Teachers’ personal epistemological beliefs about students with disabilities as indicators of effective teaching practices
Bibliographic record
Abstract
Teachers’ epistemological beliefs, that is, their beliefs about the nature of knowledge and how it is learned, appear to be highly influential in their classroom practices. To date, the exploration of teachers’ epistemological beliefs has been complicated by philosophical and methodological disputes. A method is presented here for inferring the epistemological beliefs of elementary school general education teachers through their descriptions of their work with students with disabilities. Evidence to support the reliability of this method is also presented. Differences in teacher belief constructs are related to differences in instructional practices – a relationship which holds for instructional interactions with both individual students and the whole class, and which predicts instructional practices for students both with and without disabilities. We therefore speculate that differences in teachers’ beliefs about students with disabilities might be related to their larger epistemological theories about knowledge and learning. In speculating about the source of differences in beliefs and practice, it is notable that the normative school beliefs, that is, the prevailing beliefs in a school about teachers’ roles and responsibilities for students with disabilities, appear to influence the beliefs of individual teachers. The potential for differences in teachers’ beliefs and practices to influence student outcomes is also considered, with some preliminary evidence from student self‐concept data.
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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 | 0.005 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".