Name
Abstract | ||
|---|---|---|
In order to give adaptive instruction to the learner, it needs to know what knowledge the learner has and what goals the learner is trying to archive. This paper proposes a method to build a model based on Bayesian networks in order to assess the learner's knowledge level. An overlay student model based on Bayesian networks is presented. This student model built on knowledge relationships with prediction ability is discussed in details. In this model, an assessing method based on Logistic model in IRT with three parameters is provided to evaluate student's performance. A case study in the course of Data Structure is illustrated in this paper. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-72588-6_101 | International Conference on Computational Science (3) |
Keywords | Field | DocType |
bayesian network,bayesian networks,student model,prediction ability,knowledge level,logistic model,adaptive instruction,knowledge relationship,case study,data structure,overlay student model | Data structure,Knowledge level,Computer science,Bayesian network,Artificial intelligence,Overlay,Logistic regression,Machine learning | Conference |
Volume | ISSN | Citations |
4489 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 1 | 2 |