TAM-Based Model for Evaluating Learner Satisfaction of E-Learning Services Case Study: E-Learning System of University of Tehran - Sina Sayardoost Tabrizi; Azin Sabzian; Ali Moeini; Keikhosrow Yakideh (International Journal of Web Research)
During the COVID-19 pandemic, universities worldwide favored distance learning systems. Although e-learning provides numerous benefits, it also poses challenges for learners, so learners’ satisfaction is a significant concern to be assessed. The present study aimed to assess learners’ satisfaction with the University of Tehran's LMS during the pandemic. It applied a model based on the Technology Acceptance Model (TAM) and supplemented it with factor analysis. Research validity was assessed by using confirmatory factor analysis, while Cronbach's alpha was employed to measure the reliability of the research instrument. The study used the Partial Least Squares (PLS) analytical method to construct structural equations. In order to do so, data was collected from a comprehensive questionnaire distributed to 334 students at the University of Tehran, in which 143 participated. The findings reaffirmed the TAM's effectiveness in understanding the factors influencing learners’ satisfaction with the LMS. Consequently, these insights empower the technical team to enhance system functionality and infrastructure, aiming at improving service quality in the first semester of the academic year 2021. The Results showed that: 1) The TAM-based proposed scale has successfully explained factors predicting learners’ satisfaction. 2) Technical knowledge contributes to the perceived ease of use and influences perceived usefulness with a coefficient of 0.89, and 3) The significant relationships between technical knowledge and attitude were met. The paper's contribution is finding that learners’ technical knowledge significantly impacts their satisfaction, which helps the ICT team develop a user-friendly environment and increases the flexibility of templates. The study focused on creating training videos to improve learners’ technical knowledge. These results can change and improve the software development strategy for the next semester.