Factors influencing online learning fatigue among blended learners in higher education

Abstract

This cross-sectional study aims to investigate the factors influencing the levels of online learning fatigue among blended learners in higher education amid the post-pandemic era. In this context, a total of 347 college students voluntarily completed an online questionnaire, including the Online Learning Fatigue (OLF) Scale, to determine the fatigue levels and to examine the three-level construct of the OLF. The gender preference in the seven OLF subscales supported the literature that women are more prone to be fatigued. Additionally, the findings supported the structural relationships between the seven factors of the three-level construct of the OLF and produced results that support the theoretical framework for the model to scrutinize online learning fatigue levels in higher education. The regression analysis results supported that information equivocality was a significant predictor of information overload, and that the system complexity and system pace of change were significant predictors of system feature overload. Finally, it supported the three-level construct of the OLF, supporting the notion that system feature overload, communication overload, and information overload are significant predictors of LMSs fatigue. Considering the limitations, the factors that should be addressed to form well-structured online learning settings are scrutinized, and theoretical and practical implications are discussed.