Health and Physical Education Preservice Teachers’ Health Literacy Levels and Teaching Practices: Protocol for a Design-Based Research Approach
Bibliographic record
Abstract
BACKGROUND: Research examining the design and impact of health literacy (HL) programs and interventions on preservice teachers' HL and health and physical education (HPE) teaching practices to enhance students' HL is nonexistent. However, research indicates that many teachers and preservice teachers report low levels of HL, and recent research has highlighted preservice teachers' challenges in teaching HPE to enhance their students' HL capabilities. This is concerning, as HL is a focus in curricula and schooling both in Australia and internationally. Therefore, teachers are engaging in professional development aimed at enhancing their HL teaching practices, which raises questions about how further development of initial teacher education can enhance preservice teachers' HL capabilities and teaching practices in schools. OBJECTIVE: This protocol aims to provide details of a study to be conducted in the University of Sydney, involving final-year HPE preservice teachers, aimed at developing their HL capabilities and teaching practices. METHODS: The proposed methodology underpinning the research program follows a 7-stage design-based research approach, with the 7 stages outlined in 4 sequential studies. These 4 studies include a systematic review, a qualitative focus group study, a pilot study, and a controlled trial study. This paper details the plan for conducting the 4 studies in a comprehensive and transparent manner, thus contributing to the methodological evidence base in this field. RESULTS: The pilot study was conducted between July 2024 and December 2024, and data analysis was conducted between January 2025 and June 2025. The controlled trial will be conducted between July 2025 and December 2025. Final data analysis will occur between January 2026 and June 2026. CONCLUSIONS: This project will assist in determining what key stakeholders see as important to include in an initial teacher education program designed to enhance HPE preservice teachers' HL capabilities and teaching practices. The design principles generated from this project will contribute to the inclusion and development of initial teacher education programs and practices and strengthen preservice teachers' HL and their teaching of HPE, thereby enhancing HL teaching practices. This is significant considering that HL is included in the curriculum internationally, and the development of HL for school-age students has been identified as a World Health Organization goal. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/69900.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.124 | 0.120 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.066 | 0.018 |
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".