Determinants of Student Information Technology Adoption

Innovating service delivery in higher education is central to supporting institutional and societal goals of increasing the numbers of college graduates and for transforming higher education institutions to center on the needs of today\u27s students. Within this context, technology plays a critical role. This research seeks to contribute to institutional, academic and educational technology sector efforts to dramatically enhance service quality, in support of improving undergraduate student outcomes (student success), by identifying the determinants of student information technology adoption and removing barriers to accessing higher education. Using a mixed-methods and empirical approach based on the Unified Theory of Acceptance and Use of Technology (UTAUT), after an extensive literature review, individual interviews and focus groups, a web-based survey was administered to undergraduate students at Portland State University in Portland, Oregon to learn about their experiences with myPSU. myPSU is a web-based digital services platform (available as a native mobile application and website) that aids students in accessing services and resources critical to maintaining their enrollment. Structural Equation Modeling (SEM), including Principal Components Analysis (PCA), was used to analyze 1,841 valid survey responses and derive statistical results. The findings suggest that effort expectancy and social influence stand out as critical influences on behavioral intention to adopt myPSU, and new to UTAUT, that social influence and a students\u27 basic technology skills are significant determinants of effort expectancy. The model accounts for 42% of the variance for effort expectancy, 56% of the variance for behavioral intention to use and 83% of the variance for use behavior. Theoretically, this study contributes to the development of the UTAUT technology adoption model by suggesting the need, at least in a higher education context, of including skills as an important factor, as well as supporting the idea that more complex relationships exist between latent variables than a strict application of the UTAUT model affords. Also, PCA was leveraged to simplify the research model and its use raised questions about what role performance expectancy (perceived usefulness) might play in student information technology adoption. In sum, this research uniquely contributes to the research literature. It applies UTAUT to a higher education context to study the delivery of technology-enabled services and in doing so it makes contributions towards explaining the critical determinants of the adoption of software for accessing university services (one type of student information technology), related to how UTAUT could be applied in the university setting and how the model could be enhanced