Review of Mackey, A. (2020). Interaction, feedback and task research in second language learning: Methods and design. Cambridge University Press.
Notice bibliographique
Résumé
This book by Alison Mackey focuses on three key and essential constructs in the study and research of second/foreign language (L2) learning and teaching.These are Interaction, Feedback, and Task (IFT) studies.This is the first volume and serious attempt to bring these three central constructs in L2 learning and teaching together, explain them, and show how they relate to each other and how they relate to L2 research and study.The book addresses all key topics and developments related to these three areas in an approachable manner from their early inception in the 1970s and 80s till the present time including the use of state-of-the-art technology like eye-tracking, imaging, and fMRI in research into IFT and L2 learning.Using examples from published IFT studies in leading journals, volumes, or dissertations, the book presents clear and practical advice on how to carry out research in these areas, providing step-by-step guides to design and methodological principles.The book consists of a preface, ten chapters, a glossary, a list of references and an index.The preface introduces the book, its goal, significance, and contribution to the body of literature on interaction, feedback and task (IFT) studies.The author states, "Overall, my hope is that this book will support and inspire more research into the three closely related areas of interaction, feedback, and tasks, and how they combine to promote second language learning" (p.xv).Chapter 1, Theory and approaches in research into IFT in L2 learning, introduces the theoretical and empirical foundations of research into IFT and how these three constructs are related to each other and to the wider field of L2 learning and teaching.The chapter discusses open questions and various research problems of relevance to IFT studies.Chapter 2, Designing studies of the roles of IFT in L2 learning, describes the different kinds of research designs and approaches that are available on IFT studies and how these are considered to promote L2 learning.The chapter provides a starting point for people interested in carrying out studies on these topics, or who want to appraise, critique, or better understand research methods used in IFT studies.Chapter 3, Investigating individual differences in IFT studies on aptitude, working memory, and cognitive creativity in L2 learning, describes the measures used in investigating individual differences in IFT studies like working memory and aptitude scores.The chapter also includes a thorough discussion of a relatively under-studied area, cognitive creativity in second language acquisition (SLA), and how this informs research into IFT studies.Chapter 4, Collecting introspective data in IFT research, discusses introspective research methods and how they enhance our understanding of the cognitive and social processes that underlie interactiondriven learning.In the author's words, the chapter describes "a range of commonly used tools for obtaining introspections, including stimulated recalls, think-alouds, interviews, discourse completion tasks, and self-reports on social media, all in the context of research on interaction, feedback, and tasks" (p.71).Chapter 5, Creating and using surveys, interviews, and mixed methods for research into IFT and L2 learning, focuses on surveybased research like interviews.The chapter discusses issues like designing questionnaires, question types, and how we develop and administer surveys.The chapter also explains the
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».