The impact of a teacher education course on pre‐service teachers' beliefs about inclusion: an international comparison
Bibliographic record
Abstract
In this comparative study, the impact of two stand‐alone university courses on pre‐service teachers' attitudes, concerns and teaching efficacy to teach in inclusive classrooms is examined. Twenty‐eight pre‐service teachers ( PSTs ) from A ustralia and 60 PSTs from C anada completed a survey at pre‐ and post‐stages of the course. It was found that after completion of the course, Australian participants' attitudes improved, their concerns declined, and they became more confident in their ability to teach in inclusive classrooms. Similarly, C anadian participants' concerns declined and their teaching efficacy improved, but they became more apprehensive about teaching in inclusive classrooms. Relationships among the three variables (attitudes, concerns and teaching efficacy) were examined at pre‐ and post‐test stages for both cohorts to understand how they interacted within each of the two countries. Implications of the findings for teacher education are discussed.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".