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Exploration of Personalized Learning for University Students in the Era of AI

Qi Wang, Jinshui Wang, Zichao Wang, Xingquan Wu, Ying Liang, Guangzhou Zhou

Abstract


This paper delves into the pivotal role of Artificial Intelligence (AI) in enhancing personalized learning for university students. It begins by highlighting the challenges faced by students in resource acquisition, learning method adaptability, and motivation, and then discusses
how AI can address these issues through customized resources and adaptive learning environments. The paper further explores the application
of AI in course design, intelligent tutoring, learning analytics, and collaborative learning platforms, showcasing the technologys potential to
improve learning efficiency and outcomes. It also examines the future trends and challenges in the popularization of personalized learning,
emphasizing the need for ethical considerations and data security. The paper concludes by suggesting that future research should focus on the
long-term impact of AI in education and the importance of ensuring equitable access to its benefits for all students.

Keywords


Artificial Intelligence (AI); Personalized Learning; Higher Education; Learning Analytics

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References


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DOI: http://dx.doi.org/10.18686/neet.v2i4.4388

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