Planning and assessment practices among Spanish physical education teachers according to experience and teaching level
Bibliographic record
Abstract
The intent of this study was to determine the prevalence of formal lesson plan development as well as examine assessment practices (i.e. frequency of assessment; types of assessment tools most commonly utilized; aspects of physical education most commonly assessed) among physical education teachers in Spain. Furthermore, this study investigated relationships between physical educators’ (a) years of teaching experience and (b) teaching level (primary school vs. secondary school), with both their frequency of formal lesson planning and their assessment practices. The standardized and validated PROAFIDE questionnaire was completed by 499 physical educators presently teaching at either the primary or secondary school level. Results indicated that the vast majority of study participants utilize detailed written lesson plans and perform regular assessments. The percentage of use was found to rise among teachers with increased teaching experience, and among those who were teaching at secondary school. The most commonly used assessment instruments were found to be tests, specifically personally made tests and pre-existing batteries of tests (e.g. Eurofit Fitness Testing Battery). The least used assessment instrument was found to be homework. For all the various assessment tools, it was found that attitudinal aspects were assessed more commonly than physical, cognitive, technical, and tactical aspects. Future research needs to investigate the implications of regular planning and assessment, or lack thereof, on actual practice.
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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 | 0.002 | 0.003 |
| 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".