Enriching mathematics expectations in grade one with a Reggio-inspired emergent curriculum
Bibliographic record
Abstract
"This thesis researches the mathematics learning of young children. In a school seriously invested in the Reggio Emilia experience for ten years, grade-one learning is project based. I pose the question is it possible to enrich numeracy expectations in the Ontario mathematics curriculum for grade one, while engaging in a Reggio-inspired emergent curriculum? As a teacher/researcher I observed and listened carefully to the students' interactions. I facilitated discussions, problem solving and directions for the project, while remaining open to the children's mathematical theories. I paid close attention to their hypotheses about proportion as well as their exploration into perimeters, and I supported their math manipulatives "factory." Pedagogical documentation in the form of graphic novels demonstrates how emergent curriculum weaves play-based inquiry with sophisticated mathematical thinking. I argue that emergent curriculum and provincial expectations can co-exist in a grade one classroom to infuse complex mathematical thinking with joy and beauty."
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.001 | 0.000 |
| 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 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".