Integrating Technology Acceptance Model With Utaut To Increase the Explanatory Power of the Effect of Hci on Students' Intention To Use E-Learning System and Perceive Success

Abstract

This study aimed to investigate the potential human-computer interaction factors (HCI) affecting students' behavioural intentions (BI) to use the e-learning system and perceive success. This paper proposes a comprehensive model, integrating the technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT). The data were collected via an online survey conducted on 232 students utilizing the Khas Learn system of Kadir has University in Turkey. The proposed hypotheses were tested by multi-linear regression. The results illustrated that the main predictors of students' success (SS) are behaviour intention, ease of use, usefulness, visual design, and learner interface interactivity which explained 53.6% of perceived success in using the system. While, the main predictors of BI are facilitating condition, effort expectancy, ease of use, and usefulness which explained 71% of the variance in continuance intentions to use e-learning. Therefore, the empirical findings provide strong backing to the technological-social-psychological dimensions extended by HCI main factors, which showed a high explanatory power in accepting e-learning technology and leads to enhance the SS, where five of the model's goodness-of-fit values meet five criteria of structural equation modeling (SEM).