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Using Genetic Algorithms in Pervasive Learning Systems
Current Issue
Volume 2, 2014
Issue 5 (October)
Pages: 44-47   |   Vol. 2, No. 5, October 2014   |   Follow on         
Paper in PDF Downloads: 33   Since Aug. 28, 2015 Views: 1558   Since Aug. 28, 2015
Siranush G. Sargsyan, Department of Programming and Information Technologies, Yerevan State University, Yerevan, Armenia.
Anna S. Hovakimyan, Department of Programming and Information Technologies, Yerevan State University, Yerevan, Armenia.
In this article an approach for the problem of building such tools of pervasive learning system that gives the user a chance to get the desired knowledge of teaching course in a user adaptable manner is suggested. This approach is based on “teaching scenarios” (sequence of teaching units) being constructed during the process of learning. We introduce a tool that builds user adaptable teaching scenarios based on Genetic Algorithms, built-in the Genetic Chooser Algorithm (GCA). These scenarios are being constructed via the quality and quantity characteristics of the teaching units and user’s knowledge. A course-map building tool is also introduced in GCA that helps user to see his /her progress through the course.
Genetic Algorithm, Pervasive Learning, User Adaptable Scenario, Knowledge Vector, L-Systems
S.G. Sargsyan, A.S. Hovakimyan, K.S. Darbinyan, N. Ispiryan, E. Petrosyan, TeachArm Toolset for e-learning support, Proc. of International Workshop. Information Technologies in education, Yerevan, Armenia, 2005.
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