Modified Literature Circles: Improving ESP Students’ English-speaking Skills Through Movie Circles
Bibliographic record
Abstract
For Thai students, English-speaking skills have been among the most problematic. This study aims to compare the English-speaking skills of English for Specific Purposes (ESP) students before and after employing movie circles, and to investigate their attitudes toward employing movie circles. The participants consisted of 30 ESP students studying a dual program in social development and education at a public university in Thailand. They were also classified as pre-service social studies teachers. A mixed-methods study was performed utilizing the one-group pre-test-post-test design. Both qualitative and quantitative methods were employed. The instruments were movie circle lesson plans, pre- and post-English-speaking tests, an attitude questionnaire, and semi-structured interview questions. The results revealed significant improvement in the ESP students’ English-speaking skills, as well as positive attitudes toward using movie circles to improve English-speaking skills. The findings suggest that movie circles, or peer-led discussion activities, can be integrated into ESP classrooms with the specific goal of improving English-speaking skills.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".