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Record W2587682872 · doi:10.5539/ibr.v10n3p69

Development of Physical Education Model for 7-12th Graders

2017· article· en· W2587682872 on OpenAlexvenueno aff
Sheng-Kuang Yang, Yen-Chen Huang, Yi-Hsien Lin

Bibliographic record

VenueInternational Business Research · 2017
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyConstructivePhysical educationGoodness of fitDiscriminant validityPath analysis (statistics)Order (exchange)Applied psychologySocial psychologyMathematics educationComputer scienceMathematicsStatisticsDevelopmental psychologyInternal consistencyPsychometrics

Abstract

fetched live from OpenAlex

During physical, social support also affects the change in students’ attitude towards sports. Therefore, in order to propose suggestions for improving physical education, this study enrolled students participating in sports team in Taiwan as the research subjects and performed investigations them to develop the participation model for students in sports teams and provide constructive strategies according to it, in order to effectively improve students’ sports participation. According to the research conclusions, the goodness of fit of the overall measurement model is good, the convergent validity and discriminant validity are acceptable, and most of the relevant indices all meet the criteria. This study used path analysis to analyze the path coefficients among various variables, and discovered that all of the paths were significant. The potential variable that has the most significant influence on participation motivation is social support, namely, the influence of social support on participation motivation is more significant.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.221
GPT teacher head0.500
Teacher spread0.279 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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
Published2017
Admission routes1
Has abstractyes

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