Analyzing Students’ Attitudes and Behavior Toward Artificial Intelligence Technologies in Higher Education

Abstract

In this study, we aim to contribute to the existing literature on the implementation of artificial intelligence (AI) in education. We explore the factors that impact the behavior and attitude of students toward the use of AI in higher education. We employed a quantitative approach using a wide range of adoption theories and models, including the unified theory of acceptance and use of technology model. We formulated hypotheses and verified the conceptual model. A questionnaire was used to collect data from 350 students. The structural equation model (SEM) was applied to estimate the relationship between dependent and independent variables. Based on SEM results, we found that despite perceived risk negatively impacting students’ attitudes, the factors of performance expectancy and facilitating conditions significantly influenced students’ attitudes and their behavioral intention to use AI in education. The results also show that effort expectancy does not significantly influence attitudes toward AI use in higher education. Research limitations are discussed at the end of this study.