PRELIMINARY ASSESSMENT OF MASTER OF PUBLIC HEALTH STUDENTS’ PERCEPTION OF CORE COMPETENCIES AND USE OF INPLACE SOFTWARE IN THE FACILITATION OF COMPETENCE-BASED LEARNING
Bibliographic record
Abstract
Objective: The future of public health in Canada depends on the competence of today’s public health students. The Public Health Agency of Canada (PHAC) core competence categories are designed to guide public health practice and the training of public health students. The objectives of this study were to understand public health graduate students’ perception of the PHAC core competencies and report the usability of a practicum placement software in the facilitation of competence-based learning. Methods: Twelve students in the first year of the graduate program in public health participated in two focus group sessions. Participants were asked to select their top and least desired PHAC competencies and then discuss the reasons for their selection. Factors that may have influenced the category selection and their opinion on improving the competence categories were discussed. The system usability scale (SUS) was administered to the student participants and two staff members to help understand the usability of the practicum placement software in the facilitation of competence-based learning. Results: Partnership, collaboration, and advocacy emerged as the top-desired, with public health sciences being the second top-desired. The assessment and analysis category was the least desired, followed by the Leadership competence category. Prior educational background, future career goals with respect to job prospects were among the key factors that influenced the students’ competence selection. Conflict resolution, outreach, and community engagement were some of the suggestions of categories that could be included in the core competence categories. The system usability score for InPlace platform was 61.8 (95% 56.7- 66.9). Conclusions: Overall, students believe that the PHAC core competencies are comprehensive. They suggested seeing certain terminologies become a prominent part of the competence categories. The use of InPlace platform in the facilitation of competence-based learning may require more time for adequate user experience.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".