From data to story: Leveraging LLM-powered chatbots for learning business data analytics and visualisation in Mathematica

Fei Du, Jinwen Luo, Sophy Xiaofei Wang

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter reports on implementing a transformative business analytics course integrating AI and AI literacy at Gies College of Business, University of Illinois, Urbana-Champaign (UIUC). The course employs a novel teaching approach using Mathematica integrated with AI functionalities, including a GPT-powered chatbot. This integration facilitates an innovative 'AI Mashup' method, enhancing students' ability to analyse diverse data types and produce compelling data narratives. Key course features include practical applications of computational recipes for complex analytics, interactive digital textbooks, and an emphasis on minimal coding for maximum functionality. Feedback from students indicates a high appreciation for the diverse applications enabled by powerful tools and the structured, beginner-friendly curriculum. The findings suggest that AI-integrated tools can enhance business analytics education by simplifying technical complexities and focusing on data storytelling, thereby preparing students more effectively for the digital economy's demands with increased AI literacy.

Original languageEnglish (US)
Title of host publicationEffective Practices in AI Literacy Education
Subtitle of host publicationCase Studies and Reflections
PublisherEmerald Group Publishing Ltd.
Pages101-110
Number of pages10
ISBN (Electronic)9781836088523
ISBN (Print)9781836088530
DOIs
StatePublished - Dec 2 2024

Keywords

  • AI integration in education
  • AI mashup
  • Business analytics education
  • Computational thinking
  • Large language models

ASJC Scopus subject areas

  • General Social Sciences

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