Human Relations in Instructional Supervision: EFL Trainees’ Appraisal of a TEFL Practicum
Bibliographic record
Abstract
Instructional or educational supervision is a valuable training tool that can be used to support pre-service teacher education. When it is well implemented, it helps student teachers develop self-awareness, self-assessment and self-reflection skills. This study explores a group of 18 Beninese EFL trainees’ perceptions of instructional supervision and their practicum experiences. It also examines the nature of the relations between them and their supervisors. A mixed method research design is used for the study. The data are collected through three instruments: a questionnaire addressed to the participant EFL trainees, the written records of their practicum experiences, and a follow-up interview to 6 of them who are randomly selected. The findings reveal a lot of discrepancies between the type of supervision they expected and the one they experienced during the practicum. Some useful suggestions are discussed to contribute to a better understanding of the supervisory process and the role of the supervisor in a practicum.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".