The teacher is a facilitator: Reflecting on ESL teacher beliefs through metaphor analysis
Bibliographic record
Abstract
Metaphors offer a lens through which language teachers express their understanding of their work. Metaphor analysis can be a powerful reflective tool for expressing meanings that underpin ways of thinking about teaching and learning English as a second/foreign language. Through reflecting on their personal teaching metaphors, teachers become more aware of the beliefs that underpin their work. This paper reports the reflections on the prior beliefs of three experienced ESL teachers in Canada through the use of metaphor analysis. The paper attempts to explore the prior beliefs of the three experienced ESL teachers in Canada through metaphor analysis by using the Oxford et al. (1998) framework as a theoretical lens in which to gain understanding of the use and meaning of these metaphors. Results indicated that all three teachers used a total of 94 metaphors throughout the period of the group discussions and interviews, and that the metaphors used most were those related to learner-centered growth, followed by social order, then social reform.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.066 | 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".