composed of cognitive, social and affective dimensions. However, the concept of cognitive style conflicts with the LCDH because its proposed causal mechanisms are not specifically language related. Tiedemann (1989) reviews cognitive style research and suggests that most measures of cognitive style are ability tests and concludes there is ‘insufficient empirical evidence for any construct of a cognitive style in the sense of a bipolar, value-differentiated and pervasive preference dimension’ (1989: 272). Skehan (1991) finds little evidence to suggest that style or strategy training improves FL learning. Likewise, native language researchers have found that one aspect of cognitive style – sensory modality testing and teaching – is ineffective (see Kavale & Forness, 1987, 1990). Liberman (1985) has shown that the contrast between ‘auditory’ and ‘visual’ learners is irrelevant to the teaching of reading. To invalidate the LCDH, advocates of cognitive styles theory would have to show that modality deficits are improved by ‘style training,’ that such improvement results in enhanced FL learning in the presence of native language deficits, and that matching teaching methodologies with students’ cognitive styles enhances FL learning in the presence of native language difficulties. However, evidence in native language and FL research does not support these arguments. Fourth, FL educators could speculate that there are specific affective qualities needed to learn a FL successfully. Horwitz and her colleagues have hypothesized an anxiety specific to FL learning. However, she and others have failed to present evidence that students in their studies have only FL learning problems, or that the anxiety does not generalize to other academic subjects. Poor FL learners’ propensity to do poorly

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primarily in FL courses might be viewed as support for theorists who posit affective differences as causal mechanisms in FL learning difficulties. However, I argue that FL theorists who advocate affective differences as causal mechanisms in FL learning problems would have to provide evidence showing that: (1) an unsuccessful FL learner’s affective differences (high levels of anxiety) do not cause failure routinely in other language-based subjects; (2) there are no native language differences between students who exhibit affective differences (high vs. low motivation, high vs. low anxiety); and (3) students with significantly weaker native language skills and higher levels of anxiety/lower motivation can have their anxiety reduced (or motivation increased) and become as proficient in FLs as students with significantly stronger native language skills. This is not to suggest that there are not students with strong native language skills and average to above average FL aptitude who do poorly in all subjects – there is a small group of students with this profile (Sparks & Ganschow, 1993b). Also, an affective difference such as motivation may be important for FL learning, but there is no reason that motivation is more important for FL learning than it is for other academic learning tasks.1 Fifth, FL educators could argue that language-related differences between good and poor FL learners are unimportant. This speculation would not support the LCDH, which suggests that good and poor FL learners exhibit differences in skills specifically language related but that do not extend too far into other domains of cognitive functioning (math, nonverbal ability). FL researchers have done little research supporting or disproving Carroll’s (1962) FL aptitude theory or Pimsleur’s (1966a, 1968) theory about ‘auditory ability’ (phonological) differences between good/poor FL learners. More recently, we have shown that there are specific native language and FL aptitude differences between good/poor FL learners in secondary/postsecondary education (Ganschow & Sparks, 1995; Ganschow et al., 1991, 1994; Sparks & Ganschow, 1995b; Sparks et al., 1992a, 1992b). Sixth, FL educators could acknowledge that native language differences between good and poor FL learners exist but that these differences do not impact FL learning. However, in several studies we have found that FL learners with significantly lower native language skills have lower FL achievement (Ganschow et al., 1991, 1994; Sparks & Ganschow, 1995b; Sparks et al., 1992b). For example, Sparks, Ganschow and colleagues (1992a) followed 65 identified low-risk (LR) and high-risk (HR) secondary students taking first-year FL courses. On native oral and written language skill measures, LR students obtained scores ranging from 55th to 85th percentile on all measures; HR students obtained scores ranging from 37th to 68th percentile. The LR group’s final FL grades were mostly As, a few B’s and one C. The HR group’s final grades were mostly D’s and F’s with three C’s. FL educators who argue that

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native language differences and FL learning problems are unrelated must show that students with significantly different levels of native language skill can become equally proficient in a FL, or find no native language differences among students with significantly different levels of FL proficiency. Seventh, FL educators could argue that native language learning differences between good and poor FL learners exist but that the differences are due to social class or socioeconomic differences. This argument suggests that native language ability is influenced primarily by factors not intrinsic to the individual. Researchers have long known that both early nurturing experiences and innate language ability are important in native language development. However, the position that FL learning differences are due primarily to social class is problematic because our research has found native language and FL aptitude differences among good and poor FL learners of similar socioeconomic background, and that students from middle- and upper-class backgrounds with FL learning problems have subtle or overt differences in native language skills (Ganschow & Sparks, 1995; Ganschow et al., 1991, 1994; Sparks & Ganschow, 1995b; Sparks et al., 1992a, 1992b, 1992c). Likewise, it is well known that differences in native language attainment are apparent even before entry into school. To falsify the LCDH, FL educators who hypothesize that these language differences are due to social class would have to show that there are no native language differences among students of the same social class. Some FL learning theories cannot explain most FL learning problems because they do not posit that poor FL learners’ problems are directly related to the learning of language. The LCDH has the potential to explain problems only with language learning. Its contribution to FL educators is the consideration of another position to view FL learning problems. Implications

