Teacher and school variables associated with the academic and social outcomes of students with special needs in general education classrooms
Notice bibliographique
Résumé
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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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».