Gains in pre-service teacher efficacy for inclusive education: contributions of initial beliefs and practicum length
Bibliographic record
Abstract
This study investigated how pre-service teachers’ self-efficacy for teaching within inclusive classrooms changes over the course of their teacher education programme, what factors predict levels of self-efficacy, and what factors contribute to gains in self-efficacy. Two hundred and twenty-four Canadian pre-service teachers completed a demographic questionnaire, the Beliefs about Learning and Teaching Questionnaire (BLTQ) and the Teacher Efficacy for Inclusive Practices scale (TEIP) at two points in time: at the onset of their first course on inclusive education, and again approximately one year later. The results of this study showed that participants with a higher number of weeks on practicum experienced growth across all three factors of self-efficacy measured by the TEIP. Additionally, participants who held more pro-inclusion beliefs experienced more gains in self-efficacy in their abilities to use inclusive instruction and manage student behaviour in the classroom. The grades participants were preparing to teach (elementary or secondary) and their amount of experience with diverse populations predicted initial self-efficacy, however these factors were mostly not associated with gains in self-efficacy. Implications for practice and research 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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".