Perceptions and Use of Teaching Strategies for Fundamental Movement Skills in Primary School Physical Education Programs
Bibliographic record
Abstract
Fundamental motor/movement skills (FMS) describe the basic skills necessary to complete physical tasks, and are a key aspect of primary school physical education (PE) programs. Yet, specific teaching styles for FMS development have been relatively unexplored. Through a mixed-methods design, experiences and perceptions of different PE teachers (preservice, specialist, and generalist) were explored. The Spectrum of Teaching Styles (STS) survey was used to quantify self-reported use of teaching styles that may be used by PE teachers (N = 102). Semi-structured, qualitative interviews with a subset of participants (N = 11) were employed to explore how PE teachers perceive FMS development in PE classes. Combined, the findings highlight a preference for collaborative approaches to teaching and learning in PE, with a specific preference for explicit teaching strategies. Survey results demonstrated a preference for Style B (the practice style), which promotes teacher facilitation of activities and constructive feedback, with opportunities for students to practice skills and receive feedback. Teachers described how confidence with PE content influences the ability to provide lessons that target FMS development; this was reinforced by desires for additional professional development and training. Together, the findings provide a holistic view of teaching styles used in PE for FMS development, and outline a need to explore teaching approaches used by different PE teachers.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".