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

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.