C4.5: programs for machine learning
C4.5: programs for machine learning
Student assessment using Bayesian nets
International Journal of Human-Computer Studies - Special issue: real-world applications of uncertain reasoning
Machine Learning
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Ensemble Methods in Machine Learning
MCS '00 Proceedings of the First International Workshop on Multiple Classifier Systems
Ensemble selection from libraries of models
ICML '04 Proceedings of the twenty-first international conference on Machine learning
YALE: rapid prototyping for complex data mining tasks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Student Modelling Based on Belief Networks
International Journal of Artificial Intelligence in Education
Performance Factors Analysis --A New Alternative to Knowledge Tracing
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
User models for adaptive hypermedia and adaptive educational systems
The adaptive web
An analysis of Bayesian classifiers
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Ensembling predictions of student knowledge within intelligent tutoring systems
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
Contextual slip and prediction of student performance after use of an intelligent tutor
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
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
A bayes net toolkit for student modeling in intelligent tutoring systems
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
Proceedings of the Third International Conference on Learning Analytics and Knowledge
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Many competing models have been proposed in the past decade for predicting student knowledge within educational software. Recent research attempted to combine these models in an effort to improve performance but have yielded inconsistent results. While work in the 2010 KDD Cup data set showed the benefits of ensemble methods, work in the Genetics Tutor failed to show similar benefits. We hypothesize that the key factor has been data set size. We explore the potential for improving student performance prediction with ensemble methods in a data set drawn from a different tutoring system, the ASSISTments Platform, which contains 15 times the number of responses of the Genetics Tutor data set. We evaluated the predictive performance of eight student models and eight methods of ensembling predictions. Within this data set, ensemble approaches were more effective than any single method with the best ensemble approach producing predictions of student performance 10% better than the best individual student knowledge model.