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Record W1564909293 · doi:10.1080/2331186x.2015.1045808

The efficacy of exergames for social relatedness in online physical education

2015· article· en· W1564909293 on OpenAlexaff
Brian J. Kooiman, Dwayne P. Sheehan

Bibliographic record

VenueCogent Education · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicImpact of Technology on Adolescents
Canadian institutionsMount Royal University
Fundersnot available
KeywordsOxymoronPsychologyPhysical educationCurriculumSocial contactThe InternetSocial psychologyPedagogyMathematics educationComputer science

Abstract

fetched live from OpenAlex

Online physical education (OLPE) has been viewed as an oxymoron. Physical education curriculum at all levels seeks to help learners grow socially in the way they interact and deal with diverse and challenging fellow students and settings. Students who have no contact with other students while they are at home for various reasons may not be able to learn the proper response to the challenges of social participation or benefits derived from social contact. This study looked at the efficacy of remote exergame participation between students aged 11–18 (N = 124). The results show that exergaming over the Internet can provide students with a social experience that results in increased relatedness between participants versus playing by themselves against a non-player character (NPC). This relatedness can help students access the social standards for physical education when enrolled in OLPE.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.048
GPT teacher head0.412
Teacher spread0.364 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations43
Published2015
Admission routes1
Has abstractyes

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