Measures of Effectiveness for E learning of University Students During the Covid-19 Pandemic Using the Statistical Model

Jameela Ali Alkrimi¹ , Raja Salih Mohammed² , Ameer Hamdi Hakeem Al-Ameedee³ , Safaa Hakeem Alkahfaji⁴ , Ban Alwash⁵ , Rawan Al-Rubaye⁶

Section:Research Paper, Product Type: Journal
Vol.11 , Issue.3 , pp.1-7, Jun-2023

Online published on Jun 30, 2023

Copyright © Jameela Ali Alkrimi, Raja Salih Mohammed, Ameer Hamdi Hakeem Al-Ameedee, Safaa Hakeem Alkahfaji, Ban Alwash, Rawan Al-Rubaye . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
E-learning considers the best solution for continuing education during the COVID-19 pandemic, especially in tertiary education. The present study aims to analyze and the evaluation efficacy of learning in an e-learning system measures to improve the technical skills among dental and medical undergraduate students during Covid-19 outbreak. One thousand five-hundred students were assigned for this study and the answers for the given questionnaire were collected. The rate of response was 96.86% among respondents who use module and classroom tools, techniques, or platforms. The statistical model was applied to the analysis of the questionnaire. Principle component analysis techniques were used to determine the variables` efficacy on the E-learning model. The reliability of the associated components was measured using ( Cronbach’s ? ) test gives 0.801. The findings of this study that medical education skills have been slightly affected by the use of e-learning during the COVID-19 pandemic. Therefore, the idea E-learning entails Familiarity with the technology; Usability, Learned skills, and Competency; Quick Responsiveness; Learning Quality of the learner; Time and Cost; Faster Learning; Information quality; and Knowledge sharing.

Key-Words / Index Term :
E-learning, Effectiveness measure, Covid-19, pandemic, principal component analysis

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