Global Research Activity on E-Learning in Health Sciences Education: a Bibliometric Analysis
Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
Progress in electronic learning (e-learning) and health sciences education is an indicator of the national and international efforts to achieve sustainable development goals regarding good health and quality education. The objective of the current study was to describe research volume and trends on e-learning in the health sciences education. A bibliometric methodology was adopted. The study period was from database inception until December 31, 2020. The data was downloaded from Scopus as a “csv” file. The data was analyzed to reveal prominent contributing countries, institution, authorship patterns, the degree of collaboration, international research collaboration, prominent sources for publications, frequent author keywords, the impact of research in terms of citations, and healthcare groups targeted in research. In total, 4576 records were retrieved. The analysis revealed an increasing growth in number of publications with time. There was a sharp peak in 2020. Recent literature on e-learning in health education included keywords such as flipped classroom, mobile learning, blended learning, and COVID-19. Countries in the European region and the region of the Americas have the highest contribution while countries in the African and the South-East Asian region have the least contribution. There was an increasing trend in the degree of author collaboration with time. However, the extent of international research collaboration was inadequate. The USA had the least percentage of documents with international authors (18%) while Sweden had the highest (70.6%). Documents published from Canada had the highest number of citations per document. The Karolinska Institute, based in Sweden, was the most active institution. The Medical Teacher journal ranked first in the number of publications while documents published in the Academic Medicine journal received the highest number of citations per document. The bulk of the retrieved literature was about medical or nursing education. The retrieved documents had an average of 12.7 citations per document and an H-index of 81. Data presented can be used to develop and enhance e-learning in health sciences education in regions with poor research contribution. Policies regarding open access publications, international research collaboration, and adoption of e-learning methodologies in low- and middle-income countries need to be endorsed.
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.
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 | 0,036 | 0,039 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,029 | 0,523 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 découle