Learning in Motion: Teachersâ Perspectives on the Impact of Stationary Bike Use in the Classroom
Bibliographic record
Abstract
The potential of physical activity to support self-regulated learning in the classroom has encouraged the implementation of stationary bicycles across Canada and the United States. Positive testimonials suggest that their use by students has positive outcomes, but there is limited empirical evidence supporting the efficacy of this pedagogical practice. The current study analyzes teachers‟ perceptions of the use and impact of stationary exercise bicycles in classrooms as part of a community running program initiative through a nationwide survey of 107 participants. Key findings identify teacher perceptions of positive outcomes in students‟ social, emotional, and cognitive development, as well as to the learning environment. A small set of unique challenges were posed by the bike integration, including limited distraction and some scheduling difficulties. Teachers approached the integration of the bikes on a spectrum of control from “student-regulated” to “teacher-regulated” with some combination of both, and movement from teacher-directed use to more student-initiated use after the bike was in use for some time. The implications for the use of stationary bikes as a tool for self-regulated learning in an active classroom are discussed and future research measuring learning outcomes is suggested.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".