Medical Morphology Training Using the Xuexi Tong Platform During the COVID-19 Pandemic: Development and Validation of a Web-Based Teaching Approach
Notice bibliographique
Résumé
BACKGROUND: Histology and Embryology and Pathology are two important basic medical morphology courses for studying human histological structures under healthy and pathological conditions, respectively. There is a natural succession between the two courses. At the beginning of 2020, the COVID-19 pandemic suddenly swept the world. During this unusual period, to ensure that medical students would understand and master basic medical knowledge and to lay a solid foundation for future medical bridge courses and professional courses, a web-based medical morphology teaching team, mainly including teachers of courses in Histology and Embryology and Pathology, was established. OBJECTIVE: This study aimed to explore a new teaching mode of Histology and Embryology and Pathology courses during the COVID-19 pandemic and to illustrate its feasibility and acceptability. METHODS: From March to July 2020, our team selected clinical medicine undergraduate students who started their studies in 2018 and 2019 as recipients of web-based teaching. Meanwhile, nursing undergraduate students who started their studies in 2019 and 2020 were selected for traditional offline teaching as the control group. For the web-based teaching, our team used the Xuexi Tong platform as the major platform to realize a new "seven-in-one" teaching method (ie, videos, materials, chapter tests, interactions, homework, live broadcasts, and case analysis/discussion). This new teaching mode involved diverse web-based teaching methods and contents, including flipped classroom, screen-to-screen experimental teaching, a drawing competition, and a writing activity on the theme of "What I Know About COVID-19." When the teaching was about to end, a questionnaire was administered to obtain feedback regarding the teaching performance. In the meantime, the final written pathology examination results of the web-based teaching and traditional offline teaching groups were compared to examine the mastery of knowledge of the students. RESULTS: Using the Xuexi Tong platform as the major platform to conduct "seven-in-one" teaching is feasible and acceptable. With regard to the teaching performance of this new web-based teaching mode, students demonstrated a high degree of satisfaction, and the questionnaire showed that 71.3% or more of the students in different groups reported a greater degree of satisfaction or being very satisfied. In fact, more students achieved high scores (90-100) in the web-based learning group than in the offline learning control group (P=.02). Especially, the number of students with objective scores >60 in the web-based learning group was greater than that in the offline learning control group (P=.045). CONCLUSIONS: This study showed that the web-based teaching mode was not inferior to the traditional offline teaching mode for medical morphology courses, proving the feasibility and acceptability of web-based teaching during the COVID-19 pandemic. Our findings lay a solid theoretical foundation for follow-up studies of medical students.
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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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) | 0,000 | 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; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».