This study surveys the e-learning acceptance of university students in Thailand. One thousand nine hundred and eighty-one (1,981) participants completed the E-Learning Acceptance Measure (Teo, 2010) which measures three constructs that predict e-learning acceptance (tutor quality, perceived usefulness, and facilitating conditions). Data analysis was performed using structural equation modeling (SEM). The results of this study showed that the three constructs were significant predictors of e-learning acceptance. Further analysis with MIMIC (multiple indicators, multiple causes) modeling revealed that university students' e-learning acceptance was significantly different by age and perceived technology competence. Younger students and those who perceived themselves to be technologically more competent reported a higher level of e-learning acceptance than older students and those who perceived themselves as less competent in using technology.