The Routledge Handbook of Second Language Acquisition and Individual Differences

Shaofeng Li, Phil Hiver, Mostafa Papi, Shaofeng Li, Phil Hiver, Mostafa Papi

• Publisher: Routledge
• Year: 2022
• ISBN:
  9781000548426
• Edition: 1
• Topic: Languages & Linguistics
• Subtopic: Linguistics
• Index: Languages & Linguistics

The Routledge Handbook of Second Language Acquisition and Individual Differences provides a thorough, in-depth discussion of the theory, research, and pedagogy pertaining to the role individual difference (ID) factors play in second language acquisition (SLA).

It goes beyond the traditional repertoire and includes 32 chapters covering a full spectrum of topics on learners' cognitive, conative, affective, and demographic/sociocultural variation. The volume examines IDs from two perspectives: one is how each ID variable is associated with learning behaviors, processes, and outcomes; the other is how each domain of SLA, such as vocabulary or reading, is affected by clusters of ID variables. The volume also includes a section on the common methods used in ID research, including data elicitation instruments such as surveys, interviews, and psychometric testing, as well as methods of data analysis such as structural equation modeling.

The book is a must-read for any second language researcher or applied linguist interested in investigating the effects of IDs on language learning, and for any educator interested in taking account of learners' individual differences to maximize the effects of second language instruction.

PART 1
Introduction

1 Individual Differences in Second Language Acquisition Theory, Research, and Practice

Shaofeng Li, Phil Hiver, and Mostafa Papi

DOI: 10.4324/9781003270546-2

Introduction

Individual difference (ID) variables are learner traits and characteristics that may have an impact on learning processes, behaviors, and outcomes. This book provides a thorough discussion of the theory, research, and pedagogy pertaining to the role ID factors play in second language acquisition (SLA). It goes beyond the traditional repertoire and includes more than 32 chapters covering a full spectrum of ID topics on learners’ cognitive, conative, affective, and demographic/sociocultural variations as well as commonly used methods in ID research. The book is motivated by the importance of IDs in SLA and the lack of a handbook-type volume that provides a comprehensive coverage and in-depth discussion of the various facets of each ID construct. In SLA, IDs receive extensive attention in nearly all start-of-the-art volumes (Ortega, 2009), handbooks (Loewen & Sato, 2017), and introductory guides (Gass et al., 2013). There have also been monographs on IDs as a substantive domain (Robinson, 2002; Skehan, 1989) and on single ID variables such as language aptitude (Wen et al., 2019), working memory (Wen et al., 2015), motivation (Dörnyei & Ushioda, 2021), learning strategies (Griffiths, 2013), and anxiety (Gkonou et al., 2017). In psychology, there are specialized journals for IDs in general, such as the Journal of Individual Differences and Learning and Individual Differences, as well as journals for specific ID variables, such as Emotion, Journal of Memory and Language, and Motivation Science. In our field, there is only one such journal—the Journal for the Psychology of Language Learning.

Despite the importance attached to IDs in SLA and the large amount of research that has been conducted, there has been no volume providing a systematic, thorough examination of ID research. The only volumes that focus exclusively on IDs are Skehan (1989), Dörnyei (2005), and Dörnyei and Ryan (2015), which provide invaluable insights and guidance for ID research. However, these volumes mainly include the “classic” ID variables such as personality, aptitude, motivation, learning styles, and learning strategies. Other important and extensively researched variables, such as working memory, age, identity, and so on, were either excluded or received little attention. For example, in Dörnyei (2005), while the “major” variables (such as motivation) received chapter-length discussions, other variables (such as anxiety and learner beliefs) were condensed into one chapter because “they do not warrant a chapter of their own” (p. 8). Clearly, the field is in urgent need of a volume that serves as a one-stop reference where the reader has comprehensive access to knowledge and information about all ID variables. This volume would constitute a timely initiative that fills a significant gap. In the rest of this chapter, we discuss the scope and significance of IDs, present views of the role of IDs in SLA theories, provide an overview of ID research, and give an introduction to the volume including chapter structure, major sections, and contributions to the field.

