Teachers' attitudes towards inclusion as linked to teachers' sense of efficacy
Bibliographic record
Abstract
In Quebec, meeting the needs of students with special needs and including these children in the general education classroom, is believed to foster their learning and social competence. Teachers have often reported that they do not always feel prepared to teach students with special needs. The purpose of this study was to examine the relationship between teachers' attitudes toward inclusion and teachers' sense of self-efficacy and the quality of the student-teacher relationship. Thirty-four teachers from the region of Montreal, teaching students with special needs in the regular French immersion classroom, responded to four questionnaires and to two open-ended questions, and shared their views and attitudes toward inclusive education. Findings revealed that a positive attitude towards inclusion was related to positive teaching efficacy. Moreover, teachers' attitude varied across disabilities. More specifically, teachers' positive attitude was related to teaching students with academic difficulties and social maladjustments. Teachers' negative attitudes toward inclusion were related to teaching students with behaviour problems and physical disabilities. Teachers also suggested that a variety of resources such as teacher assistants, academic resources and a smaller student-teacher ratio would be beneficial toward successful inclusive practices.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| 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".