Teacher and Learner Views on Effective English Teaching in the Thai Context: The Case of Engineering Students
Bibliographic record
Abstract
<p>This study aimed at investigating the characteristics of effective English teachers and students as perceived by 35 teachers and 613 students, as well as according to the surveys regarding the English-teaching problems in Thailand. The instruments included two questionnaires on the characteristics of effective teachers and students as perceived by teachers and students, based on five categories: rapport, delivery, fairness, knowledge and creditability, organization and preparation. The questionnaire responses were analyzed both quantitatively and qualitatively.</p> <p>The quantitative data revealed that for the teachers the most important attribute was organization and preparation attributes such as teaching preparation and the use of effective teaching methodology. The qualitative data revealed that the rapport items were important, especially that the teacher should be patient, not insult the students, and give clear advice. However, the students gave more weight to such rapport items as, for example, the teacher having a positive attitude toward to the students and being helpful, generous and caring about them. The qualitative data also revealed that well-prepared lessons and providing fun activities were mostly required for effective teachers. English teaching problems involve four aspects: teachers, learners, English learning content, and other factors. Discussion and the recommendations of the study are included.</p>
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 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".