A self-adjusting e-course generation process for personalized learning
Expert Systems with Applications: An International Journal
Item difficulty estimation: An auspicious collaboration between data and judgment
Computers & Education
Multiagent Based Selection of Tutor-Subject-Student Paradigm in an Intelligent Tutoring System
International Journal of Intelligent Information Technologies
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Nowadays, students can easily access online course materials at anytime or anywhere. Since the learning initiative is taken by students in an e-learning environment, student-centered course materials become more critical. They may be prepared based on an individual student's learning expectation and academic background. In this paper, a model of personalized learning environment is proposed through 1) learning object design based on elaboration theory and e-learning standards; 2) applying item response theory (IRT) in student ability test; 3) managing course materials by a dynamic conceptual network (DCN); and 4) adopting a user profile to understand students' behaviors. Finally, these building blocks are developed by open-source software tools and integrated into a single system for real-life experimental study.