Investigating the impact of generative AI on students and educators: evidence and insights from the literature

Clos, J and Chen, YY ORCID: https://orcid.org/0000-0003-2773-2933, 2024. Investigating the impact of generative AI on students and educators: evidence and insights from the literature. In: TAS '24: Proceedings of the Second International Symposium on Trustworthy Autonomous Systems. New York: Association for Computing Machinery. ISBN 9798400709890

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Abstract

Generative artificial intelligence (AI) has become one of the main concerns of knowledge workers due to its ability to mimic realistic human reasoning and creativity. However, this integration raises critical concerns about trust and ethics, which are crucial in shaping both the acceptance and effective utilisation of these technologies. There are many reports, articles and papers currently exploring the opportunities and challenges of LLMs in higher education from the perspective of students and educators. However, these papers often focus on specific contexts like in the UK, US or a particular institutions. In this paper, we examine the problems of generative AI in higher education from educator and student perspectives using scientometrics and text analysis to provide an overview of the research landscape, followed by a narrative review and thematic analysis of selected literature. Some findings of this work are: (1) Students and educators found different ways to use generative AI. Students focus more on using it as an assistant (revising and preparing for lectures, helping with homework) and educators as a content production assistant (writing lecture notes, personalising content). Commonalities are that both students and educators use generative AI as an accessibility aid, e.g., to rephrase sentences or explain concepts. (2) The main concerns of higher education regarding generative AI are equity in access, clarity of rules regarding usage, and job displacement.

Item Type:	Chapter in book
Description:	Paper presented at the Second International Symposium on Trustworthy Autonomous Systems (TAS '24), Austin, Texas, United States, 16-18 September 2024. Article no. 25
Creators:	Clos, J. and Chen, Y.Y.
Publisher:	Association for Computing Machinery
Place of Publication:	New York
Date:	16 September 2024
ISBN:	9798400709890
Identifiers:	Number Type 10.1145/3686038.3686063 DOI 2386026 Other
Rights:	This work is licensed under a Creative Commons Attribution International 4.0 License.
Divisions:	Schools > Nottingham Business School
Record created by:	Jonathan Gallacher
Date Added:	26 Feb 2025 09:25
Last Modified:	26 Feb 2025 10:03
URI:	https://irep.ntu.ac.uk/id/eprint/53135

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