EFL Learners Interaction with Feedback Presented through a Computer-Assisted Reading Program
Bibliographic record
Abstract
This article examines the interaction patterns of second language (L2) learners when engaging with different types of feedback presented through a computer reading program. There were 12 EFL learners who were asked to complete reading exercises in the program, and the way they interacted with the feedback provided was examined through interviews, observations and think-aloud exercises. The qualitative analyses explored participants' experience of the reading feedback and how EFL learners of different language levels behaved when presented with knowledge of correct response (KCR), elaborated feedback (EF), and no feedback. The results showed limited use of the EF, and most students relied on KCR to guide their reading. In addition, many of the participants commented on the complexity of the EF, which presented as a barrier to facilitating reading comprehension. From the interviews, it was discovered that feedback could negatively influence the reading experience for low-level learners as the feedback was not accessible enough to help in the reading comprehension process.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".