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Record W2191511577 · doi:10.26522/tl.v10i1.428

School-based Physical Activity: Planning with student motivation in mind

2015· article· en· W2191511577 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueTeaching and Learning · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsBrock University
Fundersnot available
KeywordsPsychologyMathematics educationMacroPhysical activitySample (material)PedagogyMedical educationComputer scienceMedicine

Abstract

fetched live from OpenAlex

Central to providing rich and diverse PA opportunities in schools are our classroom teachers. Regardless of generalist or specialist training in health and physical education, all of our Ontario teachers play a vital role in providing opportunities for children and youth to learn through PA. This paper (a) positions student participation in school-based PA as an essential public health outcome, (b) explores barriers affecting teachers’ efforts to provide school-based PA, and (c) offers teachers one potential macro planning and instructional solution to address a single barrier-the challenge associated with planning for student motivation in school-based PA settings. Keller’s (1987) influential ARCS model of motivational design provides the foundation for the proposed solution. An adapted version, the ARCS School-Based PA model, is presented. The adapted model offers considerations and sample category success strategies that could be embedded in teachers’ current school-based PA planning and instructional practices to support the development of school-based PA programming that is firmly grounded in learner motivation and needs.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.397
Teacher spread0.343 · 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