A model for reasoning about persistence and causation
Computational Intelligence
Evaluating tutors that listen: an overview of project LISTEN
Smart machines in education
Using Bayesian Networks to Manage Uncertainty in Student Modeling
User Modeling and User-Adapted Interaction
Student Modelling Based on Belief Networks
International Journal of Artificial Intelligence in Education
Identifiability: A Fundamental Problem of Student Modeling
UM '07 Proceedings of the 11th international conference on User Modeling
A Case Study Empirical Comparison of Three Methods to Evaluate Tutorial Behaviors
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Does Help Help? Introducing the Bayesian Evaluation and Assessment Methodology
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
International Journal of Artificial Intelligence in Education
Virtual Sport System for Optimum Exercising Based on a User Model
Edutainment '09 Proceedings of the 4th International Conference on E-Learning and Games: Learning by Playing. Game-based Education System Design and Development
Educational data mining: a review of the state of the art
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
An analysis of students' gaming behaviors in an intelligent tutoring system: predictors and impacts
User Modeling and User-Adapted Interaction
Ensembling predictions of student knowledge within intelligent tutoring systems
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
Faster teaching by POMDP planning
AIED'11 Proceedings of the 15th international conference on Artificial intelligence in education
Analyzing student gaming with bayesian networks
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part II
Modeling individualization in a bayesian networks implementation of knowledge tracing
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part I
The fine-grained impact of gaming (?) on learning
ITS'10 Proceedings of the 10th international conference on Intelligent Tutoring Systems - Volume Part I
The sum is greater than the parts: ensembling models of student knowledge in educational software
ACM SIGKDD Explorations Newsletter
International Journal of Artificial Intelligence in Education - Special issue on Best of ITS 2010
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This paper describes an effort to model a student's changing knowledge state during skill acquisition. Dynamic Bayes Nets (DBNs) provide a powerful way to represent and reason about uncertainty in time series data, and are therefore well-suited to model student knowledge. Many general-purpose Bayes net packages have been implemented and distributed; however, constructing DBNs often involves complicated coding effort. To address this problem, we introduce a tool called BNT-SM. BNT-SM inputs a data set and a compact XML specification of a Bayes net model hypothesized by a researcher to describe causal relationships among student knowledge and observed behavior. BNT-SM generates and executes the code to train and test the model using the Bayes Net Toolbox [1]. Compared to the BNT code it outputs, BNT-SM reduces the number of lines of code required to use a DBN by a factor of 5. In addition to supporting more flexible models, we illustrate how to use BNT-SM to simulate Knowledge Tracing (KT) [2], an established technique for student modeling. The trained DBN does a better job of modeling and predicting student performance than the original KT code (Area Under Curve = 0.610 0.568), due to differences in how it estimates parameters.