Exploring Teachers' Fears and Resistance when Learning about Culturally Responsive Pedagogy in the Mathematics Classroom
Bibliographic record
Abstract
In this study, we examine the fears and resistance of prospective and practicing teachers (PPTs) toward culturally responsive pedagogy (CRP) in mathematics classrooms. Drawing on reflective journal assignments collected during several offerings of a teacher education course in Canada, we ground our analysis in Ladson-Billings’ elements of a culturally relevant pedagogy and extend it through our COFRI model (Challenges, Opportunities, Fears, Resistance, Insights). Our use of thematic analysis with PPTs’ reflections reveals that PPTs experience mathematical, pedagogical, and ideological fears, alongside forms of resistance which can also be categorized as mathematical, pedagogical, and ideological. These PPT-expressed fears and resistance serve as barriers to developing one’s CRP, highlighting tensions between personal and professional identity, systemic constraints, and the complexities of implementing CRP. To address these barriers, we introduce reflective praxis tools that encourage PPTs to confront and navigate their fears and resistance. Through this research, we aim to advance understandings of CRP in mathematics education and offer actionable strategies for promoting equitable and culturally responsive teaching practices.
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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 | 0.024 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.019 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".