Nonspecialist Preservice Primary-School Teachers: Predicting Intent to Teach Physical Education
Bibliographic record
Abstract
The purpose of this study was to establish the utility of the Theory of Planned Behavior in predicting nonspecialist, preservice primary-school teachers’ intentions to teach physical education for 2 hr per week. A questionnaire was developed, according to the recommended procedures, and was administered to 128 final-year teacher trainees in two Primary Teacher Training courses in England. A variety of predictors were identified, including beliefs of significant others, such as parents; a positive assessment of control over difficult barriers; and experiences of past (teaching) behavior. The most significant predictor in discriminating between intenders and nonintenders, however, was personal exercise behavior. Helping preservice primary-school teachers become more physically active themselves might positively influence their intent to teach physical education 2 hr per week more than alleviating barriers to teaching physical 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".