Exploring teacher practices for enhancing student engagement in culturally diverse classrooms
Bibliographic record
Abstract
Self-regulated learning (SRL) and culturally responsive teaching (CRT) research, although from different viewpoints, both show instructional practices that enhance student engagement. This study examined the integration of self-regulated learning promoting practices (SRLPPs) and culturally responsive pedagogical practices (CRPPs) in the classroom context especially during a complex task. Using mixed-methods case study design, it explored how an elementary classroom teacher at a multicultural public school in the West Coast of Canada combined SRLPPs and CRPPs to support culturally diverse students’ engagement. Data were collected through:(a) classroom observations, (b) practice records and documents, (c) students’ work samples, (d) teacher interview, (e) student interviews, and (f) student surveys. Findings indicated that the teacher enacted integrated practices categorized as: (a) classroom foundational practices; (b) designed instructional practices; and (c) dynamic support practices. Also, students’ engagements related to their perceptions of teacher practices. Culturally diverse students were highly engaged in contexts with rich combinations of SRLPPs and CRPPs. Finally, this paper discussed the implications for theory (e.g., CRT, SRL), practice (e.g., an integrated pedagogy), and research (e.g., how to support culturally diverse learners’ engagement in contexts).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".