Scope and Significance of IDs

Individual difference factors or variables refer to traits, dispositions, and characteristics, be they biological, social, psychological, or a combination of these, that make learners unique individuals, cause variation among learners, and are hypothesized to have a direct and/or indirect impact on learning outcomes. In this conceptualization, IDs go beyond the cognitive and affective domains such as language aptitude, motivation, and anxiety, and include learners’ individual variations in age and social identity, such as gender and ethnicity. Also, IDs are predictors of learning outcomes rather than learning outcomes per se; in other words, they are conceived as independent variables that influence learners’ achievements in a second language. However, conceiving IDs as predictor or independent variables does not prevent researchers from investigating IDs as dependent variables, for example whether working memory is subject to training or whether aptitude increases with age. Rather, it is meant to clarify that the rationale for investigating IDs is primarily because of their significance in making a difference in learning outcomes. It is also possible that the predicted learning outcome of an ID variable may have a subsequent impact on the ID variable itself. For example, while anxiety is often hypothesized to be an independent variable that causes low achievement, it is also possible that anxiety is a result of low achievement (Skehan, 1989). Notwithstanding the possibility that low achievement is a source of anxiety, the primary reason for investigating anxiety is its posited harmful effects on learning outcomes. It is necessary to further clarify that as independent variables, IDs may be directly related to learning outcomes or indirectly associated with learning outcomes by influencing learning behaviors and processes that are considered or proven important for learning outcomes, such as learners’ noticing of corrective feedback and production of language-related episodes.

The taxonomy of ID factors in second language (L2) research has been notoriously equivocal. For example, Robinson (2002) divided ID factors into two broad categories: cognitive and conative/affective, with the former being more stable (e.g., working memory) and the latter more malleable (e.g., anxiety). MacIntyre (2002) stated that affective variables include attitude and motivation, anxiety, and self-confidence, while cognitive variables include aptitude, intelligence, and strategies. The categorization scheme proposed by Cronbach (2002), which includes affective, conative, and cognitive dimensions, seems more informative and elaborate: “Affective has to do with feelings and emotions. Conative has to do with goal setting and the will. And cognitive refers to analysis and interpretation. It includes reasoning, remembering, and using symbols” (p. 4). Drawing on Cronbach’s typology and adding one more category, we divide the ID factors covered in this volume into four categories: cognitive, conative, affective, and sociocultural/demographic differences. In this taxonomy, cognitive variables include language aptitude, working memory, declarative/procedural memory, learning strategies, cognitive styles, and metacognition; conative variables subsume motivation, mindsets, goal complexes, and willingness to communicate; affective variables encompass anxiety, enjoyment, self-efficacy, and learner beliefs; and sociodemographic variables comprise age and identity. We realize that this taxonomy may not be perfect and that there may be an overlap between certain categories, especially between conative and affective variables, but it provides a convenient framework to organize the chapters.

The significance of ID factors lies in their predictive power on learning outcomes, their explanatory functions in the mechanisms of L2 learning, and their implications for the practice of language teaching and learning. First, regarding the predictive power of IDs, a number of meta-analyses have been conducted that aggregated all empirical evidence on particular ID variables, such as language aptitude (Li, 2016), motivation (Masgoret & Gardner, 2003), anxiety (Zhang, 2019), and working memory (Linck et al., 2014). These variables have been found to be significantly predictive of L2 achievements, the mean correlations ranging from 0.3 to 0.5, suggesting that the variables account for around 10–25% of the variance in L2 learning, which is remarkable given the multitude of factors contributing to L2 achievement, such as the quality of instruction and availability of resources.

Second, the findings of ID research contribute to a more accurate understanding of the mechanisms of language learning. By way of illustration, to examine the theoretical dispute over the nature of language learning, such as whether it is explicit or implicit or whether it involves the dual process of implicit and explicit learning (Krashen, 1982), one can explore whether implicit and explicit cognitive abilities contribute to L2 proficiency and whether the two types of cognitive abilities are differentially predictive of implicit and explicit knowledge, learning, and instruction (Li, this volume). Likewise, to ascertain whether early and late bilinguals learn a second language differently, one can explore whether their ID traits or characteristics are associated with their L2 attainment in different ways (Granena, 2013). Similarly, to understand whether learning at initial and later stages occurs in different ways, one can collect evidence to examine whether different ID factors, such as declarative and procedural memory, are implicated at different stages of learning (Hamrick, 2015).

