Towards a research agenda for generative AI in university mathematics education.

Paola Iannone, Irene Biza, Ben Davies, George Kinnear, Juuso Henrik Nieminen

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract

This paper reports preliminary results of a study employing the Delphi method to ascertain the consensus of stakeholders regarding the role and use of generative artificial intelligence (genAI) in teaching and learning undergraduate mathematics. Participants to the study included mathematicians, mathematics educators, and learning designers. The data consists of responses to an online survey which asked participants to state the most urgent research questions related to the use of genAI in university mathematics. We obtained 41 research questions by 34 participants from 23 institutions. We grouped these questions under two broad thematic headings: "questions concerning students' interaction with genAI" and "questions concerning teachers' interaction with genAI". These themes indicate what participants deem a pressing research agenda concerning genAI in university mathematics to be. We conclude with a description of the next steps for this study.
Original languageEnglish
Title of host publicationProceedings of the Fourteenth Congress of the European Society for Research in Mathematics Education (CERME14)
Pages2261-2268
Publication statusPublished - 3 Sept 2025

Keywords

  • university mathematics
  • GenAI and large language models
  • Delphi method

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