Treffer: Harness the Power of Interactive Large Language Model in Teaching Using a Capstone Project in the Database Management Course.

This teaching case explores the integration of generative AI, specifically Large Language Models (LLMs) such as ChatGPT, into the pedagogy of a database management course. Database management is a critical field within Information Systems, requiring students to master a wide array of skills, from conceptual design to SQL programming and real-world problem-solving. However, traditional teaching methods often present database concepts in isolation, which can hinder students' ability to grasp the holistic nature of database design, development, and maintenance. Additionally, current pedagogical approaches tend to emphasize technical syntax over critical thinking and problem-solving. They provide limited feedback, especially in larger classes, which delays students' learning progress. This case addresses these challenges by incorporating a capstone project that leverages ChatGPT to facilitate interactive and adaptive learning. Through the project, students engage with practical tasks such as designing relational databases, generating SQL queries, and maintaining databases in response to dynamic business requirements. ChatGPT plays a central role in providing immediate feedback, helping students refine their understanding, and allowing them to explore more advanced database operations at their own pace. The AI tool also encourages students to actively participate in their learning, transforming them from passive recipients of information into critical thinkers who can apply their skills to real-world problems. A quantitative evaluation of final exam grades revealed significant performance improvements in graduate cohorts. While undergraduate cohorts showed a positive upward trend, further analysis with larger sample sizes is recommended. The case highlights the transformative potential of generative AI in education, showcasing how AI-driven tools can enhance student engagement, personalize learning, and ultimately improve educational outcomes in database management education. Furthermore, the principles demonstrated in this case can be extended to other Information Systems courses, such as systems analysis, programming, and data analytics, broadening the applicability of generative AI in Information Systems education. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Information Systems Education is the property of Information Systems & Computing Academic Professionals (ISCAP) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)