Publication date: Sep 04, 2025

ObjectiveThis study investigates students’ acceptance of e-learning during the COVID-19 pandemic, examining differences between voluntary and involuntary use contexts. BackgroundDuring the COVID-19 pandemic, universities shifted to online instruction for an extended period. E-learning became mandatory to use and was met with varying degrees of acceptance by students, whose educational expectations and experiences were altered. By 2022, institutions began transitioning to optional e-learning use, creating a natural setting to examine technology acceptance under both voluntary and involuntary conditions. MethodThis study employed a two-phase approach, first validating an extended Technology Acceptance Model (TAM) incorporating seven factors derived from focus groups. Second, conducting multigroup analysis of acceptance between voluntary and involuntary users. Data was collected through surveys from 908 undergraduate students. ResultsPLS-SEM analysis revealed strong explanatory power (R = .463-. 731) for the extended TAM framework. Compatibility demonstrated the strongest effect on perceived usefulness, while information quality and system quality influenced both perceived usefulness and ease of use. Multigroup analysis revealed significant contextual differences in students’ acceptance. Perceived ease of use more strongly influenced behavioral intention for voluntary users, while perceived usefulness had stronger effects for involuntary users. ConclusionThe extended TAM framework significantly predicted e-learning acceptance in both voluntary and involuntary contexts. Significant differences between usage scenarios were identified, extending TAM’s applicability to crisis situations. ApplicationThis study provides insights for postpandemic educational technology implementation, emphasizing system quality and alignment with learning preferences. Practitioners should consider differences in adoption contexts when working to facilitate acceptance among both voluntary and mandatory users.

Semantics

Original Article