ISCAP Proceedings: Abstract Presentation
Do Technology-Use Intentions Translate into Learning? Testing an Extended UTAUT Model among Information Systems Students
Ping Wang
James Madison University
Thomas Dillon
James Madison University
Abstract
Digital technologies are increasingly integrated into information systems education, but students’ acceptance of technology does not necessarily ensure improved learning. The Unified Theory of Acceptance and Use of Technology (UTAUT) primarily explains technology adoption through performance expectancy, effort expectancy, social influence, facilitating conditions, and behavioral intention. This study extends UTAUT beyond technology acceptance by examining whether students’ technology-use intentions translate into perceived learning and actual learning outcomes. Survey data were collected from 642 students enrolled in an introductory information systems course, and the proposed relationships were tested using partial least squares structural equation modeling (PLS-SEM). The model incorporates attitude toward using technology as a mechanism connecting performance expectancy and effort expectancy with behavioral intention. It further proposes a sequential relationship in which behavioral intention predicts perceived learning, which subsequently predicts actual learning outcomes. The results indicate that performance expectancy had a strong positive relationship with attitude toward using technology (ß = .580, p < .001), while effort expectancy also positively influenced attitude (ß = .330, p < .001). Together, these two constructs explained 67.1% of the variance in attitude. Attitude was a strong predictor of behavioral intention (ß = .529, p < .001), and social influence also positively affected behavioral intention (ß = .265, p < .001). Facilitating conditions, however, did not have a statistically significant direct effect on behavioral intention (ß = .122, p = .113). Collectively, attitude, social influence, and facilitating conditions explained 69.9% of the variance in behavioral intention. Behavioral intention was positively associated with perceived learning (ß = .441, p < .001), explaining 19.5% of its variance. Perceived learning, in turn, positively predicted actual learning outcomes (ß = .345, p < .001), accounting for 11.9% of their variance. These findings suggest that students are more likely to develop favorable attitudes toward instructional technology when they perceive it as useful for improving academic performance and relatively easy to use. Positive attitudes and supportive social expectations subsequently strengthen students’ intentions to use technology. Most importantly, technology-use intention is associated with students’ perceptions of learning, which are then related to objectively assessed learning outcomes. The findings extend UTAUT from an adoption-oriented framework to a learning-oriented model and demonstrate the importance of distinguishing perceived learning from actual academic achievement. For information systems educators, the results suggest that instructional technologies should be easy to use, explicitly connected to course objectives, and integrated into meaningful learning activities. However, the modest variance explained in actual learning outcomes also indicates that technology acceptance alone is insufficient to guarantee academic achievement. Future research should incorporate actual technology-use data and examine additional factors such as self-efficacy, prior knowledge, motivation, instructional design, and student engagement.
Keywords: UTAUT, technology acceptance, behavioral intention, perceived learning, actual learning outcomes, information systems education, PLS-SEM