Compilers: principles, techniques, and tools
Compilers: principles, techniques, and tools
An Empirical Approach to On-Line Learning in SIETTE
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
Adaptive Bayesian Networks for Multilevel Student Modelling
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
A Framework for the Initialization of Student Models in Web-based Intelligent Tutoring Systems
User Modeling and User-Adapted Interaction
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SIETTE is an efficient web-based implementation of a Computer Adaptive Test. The inference machine used is based on Item Response Theory. New enhances in the evaluation mechanisms, question selection and finalization criteria have been introduced. New evaluation mechanism allows giving structured knowledge estimation about all topics evaluated in a test. Question selection criteria are able to automatically select a balanced number of items from all topics, so teachers do not need to accomplish this task manually. This paper shows that SIETTE can successfully be integrated into web-based Intelligent Tutoring Systems with structured curriculum, in order to make initial estimations of the student's knowledge level, or even to update the student's model after his exposition to instructional components.