The Use of Artificial Intelligence in Accounting Classes: Behavioral Insights from Students - Fachrurrozie, Fachrurrozie; Nurkhin, Ahmad; Santoso, Jarot Tri Bowo; Asrori, Asrori; Harsono, Harsono (Journal of Applied Data Sciences, 2025)
Accounting learning has entered a new transformation with the intensive use of artificial intelligence. This study analyzes student behavior in using artificial intelligence in accounting lectures. The Unified Theory of Acceptance and Use of Technology (UTAUT) framework is used to understand student behavior by adding the construct of experience and competence of information and communication technology. This study contributes to the extended application of UTAUT. This survey took a sample of accounting and accounting education students at the Faculty of Economics and Business, Universitas Negeri Semarang, totaling 124 students. The questionnaire distributed via Google Forms was used as a data collection technique. The data analysis technique used was SEM-PLS. The results of the analysis show moderate student behavior in using artificial intelligence in accounting lectures, there is 2.48 of an average score. ChatGPT and Canva are the types of AI most frequently used by students in accounting courses. SEM-PLS analysis indicates that students' intentions to use artificial intelligence in their accounting lectures are more determined by performance and effort expectancy. The coefficients are 0.519 and 0.382 at a P-value of 0.000. Social influence does not have a significant effect on student intentions, with a P-value of 0.104. Student intentions, ICT experience, and ICT competence significantly influence student behavior to use AI. The coefficients are 0.382, 0.241, and 0.214 at a P-value less than 0.05. Facilitating conditions do not have a substantial effect on actual behavior, with a P-value of 0.210. The practical implication of this study is the importance of highlighting students' ICT experiences and competencies that determine the use of AI for lecture purposes.