Author ORCID Identifier
Connie S. Barber: 0000-0002-9722-8014
Abstract
The objective of this research was to examine how generative AI might impact student learning in a data analytics course. Foundationally, we discuss the literature regarding the benefits, challenges, and policy around the use of gen AI in the classroom. The teaching case is then presented through the lens of the Technological Pedagogical Content Knowledge (TPACK) framework and addresses how the case aligns with each construct in the framework. Specifically, we examined how the use of generative AI might impact student learning regarding the relationship between data analyses and the data types needed to conduct them. Results indicate that generative AI can have a positive impact on student learning of data analytics. Overall, the paper contributes to AI literature through a synthesize of extant research and policy regarding AI in the classroom. Additionally, the results of the teaching case execution add to what is currently understood about the benefits of using generative AI to teach data analytics.
Recommended Citation
Barber, C. S., & Daniju, R. (In press). Gen AI as a Tool for Use in Teaching Data Analytics: the Literature and an Executable Case. Communications of the Association for Information Systems, 59, pp-pp. Retrieved from https://aisel.aisnet.org/cais/vol59/iss1/15
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