Ensemble Knowledge Tracing: Modeling interactions in learning process

首页 > 成果 > 详情

认领

导出

Link by DOI

反馈

作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Sun, Jianwen;Zou, Rui;Liang, Ruxia;Gao, Lu;Liu, Sannyuya;...

通讯作者：

Liu, Sannyuya(lsy5918@mail.ccnu.edu.cn)

作者机构：

[Liu, Sannyuya; Zou, Rui; Li, Qing; Liang, Ruxia; Sun, Jianwen] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan 430079, Peoples R China.

[Liu, Sannyuya; Gao, Lu] Cent China Normal Univ, Natl Engn Res Ctr Elearning, Wuhan 430079, Peoples R China.

[Liu, Sannyuya; Zou, Rui; Gao, Lu; Li, Qing; Liang, Ruxia; Sun, Jianwen] Cent China Normal Univ, Fac Artificial Intelligence Educ, Wuhan 430079, Peoples R China.

[Zhang, Kai] Yangtze Univ, Sch Comp Sci, Jingzhou 434025, Peoples R China.

[Jiang, Lulu] Nanhai Expt Sch, Foshan 528299, Peoples R China.

通讯机构：

[Sannyuya Liu; Qing Li] N

National Engineering Laboratory for Educational Big Data, Central China Normal University, Wuhan, 430079, China<&wdkj&>Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, 430079, China<&wdkj&>National Engineering Laboratory for Educational Big Data, Central China Normal University, Wuhan, 430079, China<&wdkj&>National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, 430079, China<&wdkj&>Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, 430079, China

语种：

英文

关键词：

Deep neural network;Knowledge Tracing;Learning interactions;User modeling

期刊：

Expert Systems with Applications

ISSN：

0957-4174

年：

2022

卷：

207

页码：

117680

DOI：

10.1016/j.eswa.2022.117680

基金类别：

Supported by the National Key R&D Program of China ( 2020AAA01 08804 ), National Natural Science Foundation of China ( 62077021 , 62077018 , 61977030 , 61937001 , 61807012 ), Humanity and Social Science Youth Foundation of Ministry of Education of China ( 20YJC880 083 ), Joint Research Fund of China Ministry of Education and China Mobile Company ( MCM20200406 ), Fundamental Research Funds for the Central Universities ( CCNU22LJ005 , CCNU20ZN007 ), Teaching Reform Research Project for Postgraduates of CCNU ( 2020JG14 ), and Teaching Research Project for Undergraduates of CCNU ( 202009 ).

机构署名：

本校为第一机构

院系归属：

国家数字化学习工程技术研究中心

摘要：

Knowledge Tracing (KT) aims to continuously estimate students’ evolving knowledge state during their learning process, which has attracted much research attention due to its potential for delivering personalized and optimal experiences to students in intelligent learning systems. The learning process is essentially the pairwise interactions of Students, Concepts, and Questions (S–C, S–Q, C–Q for short). Modeling all these interactions will improve the performance of KT. However, existing KT methods hardly exploit all the interactions in a s...

反馈

产权有误：本人成果被他人认领

数据有误：数据基本信息有误

归属有误：成果的院系归属、机构署名归属有误

其他原因：

验证码：

看不清楚，换一个

确定

取消

成果认领

标题：

用户	作者	通讯作者	--
	请选择	请选择	--

确定

取消

Ensemble Knowledge Tracing: Modeling interactions in learning process

反馈

成果认领

提示

该栏目需要登录且有访问权限才可以访问