Students’ Attitudes Toward Peer Feedback: Paving a Way for Students’ English Writing Improvement
Bibliographic record
Abstract
This study aimed at exploring students’ attitudes toward peer feedback to develop their English writing ability. A mixed methods research, an embedded experimental design, was adopted to elicit students’ viewpoints toward peer feedback making use of five-point Likert scale questionnaires comprising 36 statements and six open-ended questions, which were conducted to 21 undergraduate students majoring in English in one university in the three Southern border provinces of Thailand. For the data analysis, A paired samples t-test was quantitatively analyzed, wherereas content themantic analysis was adopted for qualitative data. The overall findings illustrated that the students had a positive attitude toward using peer feedback that achieved a high level in four domains in terms of the writing process, affective strategies, critical thinking skills and social interaction ability. From the result, it could also be seen that students understood about the writing strategy and were able to conduct peer feedback process more effectively, produced improved writing performance with better grammar structure. Additionally, discussing by peers evevated critical thinking skills and developed social skills through working collaboratively. Importantly, peer feedback process supports a student-centered approach and allows students to become more autonomous learners in writing. Consequently, peer feedback should be taken into consideration in the curricula of L2 writing.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".