The potential of an online educational platform to contribute to achieving sustainable development goals: a mixed-methods evaluation of the Peoples-uni online platform
Bibliographic record
Abstract
BACKGROUND: This paper reports on an online platform, People's Open Access Education Initiative (Peoples-uni), as a means of enhancing access to master's level public health education for health professionals. Peoples-uni seeks to improve population health in low- and middle-income countries by building public health capacity through e-learning at very low cost. We report here an evaluation of the Peoples-uni programme, conducted within the context of Sustainable Development Goal 4, which seeks to "ensure inclusive and quality education for all and promote lifelong learning" by 2030. The evaluation seeks to address the following three questions: (1) Did Peoples-uni meet its intended goals? (2) What were the different types of impacts that students experienced? (3) What suggestions for future changes in Peoples-uni did students recommend? METHODS: A mixed methods evaluation consisted of two parts, namely an online survey and a telephone interview. A total of 119 master's level graduates were invited to participate; responses were obtained from 71 of those invited, giving a response rate of 60%. Respondents were spread across 31 countries. Interviews were conducted with 18 respondents. RESULTS: There was strong evidence that Peoples-uni had achieved its stated goals. Potential impacts on students included knowledge to enhance practice and appreciation of context, enhanced research capacity through knowledge of public health, critical thinking and evidence-based programming, and empowerment of students about the potential of education as a means of improving their lives. Accreditation through future partnerships with local universities was recommended by students. CONCLUSIONS: Peoples-uni has been able to deliver a credible public health master's level educational programme, with positive impacts on the students who graduated. Challenges are to find a way to accredit the programme to ensure its sustainability and to see how to take full advantage of the current, and future, graduates to turn this from an education programme into a capacity-building programme with real impact.
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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 | 0.072 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".