GraphCA: Learning from Graph Counterfactual Augmentation for Knowledge Tracing-Reference-Cited by-同舟云学术

GraphCA: Learning from Graph Counterfactual Augmentation for Knowledge Tracing

Published:2023-11 Issue:11 Volume:10 Page:2108-2123
ISSN:2329-9266
Container-title:IEEE/CAA Journal of Automatica Sinica
language:
Short-container-title:IEEE/CAA J. Autom. Sinica

Author:

Wang Xinhua¹,Zhao Shasha¹,Guo Lei¹,Zhu Lei¹,Cui Chaoran²,Xu Liancheng¹

Affiliation:

1. School of Information Science and Engineering, Shandong Normal University,Jinan,China,250358

2. School of Computer Science and Technology, Shandong University of Finance and Economics,Jinan,China,250014

Funder

Natural Science Foundation of China

Natural Science Foundation of Shandong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Information Systems,Control and Systems Engineering,Control and Optimization

Link

http://xplorestaging.ieee.org/ielx7/6570654/10266575/10266657.pdf?arnumber=10266657

Reference70 articles.

1. More Accurate Student Modeling through Contextual Estimation of Slip and Guess Probabilities in Bayesian Knowledge Tracing

2. Counterfactual Cycle-Consistent Learning for Instruction Following and Generation in Vision-Language Navigation

3. Knowledge tracing: Modeling the acquisition of procedural knowledge

4. Counterfactual Samples Synthesizing for Robust Visual Question Answering

5. Effective skill assessment using expectation maximization in a multi network temporal bayesian network;pardos;Proc Young Researchers Track at 9th Int Conf Intelligent Tutoring Systems,0

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