Motivation to Move with Exergaming in Online Physical Education
Bibliographic record
Abstract
Motivation to move is critical in online physical education (OLPE). This study looked at the motivational aspect of remote exergaming versus another student versus proximally against a console generated non-player character (NPC). Research shows that students in grades 4-12 are motivated to play exergames because they are native gamers. The entertainment value of the exergame garners more effort from the students than they realize they are expending. This research showed that exergames are motivating for students (N=124) aged 11-18 in grades 6-12. The subjects reported high motivation to participate while playing both a computer-generated NPC and a remote human opponent over the internet. Scores for motivation were highest when subjects played another student over the internet but were also high for proximal NPC play. This research positions exergaming as a potential piece of OLPE curriculum that can help students access the emotional aspect of physical education curriculum.
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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 | 0.000 | 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".