research-article

Cognitive Diagnosis Focusing on Knowledge Concepts

Authors:

Weiqi LuoAuthors Info & Claims

CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management

Pages 3272 - 3281

https://doi.org/10.1145/3511808.3557096

Published: 17 October 2022 Publication History

Abstract

Cognitive diagnosis is a crucial task in the field of educational measurement and psychology, which aims to diagnose the strengths and weaknesses of participants. Existing cognitive diagnosis methods only consider which of knowledge concepts are involved in the knowledge components of exercises, but ignore the fact that different knowledge concepts have different effects on practice scores in actual learning situations. Therefore, researchers need to reshape the learning scene by combining the multi-factor relationships between knowledge components. In this paper, in order to more comprehensively simulate the interaction between students and exercises, we developed a neural network-based CDMFKC model for cognitive diagnosis. Our method not only captures the nonlinear interaction between exercise characteristics, student performance, and their mastery of each knowledge concept, but also further considers the impact of knowledge concepts by designing the difficulty and discrimination of knowledge concepts, and uses multiple neural layers to model their interaction so as to obtain accurate and interpretable diagnostic results. In addition, we propose an improved CDMFKC model with guessing parameter and slipping parameter designed by knowledge concept proficiency and student proficiency vectors. We validate the performance of these two diagnostic models on six real datasets. The experimental results show that the two models have better effects in the aspects of accuracy, rationality and interpretability.

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Cited By

Qian HLiu SLi MLi BLiu ZZhou ABaeza-Yates RBonchi F(2024)ORCDF: An Oversmoothing-Resistant Cognitive Diagnosis Framework for Student Learning in Online Education SystemsProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671988(2455-2466)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671988
Huang YWang K(2023)Cognitive Diagnosis for Programming DomainsProceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023)10.2991/978-94-6463-242-2_19(153-163)Online publication date: 22-Sep-2023
https://doi.org/10.2991/978-94-6463-242-2_19
Zhang MZhu XZhang CQian WPan FZhao HFrommholz IHopfgartner FLee MOakes MLalmas MZhang MSantos R(2023)Counterfactual Monotonic Knowledge Tracing for Assessing Students' Dynamic Mastery of Knowledge ConceptsProceedings of the 32nd ACM International Conference on Information and Knowledge Management10.1145/3583780.3614827(3236-3246)Online publication date: 21-Oct-2023
https://dl.acm.org/doi/10.1145/3583780.3614827
Show More Cited By

Index Terms

Cognitive Diagnosis Focusing on Knowledge Concepts
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning

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cover image ACM Conferences

CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge Management

October 2022

5274 pages

ISBN:9781450392365

DOI:10.1145/3511808

General Chairs:
Mohammad Al Hasan
Indiana University Purdue University, Indianapolis, USA
,
Li Xiong
Emory University, Atlanta, USA

Copyright © 2022 ACM.

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Published: 17 October 2022

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The Guangdong Basic and Applied Basic Research Foundation
the Project of Guangxi Key Laboratory of Trusted Software
the Teaching Reform Research Projects of Jinan University
the Specially Creative University Project for Guangdong
the High Performance Public Computing Service Platform of Jinan University
the Science and Technology Planning Project of Guangzhou
National Natural Science Foundation of China

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CIKM '22

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CIKM '22: The 31st ACM International Conference on Information and Knowledge Management

October 17 - 21, 2022

GA, Atlanta, USA

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CIKM '22 Paper Acceptance Rate 621 of 2,257 submissions, 28%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

Qian HLiu SLi MLi BLiu ZZhou ABaeza-Yates RBonchi F(2024)ORCDF: An Oversmoothing-Resistant Cognitive Diagnosis Framework for Student Learning in Online Education SystemsProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671988(2455-2466)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671988
Huang YWang K(2023)Cognitive Diagnosis for Programming DomainsProceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023)10.2991/978-94-6463-242-2_19(153-163)Online publication date: 22-Sep-2023
https://doi.org/10.2991/978-94-6463-242-2_19
Zhang MZhu XZhang CQian WPan FZhao HFrommholz IHopfgartner FLee MOakes MLalmas MZhang MSantos R(2023)Counterfactual Monotonic Knowledge Tracing for Assessing Students' Dynamic Mastery of Knowledge ConceptsProceedings of the 32nd ACM International Conference on Information and Knowledge Management10.1145/3583780.3614827(3236-3246)Online publication date: 21-Oct-2023
https://dl.acm.org/doi/10.1145/3583780.3614827
Wei GHe ZGuan QFang LLuo WChen G(2023)NCDFSA: Neural Cognitive Diagnostic Focusing on Students' Attention to Knowledge Concepts2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)10.1109/SMC53992.2023.10394391(1957-1963)Online publication date: 1-Oct-2023
https://doi.org/10.1109/SMC53992.2023.10394391

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