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Exploring Implementations of GenAI in Teaching IS Subjects and Student Perceptions
Journal article   Peer reviewed

Exploring Implementations of GenAI in Teaching IS Subjects and Student Perceptions

Yabing Jiang and Kazuo Nakatani
Journal of information systems education, Vol.36(2), pp.180-194
04-01-2025

Abstract

Active Learning Artificial intelligence Bans Class Activities College Faculty Control Groups Critical Thinking Educational Change Educational objectives Experimental Groups Feedback (Response) Information systems Instructional Materials Integrity Learner Engagement Learning activities Literature reviews Opportunities Outcomes of Education Perceptions Programming Researchers Robot learning School Policy Skill Development Skills Student Surveys Students Teachers Teaching Teaching Methods Data Analysis Higher Education
This research answers the call for Information Systems (IS) faculty to actively embrace rapidly advancing AI tools in teaching. We experimented with redesigning learning activities in two courses, requiring students to use GenAI, to aid student learning and teach responsible use of GenAI. The results show that students in the experimental group performed at the same or a higher level than those in the control group in terms of learning. Additionally, the two major concerns reported in prior research, (1) academic integrity and (2) student overreliance on AI and AI hallucinations, were not issues in our study. We conducted a student perception survey and found that students responded favorably to GenAI assignments, though not all students actively engaged with GenAI. This research demonstrates two ways of incorporating GenAI in teaching (assisting with writing a technical report and learning programming concepts) and provides initial empirical support for proactively adopting GenAI in higher education. Learning from the experiment, we provide practical recommendations for applying GenAI in teaching and learning IS subjects.
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