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Record W3001489932 · doi:10.1080/25742981.2020.1715232

Physical education teachers’ (lack of) gymnastics instruction: an exploration of a neglected curriculum requirement

2020· article· en· W3001489932 on OpenAlexaffabout
Daniel B. Robinson, Lynn Randall, Erin E. Andrews

Bibliographic record

VenueCurriculum Studies in Health and Physical Education · 2020
Typearticle
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsUniversity of New BrunswickSt. Francis Xavier University
Fundersnot available
KeywordsCurriculumPhysical educationCompetence (human resources)Mathematics educationPsychologyPedagogySocial psychology

Abstract

fetched live from OpenAlex

Gymnastics is named as one of four or five broad movement domains within all of Canada’s provincial/territorial physical education (PE) curriculums. However, in practice gymnastics is afforded less relative instructional time than are all other movement domains. In light of this observation, we researched Atlantic Canadian PE teachers’ gymnastics instruction, aiming to answer three primary research questions: (1) Why does gymnastics occupy such a limited (relative) amount of instructional time?; (2) What value do PE teachers see in teaching gymnastics?; and (3) How can PE teachers develop the requisite competence and confidence to offer more gymnastics instruction in their PE programs? Employing a series of on-line focus group interviews with purposefully selected PE teachers, our results indicated that participants did indeed value gymnastics. Participants also believed the lack of gymnastics instruction was due to PE teachers’ strong focus on other areas/topics, as well as their lack of competence and confidence in teaching gymnastics. Herein, we offer a summary discussion of these results as well as suggestions for future practice and inquiry. The results and discussion should be of interest to those who share an interest in PE, curriculum inquiry, and gymnastics instruction, particularly within Western schooling contexts.

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 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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.300
GPT teacher head0.551
Teacher spread0.251 · 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 teacher head, 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

Citations16
Published2020
Admission routes2
Has abstractyes

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