Advanced Methods for Inconsistent Knowledge Management (Advanced Information and Knowledge Processing)
Constructing Adaptive Individual Learning Environment Based on Multi-agent System
CISW '07 Proceedings of the 2007 International Conference on Computational Intelligence and Security Workshops
Learning Assistant - Personalizing Learning Paths in e-Learning Environments
CISIM '08 Proceedings of the 2008 7th Computer Information Systems and Industrial Management Applications
Determination of Opening Learning Scenarios in Intelligent Tutoring Systems
Proceedings of the 2008 conference on New Trends in Multimedia and Network Information Systems
A method for learning scenario determination and modification in intelligent tutoring systems
International Journal of Applied Mathematics and Computer Science - Semantic Knowledge Engineering
Evaluating the effectiveness of intelligent tutoring system offering personalized learning scenario
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part I
KES-AMSTA'12 Proceedings of the 6th KES international conference on Agent and Multi-Agent Systems: technologies and applications
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The intelligent tutoring systems should guarantee an effective learning. Students who use those systems should achieve better learning results in a shorter time. Our previous research pointed out that the personalization of the learning scenario allows to satisfy the mentioned postulates. In this paper the method for determination of an opening learning scenario is presented. Before a student begins to learn an opening scenario is determined based on information provided during a registration process. User is offered the optimal learning path suitable for his learning styles and a current knowledge level. Worked out method applied the ant colony optimization technique. The effectiveness of the proposed solution was tested in a specially implemented environment. The researches demonstrate that the algorithm gives quite good results, because 66% of the learning material in the determined learning scenario were adapted to student's learning styles.