ISEDJ

Abstract: This teaching tip presents a scalable model for integrating Generative AI (GenAI) and ethical reasoning into WPC 300 (Problem Solving & Actionable Analytics), a required core course taken by all undergraduate business students at Arizona State University. By embedding responsible GenAI use within established course modules, the intervention aims to strengthen students’ analytical confidence, deepen their understanding of ethical issues in data analysis, and prepare them for real-world business challenges. The model also supports instructors in delivering relevant, industry-aligned skills. The course redesign introduced GenAI tools, including OpenAI’s ChatGPT and Google Notebook, alongside core analytical methods such as regression analysis and data visualization. These tools were selected for their user-friendly interfaces and their ability to extend analytical capabilities beyond traditional Excel-based methods, supporting exploratory analysis, pattern recognition, and interpretation. Ethical considerations were scaffolded through a dedicated “Mindful AI” module emphasizing fairness, accountability, and societal implications. A mixed-methods evaluation, combining paired t-tests with sentiment and thematic analysis of student reflections, demonstrated statistically significant gains in students’ analytical confidence and understanding of ethical issues. Qualitative feedback further indicated increased appreciation for AI-assisted learning and ethical reflection. This model serves as a practical guide for educators aiming to modernize analytics instruction while maintaining core learning objectives. It provides students with a pathway to greater analytical confidence and ethical awareness and supports instructors by enabling the staged introduction of AI tools within existing course materials, reinforced by concrete applied examples.

Download this article: ISEDJ - V24 N6 Page 63.pdf

Recommended Citation: Satpathy, A., Balachander, J., (2026). Teaching with Generative AI: Ethics and Analytical Confidence in Undergraduate IS Education. Information Systems Education Journal 24(6) pp 63-74. https://doi.org/10.62273/ZYUC4609