Second Language Learners’ and Teachers’ Perceptions of Delayed Immediate Corrective Feedback in an Asynchronous Online Setting An Exploratory Study
Bibliographic record
Abstract
Online language courses that rely on asynchronous teacher-learner communication face a practical problem when it comes to the provision of immediate corrective feedback by the teacher in oral interaction tasks. In this learning context, learners can still communicate synchronously and record their interaction without the teacher being present, but feedback by the teacher will be delayed in time. Research indicates that the effectiveness of feedback decreases as the time between the error and the correction increases and that immediate feedback is more effective (Arroyo & Yilmaz, 2018; Shintani & Aubrey, 2016). In this exploratory study conducted at an online university, we implemented a novel type of feedback we referred to as delayed immediate corrective feedback (DICF) and analyzed second language learners’ and teachers’ perceptions regarding its effectiveness and usefulness. Our goal was to assess the feasibility of implementing this type of feedback in our context and, ultimately, in other contexts where communication between teachers and learners takes place asynchronously. DICF was provided by teachers orally via screencast video. Learners and teachers’ perceptions were collected via two separate questionnaires. The results showed that teachers and learners responded positively to DICF and several potential benefits were identified. Les cours de langue en ligne qui s’appuient sur la communication asynchrone enseignant-apprenant rencontrent un problème pratique quand vient le temps de fournir de la rétroaction corrective immédiate par l’enseignant lors des tâches d’interaction orale. Dans ce contexte d’apprentissage, les apprenants peuvent toujours communiquer de manière synchrone et enregistrer leur interaction sans que l’enseignant soit présent, mais la rétroaction de l’enseignant sera décalée dans le temps. La recherche indique que l’efficacité de la rétroaction diminue au fur et à mesure que le temps entre l’erreur et la correction augmente, et que la rétroaction immédiate est plus efficace (Arroyo & Yilmaz, 2018; Shintani & Aubrey, 2016). Dans cette étude exploratoire menée auprès d’une université en ligne, nous avons mis en place une nouvelle forme de rétroaction, que nous avons appelée rétroaction corrective immédiate retardée (RCIR), et nous avons analysé les perceptions des apprenants de langue seconde et des enseignants quant à son utilité et à son efficacité. Notre objectif était d’évaluer la faisabilité de mettre en place ce type de rétroaction dans notre contexte, et par extension, dans d’autres contextes où la communication entre apprenants et enseignants se passe de manière asynchrone. La RCIR a été fournie oralement par des enseignants à l’aide de vidéos d’écrans. Les perceptions des apprenants et des enseignants ont été recueillies dans deux questionnaires distincts. Les résultats ont montré qu’apprenants et enseignants ont réagi à la RCIR de manière positive et plusieurs avantages potentiels ont été identifiés.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".