Towards classroom inclusivity: exploring K-12 teachers’ sensitivity to cultural diversity ( <i>Hacia la inclusividad en el aula: explorando la sensibilidad a la diversidad cultural del profesorado de K-12</i> )
Bibliographic record
Abstract
The study explored teachers’ awareness of classroom cultural diversity using a cross-sectional survey and thematic content document analysis of Ghana’s inclusive education policy and teacher professional development manuals to explore teachers’ cultural diversity awareness. 219 K-12 teachers completed the survey. The study found that teachers are culturally sensitive to working with culturally diverse families and the use of non-standard English. However, most of the teachers have limited general cultural diversity awareness of their classrooms. Consequently, teachers are less culturally sensitive to using multicultural teaching methods and creating a multicultural classroom environment. Further, teachers are less culturally responsive in their assessment practices. Our study also revealed that although teachers were introduced to multicultural education during their initial teacher training programme, within their schools, there was limited ongoing teacher professional development on multicultural education. Results from the thematic content document analysis of the inclusion policy showed that within Ghanaian schools, there are no practical guidelines on how in-service teachers and pre-service teachers can be supported to address cultural diversities in the classroom and schooling contexts.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".