In two articles, Ganschow and I hypothesize that phonological processing meets the criteria for the Assumption of Specificity (AOS) because it is a cognitive deficit specific to the task of learning language (Sparks & Ganschow, 1993a, 1995a). Stanovich (1988) uses the AOS to propose that students with reading disabilities have a cognitive deficit reasonably specific to the reading task; thus, the deficit should be language related because reading is a language-based task. In our view, phonological processing is one type of mechanism that could account for FL learning problems because: (1) it is only weakly related to intelligence; (2) as a modular mechanism, it is not strongly interactive with central processes – it may provide data for central processes but

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neither directs them nor is directed by them; (3) it cannot be remedied by efficiently functioning central processing skills; (4) it may fail without disrupting the current operations of the central processes that do not critically depend on its output; and (5) its long-term failure may have indirect but long-term effects on central processes. This final reason – long-term failure – invites speculation about the source of central (global) processing problems in some poor FL learners. For example, some students with strong phonological processing skills do exhibit weak syntactic and semantic skills (listening comprehension, oral expression, vocabulary). Students with phonological processing problems may, over time, have diminished listening comprehension and vocabulary skills. These global deficits might be seen as undermining the LCDH and negating the hypothesized modularity of some poor FL learners’ native language skill deficit. The hypothesis that we have advanced to explain these average to low-average skills is that increasingly global language deficits may be the result of a lack of reading over a number of years (Sparks & Ganschow, 1993a). In native language reading research, Stanovich (1986a, 1988) speculates that these global language deficits are the result rather than the cause of reading disability. In other words, the possibility of reciprocal causation must be considered. That is, the difficulty with phonological processing skills early in school initiates a causal chain of negative side effects (Matthew effects). Because a child does not read well, s/he is exposed to much less text than skilled readers. Differential exposure to text does not facilitate growth in skills such as listening comprehension, vocabulary and syntax. Thus, the same skills that one obtains from reading contributes to skills in listening comprehension and verbal expression, both of which are crucial for FL learning. In sum, the results of more recent native language research show that phonological processing skills play a critical role in learning to read, and have important implications for further development in reading comprehension and listening comprehension in one’s native language. In turn, these native language skill deficits further contribute to poor FL learning. Future research may be helpful in determining the specific effects of native language phonological processing skill on different aspects of FL learning over time.

Acknowledgement

A version of this chapter was previously published as Sparks, R. (1995) Examining the linguistic coding deficit hypothesis to explain individual differences in foreign language learning. Annals of Dyslexia 45 (1), 187–214.

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Note (1) The term ‘FL learning problems’ has various meanings among FL educators. At the secondary/postsecondary levels, FL learning problems are generally defined by poor grades in FL courses and/or failure to reach a level of proficiency in the FL. At higher levels of study, FL learning problems may be defined as individuals already proficient in a FL but seeking advanced training. In the latter case, I speculate that affective differences (motivation) may play a role in eventual success in moving to a higher level of proficiency. However, I also suggest that subtle native language or FL aptitude differences might be responsible for an individual’s slower progress towards, or failure to achieve, a higher level of proficiency. That is, an individual who does not successfully complete or compete in a program for advanced learners may not have the necessary native language and/or FL aptitude skills that are comparable to their more successful peers.

Part 2: Empirical Support for L1–L2 Relationships and Cross-linguistic Transfer

Introduction

Once Ganschow and I had published our essays on the LCDH and its theoretical development, we embarked upon a series of investigations that aimed to provide empirical support for the relationships among L1 ability, L2 aptitude and L2 achievement and also whether the studies would support the notion of cross-linguistic transfer of L1 skills to L2. Figure I.1 in the Introduction and Overview depicts the trajectory of our investigations that began with comparison studies of high-, average- and low-achieving L2 learners on measures of L1 skills and L2 aptitude and proceeded to studies involving prediction of L2 performance outcomes. Initially, our studies with L2 outcomes were limited to using students’ grades and performance on qualitative measures from L2 classes after we found that there were no standardized tests with which US L2 educators measured oral and written L2 achievement (proficiency). A major ‘breakthrough’ for our research was the development of L2 proficiency measures developed by our L2 colleagues – Marge Artzer, David Siebenhar and Mark Plageman – who used the American Council on the Teaching of Foreign Languages Proficiency Guidelines (American Council on the Teaching of Foreign Languages (ACTFL), 1986, 1989) that we used to measure, quantify and compare L2 learners’ performance in their listening, speaking, reading and writing skills. We published our first paper using these measures with students completing second-year L2 courses in the Journal of Educational Psychology (Sparks, Ganschow, Patton et al., 1997) and the measures remained a mainstay in our studies for many years. These L2 measures, which proved to be both valid and reliable, permitted us to conduct additional prediction studies as well as studies involving the use of more sophisticated investigations, e.g. factor analysis, multiple regression, cluster analysis, path analyses. We also completed investigations which found that IDs in L2 learners’ previous print exposure (reading volume) in L1 significantly impacted their level

