Assessing IS Learning Outcomes Effectively in the Age of GenAI

The recent, rapid expansions of artificial intelligence (AI) technologies, and especially web-based generative AI tools (GenAI), has radically changed the field of education. These changes have forced educators to reconsider the teaching instruments they deploy, and the methods they use, to formatively and summatively assess student learning. This paper represents a work-in-progress case study conducted in a senior-level college course on database administration and NoSQL. Quantitative and qualitative observations from a class of 24 students majoring in Information Systems (IS), Information Technology (IT), and Cybersecurity disciplines at a large, regional public university are reported. Findings include self-reported measures of student use of GenAI to complete technical tasks, along with comments and recommendations from students regarding their experience using GenAI in the class, especially on the final project. The paper concludes with observations about how and when to use GenAI in teaching and learning, methods for documenting and demonstrating student learning, and future research in this area.