Teacher and school variables associated with the academic and social outcomes of students with special needs in general education classrooms
Bibliographic record
Abstract
Participants were 31 teachers, 584 students, and six principals from four schools in one large suburban Canadian school board. Student outcomes of academic self-concept and peer acceptance were measured with pencil-and-paper tasks, and teachers' ratings of students' academic progress were used as a proxy measure of academic achievement. Classroom observations were conducted as measures of effective teaching behaviors and teacher interviews were conducted as measures of teachers' attitudes and beliefs about their roles and responsibilities in meeting the educational needs of students who are designated as having special needs. Teachers' and principals' attitudes and beliefs about inclusion, as well as classroom teachers' sense of personal teaching efficacy, were also surveyed with questionnaires. The purpose of this study was to evaluate the relationships among a set of student, teacher, and school variables that have been shown to influence the effectiveness of including students with special needs in general education classrooms. The present study extends on the work of P.J. Stanovich and Jordan (2000; 2002) who have developed a feedback model for describing how such variables interact with each other to facilitate positive academic and social outcomes for students in inclusive classrooms. Therefore, P.J. Stanovich and Jordan's feedback model of effective inclusion was used as a framework for exploring the relations among the student, teacher, and school variables in the present study. Significant positive relationships were demonstrated among students' levels of academic self-concept, peer-acceptance, and academic progress. Students with special needs had significantly lower levels of academic self-concept and were socially accepted significantly less than their peers who were typically achieving. Effective teaching behaviors were a significant predictor of students' academic progress. Teachers' attitudes and beliefs about inclusion were a significant predictor of students' academic self-concept. Personal teaching efficacy was a significant predictor of teachers' attitudes and beliefs about inclusion. Implications focus on the influence that teachers have on student outcomes, particularly as teachers who demonstrated more effective teaching practices tended to have students who made more academic progress through the course of a school year than their less effective counterparts.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".