Review of Griffiths, C. & Soruç, A. (2020) Individual differences in language learning: A complex systems theory perspective. Palgrave Macmillan.
Notice bibliographique
Résumé
Individual Differences in Language Learning: A Complex Systems TheoryPerspective presents a wholly contemporary analysis of individual differences (IDs) in second language acquisition (SLA).Griffiths and Soruç approach this topic through a novel lens, positing that IDs in SLA are not isolated phenomena but complex interwoven processes.This argument is developed throughout, scrutinizing IDs through a complex dynamic systems theory (CDST) perspective and hypothesizing that IDs are interrelated such that a change in one will likely spur change in others.The text situates itself firmly in modern discourse on IDs as a multifactorial component of SLA, providing timely insights on trends in second language (L2) research with appropriate considerations for educators and learners.Two conceptual chapters bookend eleven central chapters that each profile a different ID.Chapter 1 gives an overview of foundational research, parameters for the book, the theoretical perspectives that drive the work, and short synopses of the coming chapters.The authors briefly introduce the CDST perspective of IDs, noting that the text will focus on one ID at a time to mitigate the potential chaos that comes with research in complexity theory, and then outline the eleven profiled IDs.Chapter 2 examines age as a variable by juxtaposing young, adolescent, and adult L2 learners.The authors note that perceptions of age have shifted over time, with early research often concluding that youth is advantageous for L2 development and more recent research suggesting that since age interacts with varied affective factors, conclusions should seek to contextualize the impact of age on language learning.Chapter 3 explores sex and gender, delineating that while sex is a biological construct, gender is a cultural construct.The authors therefore discuss that the effects of encultured gender on L2 development should not be ignored.The authors contend that the research shows little difference in language learning abilities between the sexes and conclude that gender should be considered as one factor that may interact with other IDs.Chapter 4 focuses on four overlapping, non-malleable IDs: race/ethnicity/nationality/culture.This chapter approaches the IDs through research into culture shock in a foreign country and how it affects communication in the target language, finding that proficiency plays an integral role in understanding how well a learner may assimilate into the target culture.Chapter 5 considers aptitude, examining learners' capacity for L2 development through profiles of exceptional language learners' IDs and practices, finding overlapping patterns of age, working memory, motivation, time on task, and sociocultural interaction.Chapter 6 explores personality, questioning whether there is a direct correlation between personality and language proficiency.In this chapter, the authors report that motivation, willingness to communicate, and ego were more prominent factors in SLA than personality itself.Likewise, chapter 7 defines learning style as learners' habits and preferences for information processing and suggests that while styles are typically considered stable, learners can be taught to style stretch.Furthermore, this chapter presents evidence that those students who can style stretch tend to score better.Chapter 8 examines learning strategies, considering the role of consciousness and type in strategies and presents CJAL
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,007 | 0,011 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,004 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,011 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».