Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 6
1686-1691

Knowledge tracing via neural inference on knowledge states

Zhang Kai1
Qin Xinyi1
Kuang Ying2
Qin Zhengchu1
1. School of Computer Science, Yangtze University, Jingzhou Hubei 434000, China
2. School of Foreign Languages, Yangtze University College of Arts & Sciences, Jingzhou Hubei 434020, China
DOI: 10.19734/j.issn.1001-3695.2022.11.0518

Abstract

Aiming at the problem that knowledge tracing research ignores the topological relationship between concepts, thereby limiting the representation of concept states and ultimately affecting the prediction effect, this paper proposed a knowledge state neural reasoning knowledge tracing model. Firstly, it established the concept relationship diagram and concept state diagram. Secondly, it used the diffusion model to obtain the projection of the relationship diagram and the state diagram and complete the fusion. Then, it used the inverse diffusion process to obtain the overall knowledge state representation that integrated the relationship between concepts, and finally predicted the performance of learners. In terms of model effectiveness, comparing four related models on several datasets, the proposed model achieves certain advantages. In terms of interpretability, the proposed model shows the correspondence between the evolution process of knowledge state and the actual answer results. In terms of practical application, the intelligent learning environment based on the model has been applied to an artificial intelligence course and an English grammar course respectively, and has achieved better results than the comparison model.

Foundation Support

国家自然科学基金资助项目(62077018)
国家科技部高端外国人才引进计划资助项目(G2022027006L)
湖北省自然科学基金资助项目(2022CFB132)
湖北省教育厅科学研究计划资助项目(B2022038)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.11.0518
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 6
Section: Algorithm Research & Explore
Pages: 1686-1691
Serial Number: 1001-3695(2023)06-013-1686-06

Publish History

[2023-01-05] Accepted Paper
[2023-06-05] Printed Article

Cite This Article

张凯, 秦心怡, 况莹, 等. 知识状态神经推理的知识追踪模型 [J]. 计算机应用研究, 2023, 40 (6): 1686-1691. (Zhang Kai, Qin Xinyi, Kuang Ying, et al. Knowledge tracing via neural inference on knowledge states [J]. Application Research of Computers, 2023, 40 (6): 1686-1691. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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