Profiling University Students’ Technology Acceptance Through UTAUT

Abstract

Several studies have been conducted on e-learning acceptance among university students. Most of these studies examined various factors and individual characteristics as predictors of actual use and behavioral intention for e-learning systems. However, latent profile analysis was used in the present study, adopting a person-centered approach. Accordingly, the study’s primary purpose was to define LMS acceptance profiles by grouping university students based on gender according to four main UTAUT predictor variables. The secondary purpose was to examine the extent to which LMS acceptance profiles had a relationship with the students' online self-regulation and engagement in online learning environments. The participants in the study were 397 students from a state university in Turkey who continued their distance education. Student Engagements Scale, Online Self-regulation Questionnaire, and Learning Management System Acceptance Scale were used to collect data. The obtained data were analyzed using latent profile analysis. The results obtained in the study revealed that there were three different student profiles: "very low LMS acceptance", "low LMS acceptance", and "high LMS acceptance". According to another result, it was seen that low online self-regulation and engagement had a relationship with a student profile with very low LMS acceptance and that high online self-regulation and engagement had a relationship with a student profile with high LMS acceptance. Based on the findings, various implications were made about increasing students' LMS acceptance.