Recreational activity of students from Preschool Teacher Training College in Sabac
Bibliographic record
Abstract
This article deals with free time and recreation of college students. The aim of this research is to establish how much free time students from Preschool Teacher Training College in Sabac have and how they use it, as well as how much they are engaged in sports and recreational activities. The sample consisted of 60 female students aged 22 (±6 months). A survey with 15 questions was used. Chi-squared test was applied in statistical analysis. Results showed that only 30% of respodents had enough free time and 83,3% of them had additional needs for motion. The majority of them, 70% would choose walking and spending time in countryside. Half of them is physically active 1-2 times a week. 30% regulary go to the concerts, and majority, 71,7% sometimes go to the cinema. 55% regulary pay home visits, and 53,3% sometimes go to the cafes and discos. 56,7% sometimes play cards and 20% play on regular basis. One quarter of them never do any physical activities in their free time. 63,3% go for a walk 3-4 times a week. 66,7% sometimes go on a picnic. The majority feel capable or partially capable of making their own programme of exercising. 58,3% gained necessary knowledge of doing exercises in free time. 35% would test their mobility skills. 41,7% have partial knowledge of the importance of physical exercise on health and human body. A lack of free time, lifestyle, poor organized free time have direct impact on physical engagement of female students. A large scale of education about the importance of physical activities is necessary, as well as about testing and monitoring of health condition.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.005 | 0.001 |
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.
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".