Using Curriculum Design Principles to Improve Health Education for Adolescent Girls
Bibliographic record
Abstract
Learning and teaching are main concepts within health contexts, but curriculum theory is generally overlooked in the design of health education. In this paper, we describe the curriculum development component of a health research study designed to develop and present educational interventions for adolescent girls. Through the use of these interventions, we encouraged the girls to recognize and address potential health compromises in their dating relationships. By blending our disciplinary approaches of nursing and education to address the challenges of this research, we developed a curriculum that would effectively meet the needs of the participants. To do this, we assessed humanistic, social reconstructionist, technological, and academic curriculum approaches to determine that our approach is one of social reconstruction. We then considered teacher-centered, learner-centered, and problem-centered curriculum designs, choosing both learner and problem centered, and analyzed six dimensions of these designs. We describe these approaches, designs, and dimensions of curriculum considering pedagogical issues, criteria for evaluation, and appropriateness to educational health intervention programs.
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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 | 0.015 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".