Teaching Practices and Knowledge Base of English as a Foreign Language Teachers’ Communicative Language Teaching Implementation
Bibliographic record
Abstract
This small scale study aimed at identifying (1) the characteristics of teaching practices in CLT classrooms, (2) teachers’ opinions underlying such practices, (3) their positions while adopting CLT, and (4) a knowledge base used as a framework of CLT implementation. Eight Thai teachers who regarded themselves as CLT proponents voluntarily took part in this study. Data collected via classroom observations and post-teaching semi-structured interviews indicated that CLT involved four common features including promoting ‘small talk’ in the target language, beginning the lesson with the combination of lead-in and presentation strategies, positively reacting to students’ linguistic errors, and emphasizing semi-communicative activities. The participants’ opinions underlying CLT implementation centered on playing multiple roles including lesson designers, class managers, and English users with certain levels of English proficiency. Content, pedagogical content, and subject matter knowledge served as their major elements of the knowledge base for teaching when conducting CLT lessons.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".