In-Depth Application of Artificial Intelligence-Generated Content AIGC Large Model in Higher Education
Shi Yang, Siyuan Yang, Chaoran Tong
Abstract
Artificial Intelligence Generated Content (AIGC) large models have shown broad application prospects in various fields, and their in-depth application in higher education has also attracted widespread attention. This study aims to explore the application of the AIGC large model in higher education and evaluate its impact on teaching effectiveness. This study used literature review and experimental analysis methods to collect and analyze relevant literature. The research focuses on the application of AIGC in personalized learning, teaching resource expansion and automated assessment, and evaluates its effects. Research results show that AIGC can increase teaching efficiency to 96%. Its in-depth application in higher education has potential and advantages, and it can realize personalized learning and intelligent assisted teaching, provide customized learning resources and guidance, and promote students' learning outcomes and learning motivation.