Examining the Attitudes of Classroom Teachers Towards Sports: Example of Kırşehir Province
Bibliographic record
Abstract
The purpose of this research is to determine the attitudes of classroom teachers towards sports. Within this scope, in the first part of this study, it is aimed to describe the attitudes of classroom teachers towards sports. In the second part of the study, it was investigated whether gender, participation in sports activities and years of service differ significantly on the attitudes of classroom teachers towards sports. The screening method was used in this research. The study was carried out with 308 classroom teachers working in Kırşehir. They participated in the study on a volunteer basis. “Personal Information Form” and “The Sports-Oriented Attitude Scale” were used in the data collection process. When testing the research data, a 0.05 significance level was taken. In the analysis of the data, the items related to the sub-problem were grouped and Mann Whitney U and Kruskall Wallis techniques were used together with descriptive statistics such as frequency (f), percent (%), weighted mean (X̅) and standard deviation (SD). The attitudes of classroom teachers towards sports generally high (X̅ = 4.42). While their attitudes towards sports do not differ significantly according to their gender (U = 10381,500; p > .05); it differs significantly according to their participation in sports activities (U = 8686,000; p < .05) and years of service (X2 = 8,364; p < .05). Research results show that attitudes of classroom teachers towards sports are generally at a high level. However, it was concluded that the attitudes of classroom teachers towards sports differed significantly according to their participation in sports activities and years of service, but did not differ by gender.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".