Approach generative AI tools proactively or risk bypassing the learning process in higher education

Sallai, Dorottya ORCID: 0000-0003-3411-4818, Cardoso-Silva, Jonathan ORCID: 0000-0002-9566-7400, Barreto, Marcos ORCID: 0000-0002-7818-1855, Panero, Francesca ORCID: 0000-0002-8287-163X, Berrada, Ghita ORCID: 0000-0001-8814-409X and Luxmoore, Sara ORCID: 0000-0002-9963-7487 (2024) Approach generative AI tools proactively or risk bypassing the learning process in higher education. LSE Public Policy Review, 3 (3). ISSN 2633-4046

Text (67289f0f7e209) - Published Version Available under License Creative Commons Attribution. Download (1MB)

Abstract

The growing reliance of higher education (HE) students on Generative Artificial Intelligence (GenAI) tools for learning and assessment risks circumventing rather than enhancing the learning process without adequate support and direction. Reflecting on experiences within a UK university, we explored how students use GenAI tools in practice. We argue that students rely on GenAI differently for learning than for assessments and tend to focus more on the output or performance than on the learning journey itself. This raises questions on how GenAI can be successfully integrated into the curriculum without jeopardising learning. Based on observations that some students use GenAI platforms as a substitute for learning rather than as a tool to enhance learning, our policy recommendations focus on curriculum planning and assessment design.

Item Type:	Article
Additional Information:	© 2025 The Author(s)
Divisions:	Management Data Science Institute Statistics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science H Social Sciences L Education
Date Deposited:	21 Jan 2025 14:54
Last Modified:	21 Jan 2025 14:57
URI:	http://eprints.lse.ac.uk/id/eprint/126982

Actions (login required)

View Item