Using the fsQCA approach to investigate factors affecting university students' satisfaction with online learning during the COVID-19 pandemic: A case from China.

Abstract

During the COVID-19 pandemic, higher education institutions have been forced to switch their teaching mode to online education. There has been limited in-depth exploration of the factors affecting students' satisfaction with online learning, and no consensus has been reached among these studies' results. Students' satisfaction is essential for realizing effective online education practices and meaningful to promoting the sustainable development of online courses, and it cannot be fully explained by one single factor. Research exploring the configuration of factors affecting students' satisfaction with online learning has been rare. This study adopted a novel data analysis method, the fuzzy-set Qualitative Comparative Analysis (fsQCA) method, to explore collocations of different factors affecting higher education students' satisfaction with online learning during the COVID-19 pandemic. This research surveyed 357 university students in Mainland China during the second semester of the 2021-2022 academic year using a structured questionnaire. The study identified that when students were satisfied with assignments and had a higher level of internet self-efficacy, or they were satisfied with their instructors and assignments, they were satisfied with online classes. Additionally, internet self-efficacy is indispensable to explaining students' higher level of satisfaction with online learning. This study contributes to our understanding of university students' satisfaction with online learning during the COVID-19 pandemic by using a novel method to explore the configuration of influential factors, and it provides implications for administrators and policymakers in the education field who seek to improve students' satisfaction with online learning.