Survey Penggunaan Media Pembelajaran Information and Communication Technology (ICT) Oleh Guru PJOK Sekolah Menengah Pertama di Kabupaten Bima
Bibliographic record
Abstract
Education is the spearhead of the nation's progress learning physical education, sports and health, the balance of affective, cognitive, and psychomotor aspects must be considered, with the aim that learning is achieved optimally. The use of ICT-based learning media by junior high school physical education teachers which aims to assist the learning process and improve the quality of learning. This study aims to determine how much use of ICT-based learning media in Bima district area. Quantitative research methods using survey methods, and collects information or data using questionnaires and interviews. Research that takes a sample from a population and uses a questionnaire as the main data collection tool. The sample of this reasearch is physical education teachers at Junior High Schools in Bima Distric 27 teachers. The use of ICT-based learning media helps physical education teachers in the learning process, the average usage is 22.22% very good category, 37.04% good category, 33.33% poor category and 7.41% very poor category. In this study it can be concluded that the development of learning materials using ICT-based media by physical education teachers in junior high schools in Bima District are included in the good category.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".