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Critical e-learning quality factors affecting student satisfaction in a Korean medical school.
Si, Jihyun.
Afiliação
  • Si J; Department of Medical Education, Dong-A University College of Medicine, Busan, Korea.
Korean J Med Educ ; 34(2): 107-119, 2022 Jun.
Article em En | MEDLINE | ID: mdl-35676878
PURPOSE: This research investigated the critical factors that affect the e-learning quality. The student satisfaction model with the five factors such as content, system, learner, instructor and interaction was proposed and empirically examined. It also investigated the relationship between the interaction and other constructs. METHODS: This study used a cross sectional survey design, and convenience sampling. To examine the critical factors and their relationship, a survey of 28 items was developed based on previous studies and sent out through a learning management system to all the students (n=250) enrolled in the pre-med 1 to the medicine 3 in one medical school in Korea. The medical school delivered all the courses online due to the coronavirus disease 2019 pandemic. The collected data (n=209, 83.6%) were analyzed through structural equation modeling by using IBM AMOS ver. 26.0 and IBM SPSS ver. 26.0 (IBM Corp., Armonk, USA). RESULTS: The determinants of e-learning student satisfaction were system, learner, instructor, and interaction qualities, which together explained 72.6% of the variance of student satisfaction and the determinants of e-learning interaction quality were content and system qualities, which together explained 62.9% of the variance of interaction quality. CONCLUSION: The results of this study presented practical guidelines to improve e-learning quality in terms of student satisfaction in medical education contexts. The results indicated that more efforts should be directed toward improving interaction features such as interactive teaching styles, collaborative activities, providing instructors and learners with proper training for e-learning prior to e-learning and a quality of contents, and upgrading e-learning system for better performance and service.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Instrução por Computador / COVID-19 Tipo de estudo: Guideline / Observational_studies / Prevalence_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Instrução por Computador / COVID-19 Tipo de estudo: Guideline / Observational_studies / Prevalence_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article