Modelling students' algebraic knowledge with dynamic Bayesian networks

被引：3

作者：

Seffrin, Henrique ^{[1
]}

Bittencourt, Ig I. ^{[2
]}

Isotani, Seiji ^{[3
]}

Jaques, Patricia A. ^{[1
]}

机构：

[1] Univ Vale do Rio dos Sinos UNISINOS, PIPCA, Sao Leopoldo, Brazil

[2] Univ Sao Paulo, Sao Paulo, Brazil

[3] Univ Fed Alagoas UFAL, Rio Largo, Brazil

来源：

2016 IEEE 16TH INTERNATIONAL CONFERENCE ON ADVANCED LEARNING TECHNOLOGIES (ICALT) | 2016年

关键词：

Dynamic Bayesian Networks; Intelligent Tutoring Systems; Student Model; Learning diagnosis;

D O I：

10.1109/ICALT.2016.96

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper presents a dynamic Bayesian network model for the assessment of students' algebraic knowledge in step-based intelligent tutoring systems. The proposed work assesses knowledge about concept, skills, and misconceptions of learners. Furthermore, the proposed model is independent of the problems provided by the system (i.e., equations), because it considers the algebraic operation used by the student to solve a step as evidence instead of the final solution provided by the student. Results of evaluations comparing student's performance on a posttest with the inference of the proposed model showed statistically significant similarities between them, indicating that the inference performed by the model was accurate.

引用

页码：44 / 48

页数：5

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