Lessons Learned From COVID-19: Acceptance of E-Learning Technologies in Higher Education

Area of Science:

• Educational Technology
• Human-Computer Interaction
• Psychology of Technology Acceptance

Background:

• Universities rapidly adopted e-learning during the COVID-19 pandemic, altering student experiences.
• Transitioning to optional e-learning post-pandemic created distinct voluntary and involuntary usage contexts.
• Student acceptance of mandatory e-learning varied significantly, impacting educational expectations.

Purpose of the Study:

• To investigate student acceptance of e-learning under both voluntary and involuntary usage conditions.
• To extend the Technology Acceptance Model (TAM) with factors influencing e-learning adoption.
• To identify differences in technology acceptance drivers between voluntary and involuntary e-learning users.

Main Methods:

• Validated an extended Technology Acceptance Model (TAM) with seven factors derived from focus groups.
• Conducted multigroup analysis comparing acceptance between voluntary and involuntary users.
• Collected survey data from 908 undergraduate students, analyzed using PLS-SEM.

Main Results:

• The extended TAM framework demonstrated strong explanatory power (R² = .463-.731) for e-learning acceptance.
• Information quality and system quality significantly influenced perceived usefulness and ease of use.
• Perceived ease of use was more critical for voluntary users' behavioral intention, while perceived usefulness was more critical for involuntary users.

Conclusions:

• The extended TAM effectively predicted e-learning acceptance in both voluntary and involuntary contexts.
• Significant differences in acceptance drivers were found between usage scenarios, validating TAM's applicability in crisis situations.
• Educational technology implementation should consider context-specific adoption factors for optimal student acceptance.