App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 11

State graph evolution knowledge tracing model based on error effect mechanism

Zhang Baoliang1,2
He Jingyang1,2
Ruan Ziye1,2
Zhang Kai1,2
1. School of Computer Science, Yangtze University, Jingzhou Hubei 434023, China
2. Artificial Intelligence Research Platform, Yangtze University, Jingzhou Hubei 434023, China
DOI: 10.19734/j.issn.1001-3695.2026.04.0063

Abstract

Existing knowledge tracing models typically use prediction error as a training optimization signal without explicitly modeling its operational role. This paper proposed ESGE-KT, a state graph evolution-based knowledge tracing model incorporating an error effect mechanism. It combined input and relation modeling with local subgraph query prediction to obtain local knowledge states and current-response predictions. Conditional generation mapped scalar prediction error to a structured distribution over knowledge components, while the mechanism jointly modeled error-effect generation, propagation, and modulation on the knowledge-state relation graph, characterizing effect scope and intensity and driving progressive, stable state evolution. Experiments on four real-world educational datasets showed ESGE-KT outperformed 11 mainstream knowledge tracing models, improving AUC and ACC by up to 13.86% and 15.63%, respectively, and reducing RMSE by up to 15.10%. Results demonstrate that ESGE-KT improves prediction accuracy and state evolution stability and provides a mechanism-oriented modeling paradigm for knowledge tracing in continuous interaction scenarios.

Foundation Support

国家自然科学基金资助项目(62077018)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.04.0063
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 11

Publish History

[2026-07-02] Accepted Paper

Cite This Article

张宝良, 何璟阳, 阮紫叶, 等. 基于误差作用机制的状态图演化知识追踪模型 [J]. 计算机应用研究, 2026, 43 (11). (2026-07-31). https://doi.org/10.19734/j.issn.1001-3695.2026.04.0063. (Zhang Baoliang, He Jingyang, Ruan Ziye, et al. State graph evolution knowledge tracing model based on error effect mechanism [J]. Application Research of Computers, 2026, 43 (11). (2026-07-31). https://doi.org/10.19734/j.issn.1001-3695.2026.04.0063. )

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  • Application Research of Computers Monthly Journal
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    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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