Abstract

The COVID-19 epidemic has disrupted the normal teaching and learning in universities, which poses significant challenges to college education. The traditional face-to-face learning mode has been switched to online (distance) learning, causing various influences on students’ academic performance. As higher education plays a central role in technology innovation and society development, it is of great importance to investigate and improve online education in the context of COVID-19. This study distributed online questionnaires to college students from 30 provinces or municipalities in China to evaluates the SWOT (Strengths, Weaknesses, Opportunities, and Threats) factors of shifting from traditional learning to online learning during COVID-19 Pandemic. The SWOT analysis has been employed to construct 16 kind of internal and external evaluation factors and 4 kind of improvement strategies for assess online education. The basic data of subjective weight method — AHP comes from the questionnaire survey, and the weight value of SWOT factors is determined through the questionnaire survey results. The fuzzy MARCOS approach is used to select the most suitable strategies for its effective implementation. Several coping strategies are suggested to improve the online education in post-pandemic era, which is essential for higher education and promoting a civilized and sustainable society. “By reforming and innovating the teacher led teaching mode, stimulate students’ interest in learning, get rid of the boring learning state, create a good learning atmosphere and improve the teaching quality” is the most effective strategy to enhance the online learning experience and increase students’ satisfaction. This methodology is applicable with a case study concerning the students’ online education in pandemic and the validity of this approach is presented through comparative analysis and sensitivity analysis. Through example verification, it is found that SWOT method is suitable for online education evaluation research no matter how the research object changes.

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