59

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of L2 achievement. Over time, our studies provided converging evidence showing: (a) strong relationships between IDs in L1 ability and students’ L2 aptitude and L2 achievement; (b) L1 skills are strong predictors of L2 achievement; (c) strong relationships between L1 skills and the skills measured by the MLAT; (d) students with IDs in L2 achievement in high school exhibited significant IDs in L1 skills as early as second grade; (e) high- and low-achieving L2 learners exhibit distinct L1 and L2 aptitude and achievement profiles; (f) IDs in L1 print exposure contribute unique variance to L2 oral and written proficiency skills; and (g) cross-linguistic transfer of L1 skills to L2. Since the aforementioned findings are drawn from studies conducted in the US, it is appropriate to remind the reader of the US social context for L2s. The US is a largely monolingual society in which learning another language is neither conventional nor mandatory. In the US, only 20% of US primary and secondary level students engage in L2 study in school, only 7–8% of university students enroll in L2 courses, and L2 study largely begins in high school (Stein-Smith, 2019). Less than 1% of US adults are proficient in a L2 that they learned in school (Friedman, 2015). In contrast, studying a L2 is nearly ubiquitous for European students, who begin L2 study in primary school, and L2s are compulsory in 20 European countries (Devlin, 2018). In the US, most students study L2s as a subject to fulfill a requirement, not with the goal of becoming fluent or literate. US students in language classes can generally practice the L2 only in the classroom for short periods of time during the school year (or semester) and are rarely exposed to the L2 outside the class. In comparison, some European students may live in a country in which more than one language is spoken routinely, and some may have parents or peers who speak the target language, so they are exposed to the L2 outside the school. Given the differences in the US and European social contexts, several questions about our research should be addressed, including: (a) How much do the findings depend on the typical L2 learning context in the US? (b) How much do the findings depend on the way L2 achievement was measured? (c) Will print exposure predict language learning in a naturalistic context or is it associated specifically with L2 learning at school? Before answering, an important consideration is that with so few US students engaged in L2 study, we have found that only those students

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with average, or better, L1 skills enroll in L2 courses. Indeed, few students in our studies who were enrolled in L2 courses were found to have achieved L1 scores in the below average range ( 75th percentile vs. < 35th–40th percentile, achieve similar levels of L2 proficiency. Likewise, no studies show that individuals with low motivation (or high anxiety) and low levels of L1 skills and L2 aptitude, e.g. < 35th– 40th percentile, can decrease their anxiety or increase their motivation and achieve levels of L2 proficiency similar to an individual with stronger L1 skills and L2 aptitude, e.g. > 75th percentile. Thus, it seems unlikely that IDs in L2 learning can be attributed primarily to affective or social factors. Rather, findings that L1 cognitive factors have an impact on L2 learning suggest that IDs in L2 learning are best explained by cognitive factors. We know of no empirical studies showing that students with significantly lower levels of L1 skills/L2 aptitude can be taught, for example, according to their preferred ‘style’ or use specific learning strategies, and achieve levels of L2 proficiency similar to students who have stronger L1 skills and L2 aptitude. Instead, numerous studies have found that individuals with the aforementioned L1 skills and L2 aptitude profiles will exhibit different L2 outcomes.

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L2 educators in the US (and other monolingual cultures) are faced with a difficult challenge. Variation in language skills across individuals is normal and has effects on performance at any age (Kidd et al., 2018). In most cases, subjective evidence of IDs in students’ L2 skills is apparent in grades, effort, schoolwork completion, interest in the subject and class participation. However, objective evidence of IDs in students’ L1 skills and L2 aptitude may not be transparent to L2 teachers because all their students can read, write, speak and comprehend their L1. An additional challenge for US L2 teachers is the context in which their students are learning the L2. In fact, monolingual US students, most of whom begin L2 study in high school, are not typical L2 learners. In monolinguals, the development of speech (oral language) precedes the acquisition of reading and writing (written language). There is no language in which individuals acquire its written form before speech. By the time a child encounters the formal teaching of print, s/he has acquired a vocabulary of 3,000–5,000 words for use in speaking and comprehending oral language and for comprehending written language that is read aloud to them. However, monolingual US L2 students are learning to speak and read/write the L2 at the same time. Consequently, most US L2 learners have little or no L2 vocabulary knowledge, so they cannot comprehend the spoken or written L2. Paul Nation (Nation, 2001) has described three major differences between native and non-native speakers of a language applicable to most US high school students in L2 courses: (1) native speakers of a language acquire a large number of high-frequency words quickly prior to age five; (2) native speakers have multiple, daily opportunities to learn from input and produce output; and (3) L2 learners, especially in formal classroom instructional settings, have much less time for learning the L2 because they may not begin courses until adolescence. Two recent studies highlight the challenges faced by L2 educators in the US and confirm Nation’s differences between native and non-native speakers. In one study, high school students’ Spanish vocabulary and listening comprehension skills were found to be similar to the average native Spanish speaker at the 2½–3-year-old level, even after three years of Spanish courses (Sparks et al., 2017, 2018b). Other studies have shown that US high school students learned to decode an alphabetic L2 (Spanish) well, but still exhibited extraordinarily poor reading comprehension and listening comprehension skills, largely because of their extremely limited L2 vocabulary acquisition (Sparks, 2015; Sparks & Luebbers, 2018; Sparks et al., 2017). The constraint on L2 learning, in particular vocabulary knowledge, for US high school students is the social context in which the learning takes place: that is, most live in a home and a community where the target language is not spoken and are being educated in their native language in all other subjects. The lack of exposure to the L2 inside/outside the school

