Practitioners’ experiences with collaborative learning among students in mathematics support centres
Why this work is in the frame
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Bibliographic record
Abstract
Practitioners in Higher Education Institutions (HEIs) have been adopting and developing the practice of Mathematics Learning Support (MLS) services for the last forty years. These services vary in size and operation, but at the core of many is a MLS centre: a room dedicated to helping students with queries, which is resourced with tutors, worksheets, whiteboards, and so on. While generally these services are designed around one-to-one interactions, students in some institutions use these centres as collaborative study spaces. Inspired by this spontaneous collaborative learning among students, this exploratory mixed methods study aims to investigate the potential active utilisation of collaborative learning by mathematics support practitioners. This article examines themes developed from a recent series of interviews with practitioners on this topic.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it