Integrating AI and Data Mining Tools into Information Systems Courses-A Case Study of Successes, Challenges, and Student Outcomes

This paper examines the integration of artificial intelligence (AI) and data mining tools into an undergraduate information systems course, assessing its impact on student engagement, comprehension, and practical skill development. With industries increasingly prioritizing data-centric roles, IT education must evolve to equip students with hands-on, technology-integrated skills relevant to workforce demands. Quantitative and qualitative data were collected using a mixedmethods approach to evaluate learning outcomes and instructional efficacy. Key findings revealed that students exhibited a 20 % increase in project scores and a 15 % improvement in quiz performance, with high engagement levels during hands-on and collaborative activities. Challenges included technical difficulties and varying programming skill levels, suggesting additional support resources were needed. The case study highlights best practices such as incremental skill-building, real-world data usage, and collaborative learning, which foster adaptability and analytical thinking. These results underscore the im- portance of AI-integrated learning approaches in IT education, bridging theoretical knowledge and industry needs and preparing students for data-driven roles.