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puts considerable constraints on what L2 teachers can accomplish in classroom settings. In previous studies, Sparks et al. (Sparks, 2015; Sparks et al., 2017) outlined pedagogical implications for the development of L2 skills in US learners. These implications included, first and foremost, explaining how IDs in students’ L1 skills are related to their L2 outcomes and to IDs in social and affective differences. Students with lower levels of L1 skills will likely display lower motivation and/or higher anxiety in L2 classrooms, and they may display behaviors less conducive to the development of language proficiency. If L2 teachers are unaware that IDs in language skills are the primary reason for social and affective differences, they may employ teaching strategies that do not support the development of the core language skills needed to improve these students’ performance. In our view, the development of L2 vocabulary knowledge and language specific skills (e.g. grammar) is crucial because students with different levels of L1 skills and L2 aptitude will differ in L2 achievement. These IDs necessitate that L2 teachers provide additional, and sometimes different, instruction for students with lower levels of language ability. For example, although current L2 pedagogical methods discourage direct teaching of language skills such as grammar, students with poor knowledge of L1 grammar will require explicit instruction in the L2 grammar. More importantly, given studies showing third-year students’ L2 Spanish vocabulary skills were similar to native speakers at a 2½–3year-old level, the most pressing need for US L2 learners is vocabulary acquisition in the L2. Without a well-developed vocabulary, students will be unable to speak or comprehend the L2. Classroom teachers will have to select carefully the high-frequency L2 words most necessary for understanding simple conversations and basic texts and accomplishing life tasks, and teach these words directly and deliberately. Students are unlikely to encounter grammar and vocabulary knowledge outside the L2 classroom and, without it, they will not be able to use language in meaningful ways to accomplish personal goals. In L1 vocabulary reading research, scholars distinguish between Tier 1 (known, high-frequency), Tier 2 (applied across many settings and subjects), and Tier 3 (low-frequency, teach as need arises) words and have recommended that L1 teachers focus on teaching Tier 2 words (Nagy & Townsend, 2012). However, US L2 learners have not acquired even the high-frequency Tier 1 words that native speakers of Spanish have learned prior to 5–6 years of age. L2 teachers will have to purposely select and teach the L2 vocabulary words that native speakers acquire prior to 5-6 years of age and also teach high-frequency words found in print whose meanings are already well known by speakers of the language. An important challenge for L2 educators and researchers may be to determine the identity of the ‘relatively small amount of

100  Part 2: Empirical Support for L1–L2 Relationships and Cross-linguistic Transfer

well-chosen vocabulary [around 2,000]’ that can ‘can allow learners to do a lot’ in an L2 (Nation, 2001: 9). Conclusion

The goal of this study was to examine the extent to which students’ levels of L2 achievement would reflect their levels of L1 skills and L2 aptitude. The findings showed that L2 learners who attained higher levels of L2 achievement had significantly stronger L1 skills and L2 aptitude than L2 learners with lower levels of L2 achievement, and that students’ L1 literacy skills reflected their L2 literacy skills. Specifically, students with stronger L1 literacy and language skills developed stronger L2 literacy and language skills, and students with weaker L1 literacy and language skills developed weaker L2 literacy and language skills. The results support a long line of research implicating cognitive variables, particularly L1 skills and L2 aptitude, as the primary explanations for IDs in L2 learning. Acknowledgement

A version of this chapter was previously published as Sparks, R., Patton, J. and Luebbers, J. (2019) Individual differences in L2 achieve­ment mirror individual differences in L1 skills and L2 aptitude: Crosslinguistic transfer of L1 to L2 skills. Foreign Language Annals 52 (2), 255–283. https://doi.org/10.1111/flan.12390

6 Do L1 Reading Achievement and L1 Print Exposure Contribute to the Prediction of L2 Proficiency? Richard Sparks, Jon Patton, Leonore Ganschow and Nancy Humbach

Introduction

In recent years, investigations have shown that students with stronger oral and written L1 skills measured in high school exhibit stronger L2 aptitude and L2 proficiency and achievement (Ganschow & Sparks, 2001). Longitudinal studies have shown that preschool L1 skills are related to L2 aptitude and achievement in high school (Skehan & Ducroquet, 1988). Likewise, recent longitudinal studies have found that L1 literacy skills measured in elementary school are related to L2 aptitude and L2 proficiency and achievement in high school/college (Sparks et al., 2008b, 2009). This research on L1–L2 connections leads to speculation about whether L1 literacy skills affect students’ performance on measures of L2 aptitude and L2 proficiency. In L1 literacy research, Stanovich and others have examined whether differences in educational outcomes (vocabulary size, general knowledge, grammar) are related to differences in exposure to print (reading volume) (Cunningham & Stanovich, 1991; Stanovich & Cunningham, 1997; West & Stanovich, 1991). By developing print exposure measures as proxies for out-of-school reading activity, Stanovich and collaborators investigated the cognitive efficiency hypothesis, the idea that differences in vocabulary and language skills are caused by variation in the efficiency of the cognitive mechanisms for obtaining meaning from text, and the environmental opportunity hypothesis, the idea that vocabulary and language skill differences result from differential opportunities for 101

