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The Role and Challenges of AIGC-Driven Personalised Learning in Promoting Educational Sustainability: A Case Study Involving University Students in China

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Submitted:

03 February 2025

Posted:

04 February 2025

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Abstract
With the rapid development of Artificial Intelligence Generated Content (AIGC) technology, education is undergoing profound changes. AIGC significantly promotes inclusiveness, equity and quality of education by providing personalised learning content and intelligent instructional support to tailor the learning experience for students, which aligns with the United Nations 2030 Sustainable Development Goals (SDG4) requirements on the sustainability of education. However, despite the great potential of AIGC in education, its practical application still faces many challenges, such as unstable technology, untimely content updates, and privacy protection. This study takes Chinese college students as an example to explore the role and challenges of AIGC-based personalised learning in promoting educational sustainability. Through the analysis of 928 valid questionnaires and the SWOT-AHP method, this paper evaluates students' attitudes towards AIGC personalised learning and its impact on improving the quality of education, access to resources and fairness. The study also identified the main challenges in using AIGC, including technical problems, insufficient teacher-student interaction, and privacy security. The results show that AIGC positively impacts education's sustainability, but relevant technical and ethical challenges must be overcome to achieve its complete application. This study provides theoretical support for AIGC-based personalised learning and practical guidance for the future application and development of educational technology, aiming to provide a valuable reference for innovation and sustainable development in education.
Keywords: 
AIGC; educational sustainability; personalised learning; higher education; Chinese university students; SWOT; AHP
Subject: 
Arts and Humanities  -   Humanities
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.

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