The future of Data-Driven Learning with Generative AI

Research output: Unpublished conference presentation (presented paper, abstract, poster)Conference presentation (not published in journal/proceeding/book)Academic researchpeer-review

Abstract

ChatGPT brings both opportunities and challenges to Data-Driven Learning (DDL). In a recent article (2023), I considered the potential use of ChatGPT as a concordancer but raised questions about the authenticity of its language and the accuracy of the generated answers. Since then, new updates have been introduced by ChatGPT, which can potentially overcome these issues. This brings us a step closer to the future of DDL assisted by Generative AI (GenAI).

In this talk, I will share my vision of DDL and how new advancements in GenAI may help realise it. As a concordancer developer, I consider user experience and ease of use as priorities in tool design. These are precisely where GenAI will excel when integrated into concordancers. I will explore this further and suggest stages at which GenAI integration could be most beneficial.

The discussion will extend to the relationship between GenAI and DDL. Some suggest that the convenience of ChatGPT may hinder inductive language learning, which DDL advocates. Learners will merely receive information instead of actively engaging with concordances. However, I argue that this view is not only unfair to GenAI but also detrimental to the future of DDL.
Original languageEnglish
Publication statusNot published / presented only - 21 Jun 2024
EventEuroCALL CorpusCALL Special Interest Group webinar series - University of Bath, United Kingdom
Duration: 21 Jun 2024 → …

Seminar

SeminarEuroCALL CorpusCALL Special Interest Group webinar series
Country/TerritoryUnited Kingdom
Period21/06/24 → …

Keywords

  • Generative AI
  • Data-driven learning
  • corpus linguistics
  • ChatGPT
  • concordancing
  • software development
  • computer-assisted language learning (CALL)

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