计算机科学与探索2025，Vol.19Issue(10)：2683-2696,14.DOI:10.3778/j.issn.1673-9418.2412088
认知结构动态建模和遗忘显式计算的知识追踪模型
Dynamic Cognitive Structure Modeling and Explicit Forgetting Computation for Knowledge Tracing
摘要
Abstract
Knowledge tracing task aims to estimate students'knowledge state based on students'learning records,in which accurate modeling of learning and forgetting behavior is the key to accurately depict students'knowledge state.Existing approaches use a static knowledge structure to improve the learning modeling,and improve forgetting modeling by con-catenating temporal features and interaction information.However,students'cognitive structures change over time,and implicitly processing temporal features does not fully utilize temporal information.In order to solve the above problems,this paper proposes a framework called dynamic cognitive structure modeling and explicit forgetting computation for knowledge tracing(CSFKT),to better capture the evolution of students'knowledge states.The method first updates the adjacency matrix of students'cognitive structure using a GRU(gated recurrent unit)based on students'question answering interactions to construct a dynamically changing students'cognitive structure.Then,based on the cognitive structure,the neighbourhood aggregation is used to model the process of interactions between concepts.Next,a forgetting explicit cal-culation method is proposed,which uses the interval time and the forgetting curve formula to display the calculation of the memory retention probability and the discounted knowledge state.Moreover,this paper uses a GRU to obtain the knowledge state at the current moment and predict the probability of students'correct answers.A large number of experi-ments are conducted on three real datasets,and the results prove that CSFKT can not only model the dynamic cogni-tive structure but also explicitly model students'forgetting behaviors,with superior performance and good inter-pretability.关键词
知识追踪/图神经网络(GNN)/门控循环单元(GRU)/认知结构/遗忘曲线Key words
knowledge tracing/graph neural network(GNN)/gated recurrent unit(GRU)/cognitive structure/forgetting curve分类
信息技术与安全科学引用本文复制引用
张维,罗佩华,李志新,龚中伟,宋玲玲..认知结构动态建模和遗忘显式计算的知识追踪模型[J].计算机科学与探索,2025,19(10):2683-2696,14.基金项目
国家自然科学基金(62377024).This work was supported by the National Natural Science Foundation of China(62377024). （62377024）
