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Preparedness of medical students towards e-learning conducted during COVID-19 lockdown: A cross-sectional descriptive study
BACKGROUND: COVID-19 lockdown has mandated the medical colleges to start academics using electronic mode. Synchronous e-learning was started by our institute to replicate traditional classes in line with the routine academic schedule. the objective of this study attempted to assess the e-learning re...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459856/ https://www.ncbi.nlm.nih.gov/pubmed/34667802 http://dx.doi.org/10.4103/jehp.jehp_1125_20 |
Sumario: | BACKGROUND: COVID-19 lockdown has mandated the medical colleges to start academics using electronic mode. Synchronous e-learning was started by our institute to replicate traditional classes in line with the routine academic schedule. the objective of this study attempted to assess the e-learning readiness of the students of our institute. MATERIALS AND METHODS: A cross-sectional descriptive study was planned using the model proposed by Oketch et al. with local modifications. The questionnaire was designed in Google Forms and mailed to respond using Likert scale. The nonparametric data collected from the total 84 respondents were analyzed for validity and reliability of the questionnaire, mean values to know the readiness (mean = 3.4), and one-step multiple regression to know the predictors. RESULTS: The mean eLR (e-learning readiness) as evaluated from attitudinal readiness (Mean(AR) = 3.6), culture readiness (Mean(CR) = 2.3), material and technological readiness (Mean(MTR) = 3.7), and mental health readiness (Mean(MHR) = 2.4) is 3.03 (60.6% with n = 84). Multiple regression analysis revealed that all the variables except MHR can significantly predict e-learning readiness linearly (P < 0.05). CONCLUSION: The institute is ready for e-learning in terms of AR and MTR (mean values >3.4). CR and MHR still need a lot of improvisation to make it acceptable for e-learning. The model could explain 54.9% readiness level with CR as the most important predictor. More than 73% (n = 84) of the respondents have acknowledged the present form of online classes to be the best available option in COVID-19 lockdown and most of them are adapted to e-classes in the institute. |
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