1 Full Paper for PCF5: Health Theme Presentation Repurposing Online Continuing Professional Development Courses in Health into New Educational Contexts
Bibliographic record
Abstract
E-learning is being used increasingly to deliver continuing professional development in a wide variety of health disciplines and situations. High quality content is available online, both through established courses and through open educational resources. However, educational content that is successful in one context will often not be effective in another, especially if there are significant cultural differences between the two situations. This project is examining the redesign of online courses that are effective in one context for use in another. Online courses developed by the Public Health Agency of Canada are being used in this research. The Agency has developed nine online continuing professional development modules covering aspects of public-health practice and over 2,200 public-health professionals have successfully completed at least one module. In this project, a case study approach is being used to examine two examples of adaptation of several of these modules, one at the University of Saskatchewan, Canada, and the other, in the Caribbean under the auspices of the Pan American Health Organization. The first case involves adaptation into a different educational context, but in a similar culture. The second involves similar learners, but in a
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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.812 | 0.461 |
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".