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The Future of Learning: Large Language Models through the Lens of Students

  • He Zhang
  • , Jingyi Xie
  • , Chuhao Wu
  • , Jie Cai
  • , Chan Min Kim
  • , John M. Carroll

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As Large-Scale Language Models (LLMs) continue to evolve, they demonstrate significant enhancements in performance and an expansion of functionalities, impacting various domains, including education. In this study, we conducted interviews with 14 students to explore their everyday interactions with ChatGPT. Our preliminary findings reveal that students grapple with the dilemma of utilizing ChatGPT’s efficiency for learning and information seeking, while simultaneously experiencing a crisis of trust and ethical concerns regarding the outcomes and broader impacts of ChatGPT. The students perceive ChatGPT as being more “human-like” compared to traditional AI. This dilemma, characterized by mixed emotions, inconsistent behaviors, and an overall positive attitude towards ChatGPT, underscores its potential for beneficial applications in education and learning. However, we argue that despite its human-like qualities, the advanced capabilities of such intelligence might lead to adverse consequences. Therefore, it’s imperative to approach its application cautiously and strive to mitigate potential harms in future developments.

Original languageEnglish (US)
Title of host publicationProceedings of 25th Annual Conference on Information Technology Education, SIGITE 2024
PublisherAssociation for Computing Machinery, Inc
Pages12-18
Number of pages7
ISBN (Electronic)9798400711060
DOIs
StatePublished - Dec 8 2024
Event25th Annual Conference on Information Technology Education, SIGITE 2024 - El Paso, United States
Duration: Oct 9 2024Oct 11 2024

Publication series

NameProceedings of 25th Annual Conference on Information Technology Education, SIGITE 2024

Conference

Conference25th Annual Conference on Information Technology Education, SIGITE 2024
Country/TerritoryUnited States
CityEl Paso
Period10/9/2410/11/24

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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