Patterns of Teacher‐Student Interaction in Inclusive Elementary Classrooms and Correlates with Student Self-Concept
Bibliographic record
Abstract
The efficacy of placing students with special needs in inclusive classrooms may depend in part on how instructional factors contribute to student outcomes. Differences in frequencies and levels of cognitive engagement of interactions among nine teachers in inclusive elementary classrooms were related to three other variables: teachers' ratings on the Pathognomonic-Interventionist (PATH/INT) Scale, students' designation either as exceptional or at-risk (EX/AR) or as typically achieving (TA), and students' scores on the Piers Harris Children's Self-Concept Scale. Teachers with PATH beliefs, who attribute learning difficulties to permanent characteristics of the student that are beyond the teacher's mandate, interacted infrequently with their EX/AR students at low levels of cognitive engagement. Teachers with INT beliefs, who see themselves as responsible for the achievement of all their students irrespective of their disabilities, interacted with all students more frequently, and at higher levels of cognitive engagement. In contrast to the PATH teachers, their EX/AR students received more instructional interactions than their TA students. As expected, the EX/AR students in all classrooms had lower Piers Harris Self-Concept Total Scale scores than typically achieving students. However, both TA and EX/AR students had lower Self-Concept Total Scale scores in the classrooms of teachers with PATH beliefs, compared to students in the classrooms of INT teachers. The relationship is discussed between teachers' beliefs, their different patterns of instructional interactions with students with and without disabilities in inclusive classrooms, and the possible impact of instructional interventions on students' self-concept.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".