Towards a unified framework for knowledge tracing with graph convolutional and neural architectures

This paper sets out to propose a unified theoretical framework for knowledge tracing (KT) that combines graph convolutional networks (GCNs) with neural sequence architectures in intelligent tutoring systems. While existing methods have achieved some success, they face limitations in modelling relati...

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Bibliographic Details

Main Authors:	Yaxi, Su, Darus, Mohamad Yusof, Mat Diah, Norizan, Jinpeng, Huang, Ramli, Azlin
Format:	Article
Language:	en
Published:	Universiti Teknologi MARA 2025
Subjects:	Neural networks (Computer science) Database management
Online Access:	https://ir.uitm.edu.my/id/eprint/125995/2/125995.pdf https://ir.uitm.edu.my/id/eprint/125995/
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