Touch Together: Open-Ended Design of TouchCounts Shapes Parent―Child Affective Engagement in Family Mathematics
Bibliographic record
Abstract
This qualitative study investigates how the open-ended design of TouchCounts (Sinclair & Jackiw, 2014), a multi-touch application for early numeracy, shapes affective dynamics during parent―child interactions in family math activities. Drawing on inclusive materialism (de Freitas & Sinclair, 2014) and affect theory in mathematics education (de Freitas et al., 2019), the study conceptualizes affect as a relational, provisional force that circulates among parent, child, and technology, and is entangled with their interaction. It focuses on how TouchCounts elicits distinct affective dynamics through its open-ended and multimodal features (e.g., without prescribed or level-driven tasks, gesture-responsive multi-touch screen, full-screen math-object generation space, and support for explorative individual and collaborative use). Through micro-scale analysis of two excerpts from a parent-child dyad's interaction video-recordings, selected from five participating pairs in Canada, the study captures affective dynamics—expressed through gestures, embodied actions, and verbal output—as they emerge and unfold differently in each sub-environment (i.e., Enumerating World and Operating World). Findings show that the distinct affordances of each World give rise to nuanced, affect-rich interactions that embody diverse ways of mathematical thinking and communication. This research underscores the potential of open-ended digital technologies to shape the affective dimensions of early math learning in family contexts.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".