在线教育学习者知识追踪综述  

Review of online education learner knowledge tracing

作　　者：赵雅娟 孟繁军 徐行健 ZHAO Yajuan;MENG Fanjun;XU Xingjian(College of Computer Science and Technology,Inner Mongolia Normal University,Hohhot Inner Mongolia 010022,China)

机构地区：[1]内蒙古师范大学计算机科学技术学院,呼和浩特010022

出　　处：《计算机应用》2024年第6期1683-1698,共16页journal of Computer Applications

基　　金：内蒙古自然科学基金资助项目(2023LHMS06011,2023MS06016);内蒙古师范大学基本科研业务费专项(2022JBQN105);内蒙古自治区军民融合重点科研项目及软科学研究项目(JMRKX202201)。

摘　　要：知识追踪(KT)是在线教育中一项基础且具有挑战性的任务,同时也是从学习者的学习历史中建立学习者知识状态模型的任务,可以帮助学习者更好地了解自己的知识状态,使教育者更好地了解学习者的学习情况。对在线教育学习者KT研究进行综述。首先,介绍KT的主要任务和发展历程;其次,从传统KT模型和深度学习KT模型两个方面展开叙述;再次,归纳总结相关数据集和评价指标,并汇总KT的相关应用;最后,总结KT现状,讨论它们的不足和未来发展方向。Knowledge Tracing(KT)is a fundamental and challenging task in online education,and it involves the establishment of learner knowledge state model based on the learning history;by which learners can better understand their knowledge states,while teachers can better understand the learning situation of learners.The KT research for learners of online education was summarized.Firstly,the main tasks and historical progress of KT were introduced.Subsequently,traditional KT models and deep learning KT models were explained.Furthermore,relevant datasets and evaluation metrics were summarized,alongside a compilation of the applications of KT.In conclusion,the current status of knowledge tracing was summarized,and the limitations and future prospects for KT were discussed.

关 键 词：知识追踪 学习者 知识状态 在线教育 深度学习 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]