Challenging teachers’ perceptions of what mathematics is: Reflecting on culturally responsive pedagogy (CRP) in the mathematics classroom
Bibliographic record
Abstract
In the Faculty of Education, at the University of Regina, a new Certificate in Teaching Elementary School Mathematics was launched during July 2017. Correspondingly, a new course called ‘Culturally Responsive Pedagogy (CRP) in the Mathematics Classroom’ was developed as a required course for the certificate program. The aims of the course (and this related research study) were to engage participants (mainly elementary/K-8 teachers) in challenging and disrupting traditional views of teaching, learning, and knowing school mathematics as a politically-, culturally-, and value-neutral subject. Themes of social justice, equity, Indigenous education, Ethnomathematics, and linguistically-diverse learners were explored in thinking critically about and planning for CRP within approaches to mathematics teaching and learning. In this paper/presentation, results will be shared from a final reflective essay assignment which asked participants to consider areas of their own personal and professional growth with respect to CRP in the mathematics classroom.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.009 |
| 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".