102  Part 2: Empirical Support for L1–L2 Relationships and Cross-linguistic Transfer

word learning. Their results supported the environmental opportunity hypothesis by showing that even after controlling for cognitive ability (IQ), print exposure explained a significant portion of the variance on measures of vocabulary, general knowledge, orthographic knowledge and overall language skills. But: Could reading volume in L1 affect the development of L2 skills? In the US, L2 study generally does not begin until the high school years after students have learned to read their native language, and after being exposed to print through reading for several years. Recent L2 studies have shown that cognitive efficiency mechanisms, e.g. L2 aptitude, working memory, grammar, vocabulary, are important for L2 proficiency/ achievement. However, no studies have explored the environmental opportunity hypothesis asking whether L1 print exposure over time could play a role in L2 proficiency/achievement. In the present study, a population of L1 learners was followed from first to tenth grade when they completed two years of high school L2 courses. Students’ L1 literacy skills, L1 vocabulary and cognitive ability were assessed throughout elementary school and their L1 reading achievement, L2 aptitude, L2 proficiency and L1 print exposure were measured in high school. The authors were interested in examining: (a) whether individual differences (IDs) in high school L1 reading achievement would explain unique variance in L2 proficiency after adjusting for the effects of early L1 skills, cognitive ability and L2 aptitude; and (b) whether IDs in L1 print exposure would explain unique variance in L2 proficiency after adjusting for the effects of early L1 skills, cognitive ability, L2 aptitude and high school L1 reading achievement. Both findings would support the environmental opportunity hypothesis, i.e. experiential factors (reading volume) may play a role in L2 learning. In the review, we summarize research on L2 aptitude, cognitive ability and L1–L2 connections that supports the cognitive efficiency hypothesis. Then, we summarize literature on the effects of print exposure on L1 cognitive outcomes that supports the environmental opportunity hypothesis.

L2 Learning and L2 Proficiency: Cognitive Mechanisms at Work

Many years of research in L2 learning have supported the hypothesis that IDs in L2 proficiency/achievement are related to efficiency of cognitive mechanisms. These studies have been conducted in three broad areas: L2 aptitude, L1–L2 learning connections and L1 cognitive ability (intelligence). In a seminal study on L2 aptitude,

Contribution of L1 Reading Achievement and Print Exposure to the L2 Proficiency Prediction  103

Skehan and Ducroquet (1988) followed children who participated in the Bristol Language Project (Wells, 1985) whose language skills had been tested from 15 to 60 months and who were then administered L2 aptitude and L2 achievement measures at 13–14 years. Their findings revealed that: (a) L1 comprehension and vocabulary at 57–66 months of age were significantly related to L2 achievement at age 13 (r = .55–.67). (b) L1 development, especially early vocabulary and comprehension prior to school, was significantly related to L2 aptitude in high school (r = .54). (c) L2 aptitude was significantly related to written/oral L2 achievement (r = .49–.73). Skehan (1989: 34) concluded that L2 aptitude tests measure an ‘underlying language learning capacity which is similar in first and second language learning settings’. He reported that school success at age 10 related most strongly to students’ ‘preparedness for literacy’ and that literacy-related factors continued to influence L2 study several years later. Likewise, Sparks and others have found in longitudinal studies that IDs in L1 cognitive outcomes are related to variation in the efficiency of cognitive mechanisms related to language skills. For example, studies over 1–2 years with high school and college L2 learners have shown that students with stronger L1 skills exhibit stronger L2 aptitude and L2 proficiency/achievement (Ganschow & Sparks, 2001; Sparks, Ganschow et al., 1998). In two studies (Sparks et al., 2008a, 2008b), Sparks and colleagues found that L1 literacy measures administered in fourth grade and L2 aptitude on the Modern Language Aptitude Test (MLAT; Carroll & Sapon, 1959, 2000) best discriminated students’ performance on L2 proficiency measures years later in high school. In particular, measures of L1 literacy (word decoding, spelling) distinguished stronger from weaker L2 learners. In longitudinal studies that followed students from first to tenth grades, findings (Sparks et al., 2006, 2008, 2009) showed: (a) L1 literacy in elementary school explained 40% of the variance in oral/written L2 proficiency in high school. (b) L1 literacy (reading, spelling), vocabulary and verbal ability in elementary school explained 73% of the variance in L2 aptitude MLAT in ninth grade. (c) The best predictors of L2 decoding and spelling skills in tenth grade were L1 decoding and L1 spelling tests administered in elementary school. (d) L1 differences among high-, average- and low-proficiency high school L2 learners emerged early in elementary school.

104  Part 2: Empirical Support for L1–L2 Relationships and Cross-linguistic Transfer

Other researchers have found strong relationships between L1 and L2 achievement (Gottardo & Mueller, 2009; van Gelderen et al., 2007), and that L1 skills distinguish strong from weak L2 learners (Dufva & Voeten, 1999; Humes-Bartlo, 1989; Meschyan & Hernandez, 2002; Service & Kohonen, 1995). Other studies indicate that although L2 aptitude is largely independent of intelligence (Carroll, 1962), cognitive ability may be related to the efficiency of the cognitive mechanisms supporting L2 proficiency. In early studies, Gardner and Lambert (1965, 1972) found that although aptitude and intelligence were correlated, they were relatively independent of one another. Wesche et al. (1982) reported that L2 aptitude and intelligence may share some level of overall cognitive ability. Sasaki (1996) found that a general factor of second language proficiency is related to but not identical with general cognitive abilities. In a recent factor analysis conducted on a test battery including L1 skills, cognitive ability and the MLAT, cognitive ability was unrelated to the skills measured by the MLAT, except for paired associate learning (Sparks et al., 2011). L1 Literacy and the Environmental Opportunity Hypothesis

