Maximizing feedback for language learning: English language learnersâ attention, affect, cognition and usage of computer-delivered feedback from an English language reading proficiency assessment
Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
Attention to personalised feedback for language learning is increasing as computer-based assessment increases practicality, but little attention has been paid to how language learners interact with and use feedback from computer-based assessments. The purposes of the present research were two-fold: to investigate how adult immigrant English language learners engaged with and processed computer-based feedback on their English reading skills, and to explore how these learners used feedback depending on their processing outcomes, psychological characteristics, and English proficiency. To examine these issues, six data sources were analysed using mixed methods for complementary and developmental purposes through interviews, surveys, language assessments, and eye tracking with 102 adult immigrant English language learners in Canada. Data were analysed using qualitative coding and analysis and quantitative methods such as regression analyses and latent class profiling. Results were organized and synthesized by research questions. \nStudy findings were that the personalised sections received most attention, particularly visual results, but detailed descriptive text was useful at intermediate stages of feedback processing and usage. Learnersâ cognitive and affective strategies for negotiating feedback included emotional reactions, deflecting responsibility for negative feedback, critically evaluating report content, negotiating comprehension difficulties, and relating the report to their own lives. Learners were generally positive about personalised feedback, adapted it for their own purposes, and used known affective and cognitive strategies, confirming earlier research in these areas. In addition, confirming other previous research, major factors impacting understanding and usage were external circumstances such as English language environment and language proficiency. A mastery goal orientation, trust in report content, reflection on English skills, and desire to use the report, were positively associated with report usage. \nImplications included an observed need to fully factor feedback design into test design where impact/effects/outcomes are a guiding principle in test validation processes. From an instructional perspective, a key implication was the need to embed feedback in a high-quality, regular, and social learning environment. Further research is required to understand how feedback design can be personalized to promote more constructive feedback usage in learners with different background characteristics.
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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 | 0,000 | 0,000 |
| 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 | 0,002 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 découle