A Self-Investigation into Thai EFL Writing Instructors’ Perceptions toward Written Feedback on College Students’ Writing Essay Assignment
Bibliographic record
Abstract
Although the behavior and impacts of instructor reflection in writing classes have been extensively studied over the past few decades, a significant proportion of the work has concentrated on students' attitudes and utilization of all such responses, as opposed to teachers' perspectives, self-assessments, and actual text comments given. Research findings on instructors' attitudes regarding students' written work are far from conclusive. This research gathered data from eight Thai-nationality writing instructors of English as a Foreign Language (EFL) and one hundred and six Thai undergraduate students in order to assess teachers' attitudes toward written comments. In addition, the researcher analyzed instructors' self-evaluations of written feedback and the link between their self-evaluations and whether they even responded to EFL areas. The results revealed that these instructors' self-evaluations of the comments that they claimed they generally supplied and the genuine reflection they delivered on student writing were fairly consistent. The results also reveal that while marking writing drafts, these instructors were far more bothered with local issues, particularly grammatical, and this attention persisted throughout the amendments of the writing. Instructors' predilection for and reliance on grammatical accuracy in their comments may misguide students into prioritizing writing characteristics and then into believing that a zero-blunder essay is a competent and better-quality written work. Remarkably, despite the fact that instructors appeared to dwell on local problems for correction, all favorable comments on essays focused on global features. These instructors had little professional training in evaluating student written assignments, according to the findings of this research.
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".