A Systematic Review of Educational Data Mining

被引：1
|
作者：
Xu, FangYao [1 ]
Li, ZhiQiang [2 ]
Yue, JiaQi [3 ]
Qu, ShaoJie [2 ]
机构：
[1] Beijing Inst Technol, Sch Math & Stat, Beijing, Peoples R China
[2] Beijing Inst Technol, Network & Informat Ctr, Beijing, Peoples R China
[3] Beijing Inst Technol, Sch Comp Sci, Beijing, Peoples R China
来源：
INTELLIGENT COMPUTING, VOL 2 | 2021年 / 284卷
关键词：
Improving classroom teaching; Pedagogical issues; Media in education; BIG DATA; PERFORMANCE; STUDENTS; ONLINE; CLASSIFICATION; ACCEPTANCE; ENGAGEMENT; PREDICTION; TEACHERS; LEARNERS;
D O I：
10.1007/978-3-030-80126-7_54
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
As an important part of data mining, educational data mining (EDM) has played a significant role in the field of education. This article reviews the development process of EDM, summarizes limited research directions of EDM from the past five years, and analyses the motivation and purpose of these studies, including the problems that have been solved. Next, the tools and algorithms used are introduced according to the referenced literature. Finally, this article discusses and summarizes further research directions based on previous research results and some thoughts with the hopes of offering researchers future research directions.
引用
收藏
页码：764 / 780
页数：17
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