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

被引:0
|
作者
Al-Sayid, Fareed [1 ]
Kirkil, Gokhan [2 ]
机构
[1] Kadir Has Univ, Fac Grad Students, Ind Engn Dept, TR-34083 Istanbul, Turkiye
[2] Kadir Has Univ, Fac Engn & Nat Sci, TR-34083 Istanbul, Turkiye
来源
IEEE ACCESS | 2025年 / 13卷
关键词
Electronic learning; Adaptation models; Mathematical models; Pandemics; Education; Computational modeling; Technology acceptance model; Psychology; Load modeling; COVID-19; Technology acceptance model (TAM); UTAUT model; human computer interaction (HCI); students' success; e-learning; self-efficacy; perceived interface design and interactivity; structural equation modeling (SEM); INFORMATION-TECHNOLOGY; UNIFIED THEORY; ADOPTION;
D O I
10.1109/ACCESS.2025.3534740
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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).
引用
收藏
页码:20720 / 20739
页数:20
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