A Bayesian Diagnostic Algorithm for Student Modeling and its Evaluation
User Modeling and User-Adapted Interaction
LOCH: Supporting Informal Language Learning Outside the Classroom with Handhelds
WMTE '05 Proceedings of the IEEE International Workshop on Wireless and Mobile Technologies in Education
An Intelligent SQL Tutor on the Web
International Journal of Artificial Intelligence in Education
An Approach to Context-Aware Mobile Chinese Language Learning for Foreign Students
ICMB '09 Proceedings of the 2009 Eighth International Conference on Mobile Business
Introducing prerequisite relations in a multi-layered bayesian student model
UM'05 Proceedings of the 10th international conference on User Modeling
Student modeling with atomic bayesian networks
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
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Ubiquitous learning is of interest to many researchers and developers to build adaptive course for learners at anytime and in anywhere. To create personalized learning content suitable for each learner, one challenge is to manage and evaluate the learning model, known as the learner's profile. Our previous study represented a model of CAMLES [1] system which is a personalized context - aware adaptive system in mobile learning to support students to learn English as a foreign language in order to prepare for the TOEFL test as a case study in Vietnam. This paper represents how to apply Bayesian Network in order to manage learner model which is a key factor to determine the learning content adaptation for the learner's demands and knowledge of individual learners. Uncertainty factors used to determine the level of understanding of learners for each concept in the content model.