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Mechanisms and Challenges of the Impact of Personalized Learning Based on Aigc Technology on Educational Sustainability: A Case Study Based on Chinese College Students

by Zhileng Xiong, Yixin Li, and Qing Huang

Posted: March 19, 2025
Server: Preprints.org
DOI: 10.20944/preprints202502.0194.v4

The rapid advancements in Artificial Intelligence-Generated Content (AIGC) technology have positioned AIGC-driven Personalized learning as a critical pathway for advancing educational sustainability, particularly in addressing inclusiveness, equity, and quality. This study examines the mechanisms and challenges of AIGC applications in Chinese higher education through a mixed-methods approach combining systematic literature review and empirical analysis. Leveraging the SWOT framework and Analytic Hierarchy Process (AHP) with 928 valid student questionnaires, we establish a multi-criteria decision-making framework to evaluate strategic priorities and operational risks.

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