Subtract? That’s a Math Word! Unpacking Teachers’ Language Choices in Preschool and Kindergarten Classrooms
Bibliographic record
Abstract
Even though a substantial body of research suggests that adults’ math talk fosters children’s mathematics development and willingness to learn mathematics, little is known about how teachers make pedagogical decisions to communicate mathematics to young students. Supported by socio-constructivist and semiotic lenses, the study focuses on the close interactions between teachers and their students to better understand the educators’ perspectives and the rationale for their mathematical pedagogies when communicating and mediating number sense to young students. An instrumental case study approach and discourse analysis were utilized to investigate how a cultural tool, mathematics, was communicated and mediated to preschool and kindergarten students. Findings indicated that participants focused on supporting young students’ meaning-making processes before teaching language form. This pedagogical choice resulted in educators creating a particular early year’s mathematical discourse grounded in the avoidance of nouns and in the use of terms that students knew, verbs, and terms that denoted actions.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 | 0.000 |
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".