A Tutorial on Teaching Data Analytics with Generative AI

This tutorial addresses the challenge of incorporating large language models, such as ChatGPT, in a data analytics class. It details several new in-class and out-of-class teaching techniques enabled by artificial intelligence (AI). Here are three examples: Instructors can parallelize instruction by having students interact with different custom-made GPTs to learn different parts of an analysis and then teach each other what they learned from their GPTs. Instructors can turn problem sets into AI tutoring sessions: a custom-made GPT guides a student through the problems and the student uploads the chatlog for their homework submission. Instructors can assign different labs to each section of a class and have each section create AI assistants to help the other sections work through their labs. This tutorial advocates the natural-language programming (NLP) paradigm, in which students articulate desired data transformations with a spoken language, such as English, and then use AI to generate the corresponding computer code. Students can wrangle data more effectively with NLP than with Excel.