Voices from the field: teachers' views on health education
Bibliographic record
Abstract
Purpose Health education is often undervalued in school systems, despite addressing broad and complex learning outcomes essential for students' development and well-being. In order to gain an understanding of the current state of health education in Canada, this study examined health education teachers' perspectives about how health education is being delivered in K-12 schools. Design/methodology/approach Data were collected through an online survey completed by 120 health education teachers from across Canada. The survey was organized into four main sections: (1) school contexts, teaching experience and educational backgrounds; (2) the amount of curriculum time allocated to health education; (3) topics covered and instructional approaches used in health education and (4) teachers' experiences delivering health education content. Findings The findings highlight (1) health education teachers' limited training in health education, (2) health education teachers' perceived qualifications and preparedness to teach health education, (3) the limited presence and perceived value of health education in schools, (4) health education as the “loser” in combined health and physical education and (5) limitations in the health education curriculum content delivered within schools. Practical implications This study underscores the need for a coordinated, multi-level strategy to elevate the status of health education within schools. Key implications include the necessity for curriculum reform, strengthened teacher education, sustained professional development and a cultural shift that recognizes the value of health education. To ensure meaningful change, accountability must be clearly defined and distributed across ministries of education, school boards, school administrators and educators. These stakeholders must work collectively to prioritize, properly resource and effectively implement health education as an essential component of students' educational experience and overall well-being. Originality/value Our research highlights the importance of establishing clear accountability among school boards, post-secondary institutions, administrators and teachers to ensure that health education is effectively prioritized, supported and implemented within school systems.
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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 | 0.019 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.021 | 0.020 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".