ARTICLE
26 November 2025

Research on the Design Model of Personalized Learning Paths in Open Education Based on Artificial Intelligence

Yingjie Wang*
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1 Nanjing University of Finance and Economics, Nanjing 210003, China
LNE 2025 , 3(10), 34–39; https://doi.org/10.18063/LNE.v3i10.1097
© 2025 by the Author. Licensee Whioce Publishing, Singapore. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract

This paper analyzes the current situation, challenges and future development trends of personalized learning path design of Artificial Intelligence (AI) technology in open education. Through in-depth analysis of learning behavior data, artificial intelligence technology can construct knowledge graphs and capability models, thereby formulating personalized learning paths and significantly optimizing learning outcomes. However, the wide application of artificial intelligence has also encountered multiple challenges such as data privacy protection, handling of subjective factors, uneven distribution of resources, transformation of teachers’ functions, and ethical and moral issues. Looking ahead, data-driven educational decision-making, automated knowledge graph construction, and intelligent recommendation systems will become key development directions, but they still face important considerations such as data security and algorithm fairness.

Keywords
Open education
Artificial intelligence
Personalized learning path
Learn data analysis
Funding
Nanjing University of Finance and Economics’ University-level Teaching Reform Project, “Research on Task-oriented Teaching Methods for Social Science Courses from the Perspective of Big Data” (Project No.: XJWC3202555)
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