Third, the findings of ID research have invaluable pedagogical implications. One way to draw on ID research is to design remedial treatments based on research findings to change learners’ propensity or performance on a certain variable, such as enhancing learners’ motivation (Le-Thi et al., 2020), boosting learners’ self-efficacy (Wyatt, this volume), and decreasing their anxiety (Kralova et al., 2017). A second way is to take pedagogical steps to support learners with weaknesses on a certain variable that impacts learning. For example, the meta-analyses on anxiety (Zhang, 2019) showed that anxiety has stronger associations with listening than speaking, writing, and reading, suggesting that teachers should make a special effort to reduce learners’ anxiety and mitigate the harmful effects of anxiety in listening activities or assessments, such as allowing students to view questions before starting to listen or providing background information about the listening activity. A third way practitioners can take advantage of research findings is to adapt instruction and utilize activities that fit learners of different ID profiles (Papi, 2018). This recommendation is based on evidence that the same ID variable has differential associations with the effectiveness of different types of instruction (Li, 2013), and that instruction that matches learners’ cognitive strengths is more effective than instruction that does not (Wesche, 1981). Skehan (1989, 2002), citing several aptitude studies using cluster analysis to profile learner types, claimed that there seem to be three types of learners: those who are balanced in both memory and analytic ability and those who are strong in either of the two aptitude components. He indicated that instruction can be tailored to accommodate the three learner types. However, to date, there has been little research on learners’ ID profiles and on the matching between learner profile and instruction type. Eventually, it is hoped that sufficient evidence will be accumulated to identify ideal instruction types that fit learners with different ID profiles or configurations, such as high/low anxiety + strong/weak working memory, etc. In order to provide meaningful pedagogical guidance, researchers need to manipulate instructional treatments systematically and maintain a high degree of consistency across studies because slight methodological variation may make a difference in ID-achievement associations. Finally, ID research can serve other pedagogical purposes such as diagnosing learning impairments in cognitive abilities, selecting candidates for language classes/programs, placing learners with comparable profiles into different classes, and evaluating the effectiveness of a language program/class given learners with certain ID profiles (Li, 2017a).

Theoretical Perspectives

A theory explains an observed phenomenon regarding its nature and mechanism and makes predictions or hypotheses about related processes, outcomes, and behaviors (Long, 1990; VanPatten & Williams, 2015). Theories are important for empirical research because they provide guidance on the conceptualization of the construct to be examined, and make it possible to formulate clear, specific research questions/hypotheses, develop or select valid instruments to answer the research questions or test hypotheses, maintain methodological consistency across studies, and analyze data and interpret results in a meaningful way. Therefore, theories are essential for the construct validity of empirical research (Cooper, 2010), which refers to whether an empirical study is implemented in line with the theoretical conceptualization of the variable and whether the interpretations of the results are accurate. Theories are of special importance to ID research because many ID variables are not directly observable (hence “latent” variables), they are multidimensional/componential, and they overlap. For an ID variable to be a useful construct that explains L2 learning processes, behaviors, and outcomes, the construct needs to be theoretically conceptualized and distinguished from other variables before being empirically tested. ID studies that lack a solid theoretical basis are often based on unsystematic and isolated assumptions, observations, and practical considerations, and do not provide well-defined construct descriptions pertaining to its nature, content, and the nomological network for the ID’s association with other variables and with learning outcomes. Take language aptitude for example. Early aptitude research is, for the most part, atheoretical—it was test-, observation-, and practice-driven and targeted primarily predictive validity, namely whether it is correlated with learning outcomes. The objective was to develop tests based on observations of how learning occurred in the language classes during that period (1950s), and the validity of the tests was determined solely by whether significant correlations could be found between aptitude scores and course grades. However, the measured construct was not clearly defined. For example, the tests, such as the MLAT and the PLAB, include sections on English (L1) vocabulary, and the PLAB even includes sections on candidates’ GPA and motivation. Thus, although significant correlations were found for the test batteries, the results did not seem to accurately represent...

Table of contents

• Cover
• Half-Title
• Series
• Title
• Copyright
• Contents
• List of Figures
• List of Tables
• About the Editors
• Contributors
• Authors of Theoretical Excerpts
• Foreword
• PART 1 Introduction
• PART 2 Cognitive Differences
• PART 3 Conative Differences
• PART 4 Affective Differences
• PART 5 Sociocultural and Demographic Differences
• PART 6 Individual Difference Factors for Aspects of Second Language Learning
• PART 7 Research Methods
• Index