e-Learning in Medical Education in Sri Lanka: Survey of Medical Undergraduates and New Graduates
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
BACKGROUND: Medical education has undergone drastic changes with the advent of novel technologies that enable e-learning. Medical students are increasingly using e-learning methods, and universities have incorporated them into their curricula. OBJECTIVE: This study aimed at delineating the pattern of use of e-learning methods among medical undergraduates and new graduates of the Faculty of Medicine, University of Colombo, and identifying the challenges faced by these students in using e-learning methods. METHODS: A cross-sectional descriptive study was conducted in the Faculty of Medicine, University of Colombo, in April 2020, with the participation of current undergraduates and pre-intern medical graduates, using a self-administered questionnaire that collected data on sociodemographic details, pattern of use of learning methods, and challenges faced using e-learning methods. RESULTS: There were 778 respondents, with a response rate of 65.1% (778/1195). All the study participants used e-learning resources with varying frequencies, and all of them had at least 1 smart device with access to the internet. Electronic versions of standard textbooks (e-books), nonmedical websites, online lectures, medical websites, and medical phone apps were used by the majority. When comparing the extent of use of different learning methods, it appeared that students preferentially used traditional learning methods. The preference was influenced by the year of study and family income. The 3 most commonly used modalities for learning new study material and revising previously learned content were notes on paper material, textbooks (paper version), and e-books. The majority (98.7% [n=768]) of participants have encountered problems using e-learning resources. The most commonly faced problems were unavailability of free-of-charge access to some e-learning methods, expenses related to internet connection, poor connectivity of mobile internet, distractions while using online resources, and lack of storage space on electronic devices. CONCLUSIONS: There is a high uptake of e-learning methods among Sri Lankan medical students. However, when comparing the extent of use of different learning methods, it appeared that students preferentially used traditional learning methods. A majority of the students have encountered problems when using e-learning methods, and most of these problems were related to poor economic status. Universities should take these factors into consideration when developing curricula in medical education.
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 | 0,007 | 0,029 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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