Attitudes Towards a Moodle-based E-Learning Platform: A User Segmentation Perspective

The paper objective is to apply Technology Acceptance Model (TAM)-based usage and attitude variables for the predictive user segmentation of Moodle-based e-learning system in a university. The study explores the path models with latent variables estimated by partial least squares method (SmartPLS and plspm library of the R package were used for the parameter estimation) and uses the mixture models (FIMIX and REBUS) for model-based segmentation. Modified technology acceptance model (TAM) was estimated on the sample of 204 students of the Cracow University of Economics. As a result of segmentation analysis, 3 segments of "easiness seekers", "emotionals" and "loyals" were identified and profiled.