Effects of the Learning how to motivate training on pupils’ motivation and engagement during pre-service physical education teachers’ internship
Bibliographic record
Abstract
Introduction Pre-service physical education (PE) teachers have concerns about how to sustain pupils’ motivation. A training titled Learning how to motivate was designed to address these concerns. Objectives The aims of the study were (1) to compare the perceptions of high school pupils of pre-service PE teachers who had completed the training [experimental group (EG)] and pre-service PE teachers who had not completed the training [control group (CG)] about motivation; (2) to verify changes in the perceptions of EG and CG high school pupils with regard to motivational variables between the beginning and end of the internship; and (3) to compare observations of the motivational climate established by the pre-service PE teachers and of their pupils’ engagement between EG and CG. Methods The study involves a sample of four French-Canadian pre-service PE teachers (EG = 2; CG = 2) and their high school pupils (n = 89) during the pre-service PE teachers’ final internship. Data were collected using observations and questionnaires at the start (T1) and end (T2) of the internship. Results Findings revealed no significant differences between groups at T1. At T2, the EG exhibited higher levels of pupils’ perceived dimensions of an empowering motivational climate than the CG. Notably, between T1 and T2, performance-approach goals decreased, and external regulation increased in the EG. As for the CG, pupils’ perceived dimensions of an empowering motivational climate, competence satisfaction, and performance-approach goals decreased. Finally, there were some trends (p ≤ 0.15) related to differences between the groups for observed motivational climate and pupils’ engagement. Conclusion The training shows promise with regard to helping pre-service PE teachers apply theory to practice.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".