Video-Stimulated Recall as a Facilitator of a Pre-Service Teacher’s Reflection on Teaching and Post-Teaching Supervision Discussion—A Case Study from Finland
Bibliographic record
Abstract
The use of video in learning to teach is not new. The vast body of research shows that both pre-service and in-service teachers benefit from analyzing video lessons conducted by experienced teachers, their peers, or themselves. In this narrative case study, we analyze one post-teaching supervision discussion about a mathematics lesson. The study provides an insight into a unique setting where teaching practice took place, i.e. one teacher training school in Finland. We aim to demonstrate one pre-service teacher’s learning process in the post-teaching discussion supported by the recursive use of video-stimulated recall (VSR). VSR was used first, as a tool for encouraging reflection on the lesson during the supervision discussion, after which the pre-service teacher was interviewed while watching a video of the supervision discussion. We argue that the recursive reflection on different kinds of videos may help pre-service teachers better learn from their own teaching experiences and from the advice of the experienced supervising teacher. In addition, arguably, the recursive use of VSR may be a fruitful method for educational researchers studying teacher education.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".