计算机科学 ›› 2022, Vol. 49 ›› Issue (10): 83-95.doi: 10.11896/jsjkx.211000119

• 数据库&大数据&数据科学 • 上一篇    下一篇

知识追踪研究进展

陈之彧1, 单志龙1,2   

  1. 1 华南师范大学计算机学院 广州 510631
    2 华南师范大学网络教育学院 广州 510631
  • 收稿日期:2021-10-15 修回日期:2022-05-05 出版日期:2022-10-15 发布日期:2022-10-13
  • 通讯作者: 单志龙(zlshan@m.scnu.edu.cn)
  • 作者简介:(2020022957@m.scnu.edu.cn)
  • 基金资助:
    国家自然科学基金(62192711);广东省自然科学基金(2314050004664)

Research Advances in Knowledge Tracing

CHEN Zhi-yu1, SHAN Zhi-long1,2   

  1. 1 School of Computer Science,South China Normal University,Guangzhou 510631,China
    2 School of Network Education,South China Normal University,Guangzhou 510631,China
  • Received:2021-10-15 Revised:2022-05-05 Online:2022-10-15 Published:2022-10-13
  • About author:CHEN Zhi-yu,born in 1997,postgra-duate,is a student member of China Computer Federation.Her main research interests include big data of education and knowledge tracing.
    SHAN Zhi-long,born in 1976,Ph.D,professor,is a member of China Computer Federation.His main research interests include educational data mining and Internet of things.
  • Supported by:
    National Natural Science Foundation of China(62192711) and Natural Science Foundation of Guangdong Pro-vince(2314050004664).

摘要: 教育数据挖掘是计算机科学、统计学与教育学的交叉学科,主要通过计算机科学与统计学的理论和技术处理教育研究与教学实践的问题,比如在获得最大学习增益的情况下尽可能降低学生的学习成本和教师的教育成本。迅速发展的计算机辅助教育环境和在线教育平台产生了丰富的数据,当然也带来了挑战,无法针对性地为学生提供特定需求的资源。知识追踪是智能辅导教育领域对学生进行教学资源推荐和学习路径诊断的个性化方法,随着时间的推移,对学生的知识状态进行建模,从而根据学生的历史响应序列,预测学生未来的表现。重点从具有可解释性的训练过程、具备高精度的预测结果两方面对知识追踪进行相关文献的分析,并且介绍了该领域常见的数据集、评价指标和应用。最后,对知识追踪领域的挑战进行了展望。

关键词: 在线教育, 知识追踪, 可解释性, 高精度

Abstract: Educational data mining is an interdisciplinary subject of computer science,statistics and pedagogy,and it mainly deals with the problems of educational research and teaching practice through the theory and technology of computer science and statistics.For example,it can reduce the learning cost of students and the educational cost of teachers as much as possible under the condition of obtaining the maximum learning gain.The rapid development of computer-assisted education environments and online education platforms has generated a wealth of data,which has also posed a major challenge,of course,but it cannot provide resources for students’ specific needs.Knowledge tracing is an individual method for recommending teaching resources and diagnosing learning paths in the field of intelligent tutoring education.With the time going on,students’ knowledge states can be mo-deled to predict their future performance based on their historical response sequences.This paper focuses on the analysis of relevant literature from two aspects:knowledge tracing model on training process with interpretability,prediction results with high precision,and then introduces the public datasets,evaluation metrics and applications in this field.Finally,the challenges of knowledge tracing are prospected.

Key words: Online education, Knowledge tracing, Interpretability, High precision

中图分类号: 

  • TP391.6
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