The potential of an online educational platform to contribute to achieving sustainable development goals: a mixed-methods evaluation of the Peoples-uni online platform
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,033 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».