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User Modeling and User-Adapted Interaction
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User Modeling and User-Adapted Interaction
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ICALT '04 Proceedings of the IEEE International Conference on Advanced Learning Technologies
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Computers & Education
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Computers & Education
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CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 3
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Expert Systems with Applications: An International Journal
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UAHCI'11 Proceedings of the 6th international conference on Universal access in human-computer interaction: applications and services - Volume Part IV
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Computers & Education
Expert Systems with Applications: An International Journal
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Computers & Education
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Expert Systems with Applications: An International Journal
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ADNTIIC'11 Proceedings of the Second international conference on Advances in New Technologies, Interactive Interfaces and Communicability
An Adaptive Course Generation Framework
International Journal of Distance Education Technologies
Multiagent Based Selection of Tutor-Subject-Student Paradigm in an Intelligent Tutoring System
International Journal of Intelligent Information Technologies
Expert Systems with Applications: An International Journal
Review: Student modeling approaches: A literature review for the last decade
Expert Systems with Applications: An International Journal
Personlized English reading sequencing based on learning portfolio analysis
Information Sciences: an International Journal
Detecting students' perception style by using games
Computers & Education
Radigost: Interoperable web-based multi-agent platform
Journal of Systems and Software
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In this paper we present eTeacher, an intelligent agent that provides personalized assistance to e-learning students. eTeacher observes a student's behavior while he/she is taking online courses and automatically builds the student's profile. This profile comprises the student's learning style and information about the student's performance, such as exercises done, topics studied, exam results. In our approach, a student's learning style is automatically detected from the student's actions in an e-learning system using Bayesian networks. Then, eTeacher uses the information contained in the student profile to proactively assist the student by suggesting him/her personalized courses of action that will help him/her during the learning process. eTeacher has been evaluated when assisting System Engineering students and the results obtained thus far are promising.