Cognitive theorists generally agree that most vocabulary growth occurs through language exposure rather than direct teaching (Nagy & Anderson, 1984; Nagy et al., 1985; Nation & Coady, 1988). Reading researchers contend that the amount of reading over time, not oral language, is the primary factor in IDs in children’s vocabularies (Hayes, 1988; Nagy & Herman, 1987). Hayes and Ahrens (1988) have shown that ‘rare’ words, i.e. those that occur infrequently, are used more often in print than in speech. Numerous studies have found that extensive reading benefits language knowledge, quality of language, and academic performance generally (Nation, 2001). In a 1988 paper, Stanovich synthesized the growing body of research on IDs in the cognitive skills related to reading. He speculated that early success in the acquisition of reading skills leads generally to later success in reading; however, failure in learning to read early in school is likely to lead to significant, life-long problems in learning new information because children who fall behind in reading early read less than their peers, particularly outside school, and fall further behind. Stanovich hypothesized that failure in reading leads to IDs in reading volume and also to other negative outcomes, e.g. lower motivation to read and achieve in school, poorer vocabulary and general knowledge. At the time his paper was published, there was limited empirical evidence relevant to the hypothesis about the negative outcomes of reading failure (Hayes & Grether, 1983). Those advocating the cognitive efficiency hypothesis speculated that IDs in outcomes related to reading were related to

Contribution of L1 Reading Achievement and Print Exposure to the L2 Proficiency Prediction  105

differences in intelligence and basic psychological processes (Jensen, 1980). In contrast, those advocating the environmental opportunity hypothesis speculated that IDs in reading-related outcomes on standardized IQ and vocabulary measures are the result of differential opportunities for word learning (Block & Dworkin, 1976). Stanovich (2000) argued that a powerful determinant of children’s general knowledge and vocabulary skills is an environmental factor: exposure to print. He cited evidence showing that large differences in print exposure as early as first grade (Biemiller, 1997–8) and differences in reading volume over time linked to early reading skill (Fielding et al., 1986). In their studies, Stanovich and others piloted a checklist with foils procedure (‘quick probes’) to measure print exposure (see Stanovich, 2000, for a description of these measures). In these studies, they established the validity and reliability of checklists – Author, Magazine, and Title Recognition Tests – and found that unique orthographic processing variance was related to differences in participants’ levels of print exposure even after adjusting for the effects of their phonological processing skills, IQ and memory ability (Cunningham & Stanovich, 1990; Stanovich & West, 1989). Subsequent studies with these measures showed that print exposure explained unique variance in, and contributed to, differences in spelling, vocabulary, general knowledge and verbal fluency skills (see Cunningham & Stanovich, 1998 and Stanovich, 2000, for a summary of studies). In a longitudinal study, Cunningham and Stanovich (1997) examined the relationships between first-grade reading skill and cognitive ability and eleventh-grade outcomes in reading comprehension, written/ receptive vocabularies, and general knowledge. In this study, they administered the Cultural Literacy Test (1989), a general knowledge checklist, and a multicultural checklist (Simonson & Walker, 1988) in eleventh grade. The findings showed that first-grade reading ability was a strong predictor of eleventh-grade vocabulary and general knowledge outcomes after adjusting for the effects of cognitive ability, and that reading ability in first, third and fifth grades was reliably linked to print exposure after controlling for eleventh-grade reading comprehension. These findings showed that early acquisition of reading and exposure to print are important in predicting literacy experiences and outcomes. A number of studies have also found that literacy activities in the home – the Home Literacy Model (Senechal et al., 1998) – are related to both L1 and L2 literacy development (e.g. see Dickinson et al., 2004). Research Questions

Evidence shows that L1 print exposure reliably predicts important L1 cognitive outcomes and that there are L1 skill differences (especially L1 literacy) between high-achieving and low-achieving L2 learners.

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Likewise, studies have shown that there are strong relationships between L1 literacy and L2 aptitude, proficiency and achievement. An unanswered question is whether later L1 reading achievement and L1 reading volume might predict unique variance in students’ L2 oral/ written proficiency skills. A study which shows that L1 print exposure explains unique variance in L2 proficiency could provide support for the environmental opportunity hypothesis – i.e. differences in L2 proficiency are in part the result of differential opportunities for word learning – and for theories proposing long-term L1–L2 connections. The present chapter describes results of a longitudinal study in which students were followed over ten years from first to tenth grades. We proposed two research questions asking: (a) whether IDs in L1 reading achievement measured in high school would explain unique variance in students’ L2 skills in reading comprehension, writing, listening comprehension and oral expression, word decoding, spelling and overall proficiency, after adjusting for variance explained by their early L1 literacy and verbal skills, cognitive ability in L1 and L2 aptitude; (b) whether IDs in L1 print exposure and general knowledge measured in high school would explain unique variance in students’ L2 skills in reading comprehension, writing, listening comprehension and oral expression, word decoding, spelling and overall proficiency, after adjusting for variance explained by their early L1 literacy and verbal skills, cognitive ability in L1, L2 aptitude and L1 reading achievement measured in high school. Method Participants

Participants were 54 high school students, 25 male and 29 female, from a large middle-class, rural school district in the Midwestern US. All students had completed two years of L2 courses in either Spanish (n = 30), French (n = 14) or German (n = 10) in the same high school. Participants were followed from first to tenth grades. All participants had completed their second year of the L2 by the end of the tenth grade. The mean age of the participants beginning first grade was 6 years 9 months; at the end of the study 10 years later, it was 16 years 4 months. A cohort model was used in which a sample of students in first grade was selected and followed over 10 years. None of the 54 participants had received L2 instruction prior to ninth grade. All participants were monolingual and their home language background was English. Each participant was exposed to similar learning conditions and had the same number of hours of L2 classroom instruction over two years (180-day school year, one class per day).

