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Record W3131892636 · doi:10.1123/jtpe.2020-0186

An Actor-Oriented Perspective on Implementing a Pedagogical Innovation in a Cycling Unit

2021· article· en· W3131892636 on OpenAlexaff
Andy Vasily, Tim Fletcher, Doug Gleddie, Déirdre Ní Chróinín

Bibliographic record

VenueJournal of Teaching in Physical Education · 2021
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsKootenay Association for Science & TechnologyAlberta Advanced EducationBrock UniversityUniversity of Alberta
FundersKing Abdullah University of Science and Technology
KeywordsPerspective (graphical)InsiderUnit (ring theory)Class (philosophy)Physical educationMathematics educationPsychologyPedagogySociologyComputer scienceEpistemology

Abstract

fetched live from OpenAlex

Purpose: The purpose of this research was to use an actor-oriented perspective to analyze one teacher’s implementation of the Meaningful Physical Education approach in one Grade 5 classroom in Saudi Arabia. Method: A single case study design was used, with the case being defined as Andy and his teaching of a cycling unit to one Grade 5 class. Data consisted of blog posts, tweets, and semistructured interviews. Results: Andy identified several spheres of influence on implementation, including his personal philosophy, students, co-teachers, and several organizational/environmental characteristics of King Abdullah University of Science and Technology (KAUST) School, as well as important attributes of the innovation that supported implementation. Discussion/Conclusion: An actor-oriented perspective offered insight into a teacher’s insider perspective of a pedagogical innovation, which enabled understanding of how he made sense of Meaningful Physical Education and used those ideas to guide planning, instructional, and assessment decisions in the cycling unit.

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)0.012
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0060.027
Scholarly communication0.0100.007
Open science0.0020.004
Research integrity0.0030.003
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 head0.185
GPT teacher head0.601
Teacher spread0.416 · 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 designQualitative
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

Citations12
Published2021
Admission routes1
Has abstractyes

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