Modelling the associations between academic engagement, study process and grit on academic achievement of physical education and sport university students
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: The present study examined the impact of academic engagement, study processes, and grit on the academic achievement of physical education and sport university students. METHODS: An internet-based survey recruited 459 university students aged 19-25 years (M = 21 ± 1.3) in physical education and sports (PES) to fill out questionnaires on Physical Education-Study Process Questionnaire (PE-SPQ), Physical Education-Grit (PE-Grit), academic engagement (A-USEI), and Grade Point Average (GPA). A path analysis was carried out to understand variable relationships. RESULTS: Data from each variable exhibited symmetrical and normal distribution, as indicated by the skewness and kurtosis values. The model's fit indices showed sufficient Comparative Fit Index (CFI = 0.92), Tucker-Lewis Index (TLI = 0.90), Goodness of Fit Index (GFI = 0.99) and Normed Fit Index (NFI = 0.90) and showed acceptable levels. The results indicated a statistically significant positive impact of engagement (β = 0.299, p < 0.001) and study processes (β = 0.397, p < 0.001) on academic achievement. However, the effect of grit on achievement was non-significant. CONCLUSIONS: Academic engagement as well as study processes are two important factors predicting academic achievement while grit seems to be not a major predictor. Hence, physical education and sport faculty and university administrators should prioritize student engagement as a determinant of academic outcomes by reforming or redesigning physical education and sport curriculum modules that can facilitate engagement.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it