Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Artificial Intelligence
Opening up the Interpretation Process in an Open Learner Model
International Journal of Artificial Intelligence in Education
Inferring learning and attitudes from a Bayesian Network of log file data
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
A dynamic mixture model to detect student motivation and proficiency
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Bayesian student models based on item to item knowledge structures
EC-TEL'06 Proceedings of the First European conference on Technology Enhanced Learning: innovative Approaches for Learning and Knowledge Sharing
Context-Aware Adaptation: A Case Study On Mathematical Notations
Information Systems Management
Representation for Interactive Exercises
Calculemus '09/MKM '09 Proceedings of the 16th Symposium, 8th International Conference. Held as Part of CICM '09 on Intelligent Computer Mathematics
Modeling task experience in user assistance systems
Proceedings of the 27th ACM international conference on Design of communication
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
Predictive student model supported by fuzzy-causal knowledge and inference
Expert Systems with Applications: An International Journal
Multiple-choice cloze exercise generation through English grammar learning support
International Journal of Knowledge and Web Intelligence
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This paper describes a new student model technology that combines evidences and knowledge about pedagogical and domain structure. Its structure is generated from the metadata available in the content representation of the adaptive web-based learning platform ACTIVEMATH (or other contents). The evidences are processed with Item Response Theory and Transferable Belief Model uncertainty methodologies. We summarize evaluation results for this student model.