Comparison of the Effects of Sports Education and Direct Teaching Models on the Attitude and Cognitive Domain Level of Undergraduate Students
Bibliographic record
Abstract
The purpose of this study was to compare the effects of the sports education model and the direct teaching model used in badminton courses on the attitudes of undergraduate students towards the course and its permanence on cognitive domain skills. The study group consisted of a total of 45 undergraduate students, 24 of whom were experimental groups and 21 were control groups. In the study, for collection of data, the “Intrinsic Motivation Inventory” which developed by Ryan (2000), adapted to Turkish by Çalışkur after being tested for validity and reliability (Çalışkur & Demirhan, 2013) and the “Badminton Cognitive Domain Information Form” which was prepared by the course instructor were used. Descriptive statistical analysis was used for data analysis of attitudes of groups after application, but, bacause of the lack of a normal distribution, the “Mann Whitney U” test was used for the significance of the difference between the cognitive domain and the permanence of learning, As a result; significant differences were determined between the students’ interest/enjoyment aspect and the permanence of cognitive learning, whereas significant differences were not detected in the aspects of perceived competence, value/benefit, effort/importance, job perception/perceived choice and pressure/tension.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".