Student Writers’ Affective Engagement with Grammar-Centred Written Corrective Feedback: The Impact of (Mis)Aligned Practices and Perceptions
Why this work is in the frame
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Bibliographic record
Abstract
This project firstly explored Iranian English as a foreign language (EFL) students’ perceptions about written corrective feedback (WCF)-related practices and preferences. Secondly, the student participants’ first language (L1; e.g., Farsi) learner identities were operationalized, especially focusing on the skill of writing, WCF, and grammar-centred WCF. Thirdly, the students’ affective engagement with WCF was scrutinized, particularly in light of L1 student identities. The participants in the study were 15 students in an Iranian EFL context. Analysis of interview data revealed that the skill of writing was held in low regard by the students. Also, several discrepancies emerged vis-à-vis WCF methods (e.g., direct vs. coded), error correctors (e.g., teacher feedback vs. peer feedback), the amount of correction (e.g., selective vs. comprehensive correction), and the relative importance of different components of writing (e.g., grammar vs. content vs. organization). In particular, the findings showed that the students’ L1 identities involved low regard for writing, but high regard for speaking skills, and that they attached high value to grammatical accuracy and teacher explicit feedback. Finally, the findings indicated that: (a) the students’ second language (L2) identities (e.g., WCF-related preferences) were profoundly affected by their L1 student identities, and (b) the discrepancies between the students’ L2 writing preferences (e.g., preferred amount of WCF) and the teachers’ reported practices could potentially hinder students’ affective engagement with WCF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it