Changing the Spots of Leopards: A Look into the Process of Teacher Change and its Impact on Inclusive Pedagogy
Bibliographic record
Abstract
For the last two decades, systems of education have been shifting special education teaching practice away from segregated classes to inclusive schools (Reiser & Secretariat, 2012; Sharma, Loreman, & Forlin, 2012; UNESCO, 1994). Despite much success, this shift has not come without its challenges. Research has found teachers’ attitudes and beliefs about students with exceptionalities influence their inclusive pedagogy (Avramidis & Norwich, 2002; MacFarlane & Woolfson, 2013; Scruggs & Mastropieri, 1996). This paper examines the current literature on teacher attitudes and beliefs towards inclusion as well as the process of teacher change. It is concluded that despite unfavourable attitudes, when teachers have training and support paired with authentic experiences, attitudes can shift and inclusive pedagogy adopted.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.021 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| 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".