Modelling user acceptance of personalised learning apps in high schools using the SEM approach

Abstrak

This research addresses the urgent need to understand user acceptance of personalised mobile learning applications in higher education, especially as digital learning becomes increasingly essential in post-pandemic education. The study employs a quantitative research design, utilising the Technology Acceptance Model 3 (TAM3) as the theoretical framework and Structural Equation Modelling (SEM) for analysis. The population comprises undergraduate students from various departments at STIKOM Uyelindo Kupang, selected using stratified random sampling to ensure representation across faculties. Data was collected through a validated questionnaire based on TAM3 constructs, and the instrument's validity and reliability were confirmed using Cronbach's Alpha, Composite Reliability (CR), and Average Variance Extracted (AVE). The results show that Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) significantly influence Behavioural Intention (BI), while Social Influence (SI) and Facilitating Conditions (FC) also play important roles. Perceived Enjoyment (PE) enhances engagement, and Computer Anxiety negatively affects ease of use. The study concludes that TAM3 effectively models user acceptance in this context. Recommendations include improving app usability, providing institutional support, and designing engaging learning experiences to enhance the adoption and continued use of mobile learning technologies.