Learning to Teach in an Intensive Introductory TESL Training Course: A Case Study of English Teacher Learning
Bibliographic record
Abstract
Despite a growing body of research on trainee teachers’ learning during pre-service programs, intensive introductory TESL training courses are still designed to instruct a “standard” type of trainee teacher. This research study investigates the factors that mediate trainee teachers’ learning process as well as the interaction between these factors, which either facilitate and/or hinder trainee teachers’ success during an intensive introductory TESL training course. Using a qualitative holistic single-case study, informed by an interpretivist perspective, this study explores how three trainee teachers learned how to teach during a course in Southern Ontario, Canada. An integrated conceptual framework, formed by a sociocultural perspective of teacher learning, a holistic view of curriculum, and transformative pedagogy was employed and the findings include four major factors that mediated trainee teachers’ teacher learning process and three types of interaction that facilitated and/or hindered their success during the program.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.005 | 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 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".