The Analysis of Test Anxiety Among Students at School of Physical Education and Sports in Terms of Demographic Variables
Bibliographic record
Abstract
The present study aims to measure levels of test anxiety among students studying at different departments at School of Physical Education and Sports. The population of the study consists of 780 students studying at different departments at School of Physical Education and Sports at Yozgat Bozok University during 2018–2019 academic year. The sample of the study consists of 382 students who study at different departments at School of Physical Education and Sports at Yozgat Bozok University during 2018–2019 academic year and voluntarily participated in the online survey sent them by e-mail. Survey was used as a method in the present study, and demographic variables were obtained using “personal information form”. “Westside test anxiety scale”, which was adapted to Turkish context and tested for reliability and validity by Totan and Yavuz (2009), was used to determine students’ level of test anxiety. The obtained data were statistically analyzed using SPSS 18 software program. Frequency analysis, percentage analysis, arithmetic means, t test and ANOVA analysis were used for data analysis. The analyses demonsrate that no statistically significant differences were observed among students’ levels of test anxiety in terms of four different variables (p>0.05). However, as for mean scores, it was found out that female students’ level of test anxiety was higher compared to male students. Students studying coaching education had a higher of test anxiety compared to those studying physical education and sports teaching and sports management. In addition, students who did not take notes during lessons had a higher level of test anxiety compared to those who took notes during lessons. Finally, students who reviewed lessons shortly before the test had a higher level of test anxiety compared to those who reviewed their lessons on a daily basis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".