Enhancing mathematical noticing of graphs through movement, voice, and metaphor: An intervention with two students with visual impairment
Bibliographic record
Abstract
This qualitative study explores the potential for metaphor, movement, gesture, and vocalization in helping learners notice mathematically important features of graphs, and in making mathematics more accessible for learners with visual impairment. Two elementary school students with visual impairment were introduced to several multimodal activities related to the graphs of mathematical functions, using a pre-/post-assessment methodology. Video recordings of the session were coded for qualitative changes in engagement with graphs through multimodal representations. After the activity intervention, both students showed improvements in their ability to voice, gesture, and describe details of mathematical graphs with accuracy and understanding. The findings demonstrate the potential of multimodal methods for teaching mathematics and enhancing other skill areas through movement, metaphor, voice, and gesture. The findings suggest that full-bodied experience with graphs can provide foundational support for learners with visual impairment to work with print or tactile graphics. We propose that purposeful selection of materials and collaboration between teachers of students with visual impairment, mathematics educators, and teachers of dance and physical education can enhance the design and implementation of effective lessons using multimodal means.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".