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Record W3097214452

Lifelong physically active lifestyles and the Manitoba physical education curriculum: an inquiry into vision and reality

2019· dissertation· en· W3097214452 on OpenAlexaboutno aff
Gavin Winchar

Bibliographic record

VenueMspace (University of Manitoba) · 2019
Typedissertation
Languageen
FieldHealth Professions
TopicPhysical Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumLifelong learningPedagogyPsychologySociology
DOInot available

Abstract

fetched live from OpenAlex

The general research problem of my study is the suggested discrepancy between what a physical education curriculum articulates and what physical education teachers actually implement and teach in their gymnasiums. Although the curriculum may be designed with a vision or goal in mind, teachers may not carry with them that same belief. In addition, these beliefs may or may not influence the types of physical activities they implement in their teaching. To address this research problem, my study surveyed and interviewed Manitoba physical education (PE) teachers about their views on the purpose of PE, the rationale for their beliefs, and the types of activities they are using to implement the PE curriculum. Forty-five PE teachers from across Manitoba participated in the survey strand of the study, and six teachers were interviewed. The study found that across all PE teachers, across streams, years of experiences and PE assignment portion, the belief was common that a primary purpose to PE is to develop physically active and healthy lifestyles. Furthermore, the PE teachers allocated almost three times as much instruction time to an instructional model that focuses on constant activity than to a model that focuses on the mastery of skills related to a sport discipline. While study participants generally knew and agreed with the vision of the Manitoba PE curriculum, some teachers used means to achieve that vision that were not supported by the research literature on how to achieve that vision.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.036
GPT teacher head0.389
Teacher spread0.353 · 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.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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