Evaluation of a virtual, simulated international public health peer-to-peer exchange learning experience
Bibliographic record
Abstract
Introduction: Public Health's (PH) global rise is accompanied by an increasing focus on training the new generation of PH graduates in interdisciplinary skills for multisectoral and cross-cultural engagement to develop an understanding of commonalities in health system issues and challenges in multi-cultural settings. Online teaching modalities provide an opportunity to enhance global health skill development through virtual engagement and peer exchange. However, current teaching pedagogy is limited in providing innovative modes of learning global health issues outside of traditional classroom settings with limited modalities of evidence-informed implementation models. Methods: This study designed, implemented, and evaluated a novel global health online synchronous module as proof of concept that incorporated elements of virtual Practice-based learning (PBL) using a case study approach offered to currently enrolled public health students at the University of Canberra (UC) and a partnering public health university from India, the Indian Institute of Public Health Gandhinagar (IIPH-G). Using constructive learning theory and the Social Determinants of Health framework, four online sessions were designed and implemented in August-September 2022. Formal process and outcome evaluation using a quantitative adapted survey of the validated International Student Experience survey (IES) at session end and findings provided. Results: Over 100 participating public health students from Australia and India provided narrative feedback and quantitative responses from the adapted IES instrument across four key dimensions, namely "motivation," "personal development," intellectual development, and "international perspectives" reporting an overall high mean impact of 4.29 (out of 5) across all four themes seen together. In essence, the sessions supported students to explore global health issues from a different cultural perspective while developing intercultural communication skills and enhancing their global exposure in real-time. Discussions: This innovation, implemented as a proof of concept, provided evidence, and demonstrated the implementation feasibility of a flexible virtual integrated practice-based module that can supplement classroom teaching. It provides participating students with the opportunity to develop intercultural understanding and communication competence as well as support global mindedness by engaging with international peers around focused global health case studies.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".