Contribution of L1 Reading Achievement and Print Exposure to the L2 Proficiency Prediction  107

Instruments Predictor variables

The L1 measures are listed below and described in Appendix A. The L1 achievement tests measured language skills found in numerous studies to distinguish high-, average- and low-achieving L2 learners. L1 skill measures (first–fifth grades)

Word decoding. The measure of L1 word recognition and decoding was the Woodcock Reading Mastery Test–Revised Basic Skills Cluster, Forms G and H (Woodcock, 1987). A test-retest reliability of .96 was reported for the Basic Skills Cluster. Spelling. The measure of L1 spelling was the Test of Written Spelling–2 (Larsen & Hammill, 1986). A test-retest reliability of .95 was reported for the test. Reading comprehension. The measure of L1 reading comprehension was the Formal Reading Inventory, Forms A and B (Wiederholt, 1986). An internal consistency of .92–.97 was reported for the two forms of the test. Phonological awareness. The measure of L1 phonological awareness was the Lindamood Auditory Conceptualization Test, Forms A and B (Lindamood & Lindamood, 1973). A pretest-posttest reliability of .96 was reported for the two forms of the test. Vocabulary. The measure of L1 vocabulary was the Peabody Picture Vocabulary Test–Revised, Forms L and M (Dunn & Dunn, 1981). A median test-retest reliability of .82 was reported for the two forms of the test. Listening comprehension. The measure of L1 listening comprehension was the Woodcock Reading Mastery Test–Revised Passage Comprehension subtest, Forms G and H (Woodcock, 1987). A test-retest reliability of .92 was reported when this subtest was used as a measure of reading comprehension. Cognitive ability in L1. The Test of Cognitive Skills (CTB/ McGraw-Hill, 1983) was used to assess a student’s cognitive ability in L1. All test items are presented orally and no reading or writing is necessary to complete the items. A test-retest reliability of .91 was reported by the authors for this test. L1 skill measure (tenth grade)

Reading comprehension. The ISTEP Reading subtest was used to assess the participants’ level of reading comprehension and vocabulary skills. An internal consistency reliability of .94 was reported by the authors for this test. L1 print exposure measures (tenth grade)

Author Recognition Test (ART). The ART is a checklist on which students choose whether they are familiar with the name of a popular

108  Part 2: Empirical Support for L1–L2 Relationships and Cross-linguistic Transfer

author by checking his/her name (Stanovich & West, 1989). There are 40 names of authors and 40 foils, i.e. persons who are popular authors on bestseller lists and those who are not popular authors, i.e. members of editorial boards, listed in alphabetical order. Magazine Recognition Test (MRT). The MRT is a checklist on which students choose the name of a magazine with which they are familiar. It was designed to balance the ART by sampling magazine reading rather than authors of books (Cunningham & Stanovich, 1997; Stanovich & West, 1989). There are 40 names of magazines and 40 foils. The names of the actual magazines were popular publications with wide circulation in a range of genres (music, sports, fashion, outdoors, cars, technology). Cultural Knowledge Checklist (CLC). The CLC is a recognition test designed to measure familiarity with individuals who have shaped modern society. The checklist is a proxy measure of IDs in cultural awareness, not knowledge in an absolute sense (Cunningham & Stanovich, 1997; Stanovich & Cunningham, 1993). The test includes names of well-known individuals in several categories (musicians, composers, artists, scientists, military leaders, explorers) compiled from Hirsch (1987) and mixed with an equal number of foils, i.e. editorial board members. Multicultural checklist. The multicultural checklist was designed as a companion measure to the Cultural Knowledge Checklist (Stanovich & Cunningham, 1993). The 30 items were taken from the Appendix of Multicultural Literacy items developed by Simonson and Walker (1988) as a response to the preponderance of male and European items in Hirsch’s (1987) list. The 30 items were mixed with 15 foils from a journal’s editorial board. In all analyses, a composite general knowledge score called the Cultural Literacy Test (CLT) combined performance on the four knowledge measures from the Cultural Knowledge Checklist and the multicultural checklist. L2 aptitude measure (ninth grade)

The Modern Language Aptitude Test (MLAT; Carroll & Sapon, 1959, 2000) was used to measure students’ L2 aptitude. This test is designed to provide an indication of a student’s probable degree of success in learning an L2. Outcome variables L2 proficiency measures (ninth and tenth grades)

The L2 proficiency tests measured the four skills identified by the American Council on Teaching Foreign Language (ACTFL) Proficiency Guidelines (1986, 1989) as essential for L2 acquisition: reading, writing, listening and speaking. The authors of the present study also included measures of word decoding and spelling. The measures were designed by

