Code-Switching Explorations in Teaching Early Number Sense
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
New semiotic perspectives about the role of language in mathematics education indicate that teachers have a fundamental role in communicating and teaching the language that carries mathematical meaning. However, little is known about how educators of young children understand and use the language of mathematics. This study addresses this void. Supported by the understanding that mathematics has its own language (Pimm, 1987), the study focuses on code switching—the mixing of words from two languages—by educators as they shift between the language of instruction and the language of mathematics. A qualitative multiple case study approach utilizing discourse analysis was used to explore three early years teachers’ math talk. Findings indicate that these educators code-switched to the mathematics register when they talked about numbers, number words and counting, to revoice students’ ideas, to explain students’ and teachers’ actions, to provide new math information, and when they chose between two terms that belonged to the math register. Findings also demonstrated that educators preferred to avoid the use of the mathematics’ register and relied instead on what the educators called “familiar language.” Findings further indicated the presence of semantic patterns between perceptual terms and the mathematics register.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it