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Research on the Paths and Challenges of Large Language Models in Promoting Educational Equity

Author(s)

Yuming Sun*

Affiliation(s)

Experimental School Affiliated to Chinese Academy of Sciences, Beijing, China *Corresponding author.

Abstract

Large Language Models (LLMs), as a significant breakthrough in the field of artificial intelligence, are reshaping the allocation of educational resources. This paper explores how LLMs can promote educational equity through personalized learning support, multilingual education coverage, and low-cost resource provision, from the dual perspectives of technology empowerment and ethical risks. It also analyzes the challenges they face, such as the widening digital divide, embedded algorithmic bias, and inadequate cultural adaptability. The study proposes a three-dimensional governance framework comprising policy regulation, technological optimization, and social collaboration, providing a theoretical reference for the application of LLMs in promoting educational equity.

Keywords

Allocation of Educational Resources; Multilingual Education; Policy Regulation; Social Collaboration

References

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