A Review of Data Mining in Personalized Education: Current Trends and Future Prospects  

作　　者：Zhang Xiong Haoxuan Li Zhuang Liu Zhuofan Chen Hao Zhou Wenge Rong Yuanxin Ouyang 

机构地区：[1]School of Computer Science and Engineering,Beihang University,Beijing 100191,China [2]School of Information Technology and Management,University of International Business and Economics,Beijing 100029,China

出　　处：《Frontiers of Digital Education》2024年第1期26-50,共25页数字教育前沿（英文）

基　　金：supported by the National Natural Science Foundation of China(No.62377002).

摘　　要：Personalized education,tailored to individual stu-dent needs,leverages educational technology and artificial intelligence(AI)in the digital age to enhance learning ef-fectiveness.The integration of AI in educational platforms provides insights into academic performance,learning pref-erences,and behaviors,optimizing the personal learning process.Driven by data mining techniques,it not only ben-efits students but also provides educators and institutions with tools to craft customized learning experiences.To offer a comprehensive review of recent advancements in person-alized educational data mining,this paper focuses on four primary scenarios:educational recommendation,cogni-tive diagnosis,knowledge tracing,and learning analysis.This paper presents a structured taxonomy for each area,compiles commonly used datasets,and identifies future re-search directions,emphasizing the role of data mining in enhancing personalized education and paving the way for future exploration and innovation.

关 键 词：personalized education data mining ed-ucational recommendation(ER) cognitive diagnosis knowledge tracing learning analysis 

分 类 号：G434[文化科学—教育学]