Contribution of L1 Reading Achievement and Print Exposure to the L2 Proficiency Prediction  109

three L2 educators formally trained in ACTFL guidelines and were designed to ensure uniformity across the three languages. The directions were the same for each of the three languages. The L2 measures are listed here and described in Appendix B. The list of Spanish, French and German words used for word decoding and spelling can be found in the original paper. L2 word decoding. The L2 word decoding task for each of the three languages consisted of a list of 20 real words and a list of 20 pseudowords. The reliability of the L2 word decoding lists was .75–.76 (Spanish), .78–.84 (French) and .79–.81 (German). The maximum score for each year was 40 words (20 real words, 20 pseudowords) for a potential maximum score of 40 words. L2 spelling. The spelling task for each of the three L2s consisted of 20 words designed to measure spelling in each of the three languages. The reliability of the L2 spelling lists was .78 (Spanish), .81 (French) and .74 (German). The maximum score for each year was 20 words. L2 reading comprehension. Students read a one-page letter written in the L2 and answered 10 multiple-choice questions in English about the letter. Next, students read a passage from Reader’s Digest in the L2 and answered 10 multiple-choice questions in English about the passage. Students were given 15 minutes to read the letter and answer the questions and 15 minutes to read the passage and answer the questions (maximum score = 20). L2 writing test. Students wrote a response in the L2 to the letter that had been read for the reading comprehension task. The letter contained five questions to which the students were asked to respond. The students were given 15 minutes to write the letter. Each student’s writing sample was scored for five criteria: vocabulary, cultural appropriateness, structure, comprehensibility and spelling (maximum score = 25). L2 speaking/listening test. Students’ proficiency was assessed through a 10–15-minute individual oral proficiency interview. Interviewers used randomly selected topics about which the students conversed. The interview was scored for five criteria: pronunciation, vocabulary, grammar, comprehensibility and listening comprehension (maximum score = 25). Total L2 proficiency. Total L2 proficiency was the combined number of points on the L2 reading comprehension, writing, listening/ speaking, word decoding and spelling tests (maximum score = 130). The justification for combining the scores on the five tests was that ACTFL guidelines define proficiency as reading, writing and speaking/listening to a L2. Cronbach’s alpha for the total L2 proficiency measure was .89. Procedure

Four L1 measures – Woodcock Reading Mastery Test Basic Skills Cluster, Test of Written Spelling, Formal Reading Inventory, and Peabody Picture Vocabulary Test – were administered in elementary

110  Part 2: Empirical Support for L1–L2 Relationships and Cross-linguistic Transfer

school at five time intervals: beginning of first grade and at the end of the first, second, third and fifth grades. The Lindamood was administered through the third grade and the listening comprehension test was administered at the end of the third and fifth grades. For each of the L1 measures, a student’s scores from first to fifth grades were combined to obtain a mean score on each measure. The L1 measures were administered by the first and third authors with assistance from trained undergraduate and graduate students. The Test of Cognitive Skills (TCS) was administered in the first grade and the ISTEP Reading subtest was administered by the school district when the participants were in tenth grade and scores were obtained from school records. The MLAT was administered in small groups by the first author at the beginning of the ninth grade. The L2 word decoding measure was administered individually to each student at end of the ninth and tenth grades and the L2 spelling measure was administered at the end of the tenth grade by the last author. The L2 reading comprehension and L2 writing measures were administered in groups by the first author at the end of the students’ second-year L2 course. The listening/speaking (oral proficiency) measure was administered individually by the last author at the end of the students’ second-year L2 course. The print exposure and general knowledge measures were admin­ istered in small groups by the first author at the end of the students’ second-year L2 course. Results

A series of fixed-order, hierarchical regression analyses were conducted to determine the effect of the high school L1 reading achievement, L1 print exposure and general knowledge measures on L2 proficiency. The analyses were structured to indicate whether the aforementioned measures would explain variance in L2 proficiency after adjusting for variance explained by measures of elementary L1 literacy and verbal ability, L1 cognitive ability and L2 aptitude. In each analysis, the elementary L1 literacy and verbal ability measures, the cognitive ability test and the L2 aptitude variable were entered as a group (Step 1). Then, high school L1 reading achievement (ISTEP) was added to the analysis (Step 2) followed by the L1 print exposure and general knowledge measures (Step 3) to determine whether they would explain additional variance in L2 proficiency. Separate regression analyses were conducted for each of the five L2 proficiency subtests and the total L2 proficiency measure. In each analysis, the CLT (Cultural Literacy Test) was entered separately to determine whether this measure alone would explain unique variance in L2 proficiency. In addition in each analysis, the ART and MRT were combined (as ART/MRT) and entered as one variable to

Contribution of L1 Reading Achievement and Print Exposure to the L2 Proficiency Prediction  111

determine whether this measure alone would explain unique variance in L2 proficiency. Also in each analysis the ART, MRT and CLT were combined (as ART/MRT/CLT). The rationale for conducting separate regression analyses for each of the five L2 proficiency subtests was to determine whether the ART/MRT and CLT measures, singly or combined, would explain more or less unique variance in a specific L2 skill. The rationale for conducting a separate regression analysis for the combined subtests, i.e. total L2 proficiency, was to determine whether the ART/MRT and CLT measures, singly or combined, would account for more or less unique variance in overall L2 proficiency (oral and written). Results of the regression analyses for each of the L2 proficiency subtests and the total L2 proficiency measure are presented in Tables 6.1–6.6. Table 6.1  Hierarchical regression results for L2 reading comprehension ΔF

Final β

Step

Variable

R2

ΔR2

1

L1 skills/IQ/MLAT

.446

–

4.53

–

2

ISTEP Reading

.508

.062

5.52*

.434

3

CLT

.556

.048

4.65*

.296

3

ART/MRT

.553

.045

4.31*

.292

3

ART/MRT/CLT

.562

.054

5.26*

.322

Note: IQ = Test of Cognitive Skills; MLAT = Modern Language Aptitude Test; CLT = Cultural Literacy Test; ART/ MRT = Author Recognition Test, Magazine Recognition Test. *p