Bibliographic record
Abstract
Communicative Language Teaching (CLT) approach has been a well-recognized language pedagogy for decades in the world. While most of the research of CLT approach focuses on the nature of teaching and learning, teacher roles in CLT approach are less discussed and examined in the literature. The present study thus intends to look into the roles of teachers in a communicative English course through questionnaires. The questionnaires were distributed to a group of 103 university students who had learnt a communicative English course at the university for at least one year. Students were required to use metaphors to indicate how they perceived their English teachers in the CLT course by completing the stem “While learning the communicative English course, the English teacher of the course is (like) ________ because ___________.” After data were collected and later coded, categorized and analyzed, results showed that the roles of teachers in the communicative English course mainly fell into four groups: the cognitive category of providing knowledge, the affective category of interesting students with authentic learning materials and interactive learning activities, the managerial category of assisting, guiding, monitoring the learning processes as well as designing learning activities for the class, and finally the fourth group of mainly negative perceptions. The researcher holds that the role of providing and transmitting knowledge is a constituent part of the teacher role of CLT approach. Furthermore, the affective category and the managerial category unveil more inherent traits of CLT teacher roles and characterize more intrinsic features of CLT approach.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".