Bayesian Diagnosis Tracing: Application of Procedural Misconceptions in Knowledge Tracing

被引：3

作者：

Feng, Junchen ^{[1
]}

Zhang, Bo ^{[1
]}

Li, Yuchen ^{[1
]}

Xu, Qiushi ^{[1
]}

机构：

[1] 17zuoye, Beijing 100020, Peoples R China

来源：

ARTIFICIAL INTELLIGENCE IN EDUCATION, AIED 2019, PT II | 2019年 / 11626卷

关键词：

Procedural misconception; Bayesian knowledge tracing; Bayesian diagnosis tracing; Hidden Markov model; LEARNER; MODELS;

D O I：

10.1007/978-3-030-23207-8_16

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Bayesian diagnosis tracing model (BDT) replaces the generic "wrong" response in the classical Bayesian knowledge tracing model (BKT) with a vector of procedure misconceptions. Using a novel dataset with actual student responses, this paper shows the BDT model has better interpretability of the latent factor and minor improvement in out-sample predictability in some specification than the BKT model.

引用

页码：84 / 88

页数：5

共 11 条

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