Abstract: Data Analytics has emerged as an essential skill for business students, and several tools are available to support their learning in this area. Due to the students’ lack of programming skills and the perceived complexity of R, many business analytics courses employ no-code analytical software like IBM SPSS Modeler. Nonetheless, generative Artificial Intelligence (AI) services such as ChatGPT can bridge the gap for students lacking programming skills. This teaching case demonstrates how students can use ChatGPT to generate R code for logistic regression analysis of a telecommunication company’s customer churn based on the Cross-Industry Standard Process Data Mining approach. ChatGPT enables students to implement the analysis method in R with a focus on building business solutions, freeing them from technical details. Teaching business students to use ChatGPT to implement data analysis is effective in helping them understand data, analytics models, and data interpretation. Moreover, this teaching case provides an opportunity for students to understand how to work with Artificial Intelligence in Data Analytics tasks.

Keywords: Data analytics, Generative AI in teaching, Logistic regression analysis, Natural language programming

Download This Article: JISE2024v35n2pp138-143.pdf

Recommended Citation: Zhong, C., & Kim, J. B. (2024). Teaching Case: Teaching Business Students Logistic Regression in R With the Aid of ChatGPT. Journal of Information Systems Education, 35(2), 138-143. https://doi.org/10.62273/DYLI2468