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General Information
    • ISSN: 2010-3700 (Online)
    • Abbreviated Title: Int. J. Mach. Learn. Comput.
    • Frequency: Bimonthly
    • DOI: 10.18178/IJMLC
    • Editor-in-Chief: Dr. Lin Huang
    • Executive Editor:  Ms. Cherry L. Chen
    • Abstracing/Indexing: Scopus (since 2017), EI (INSPEC, IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
    • E-mail: ijmlc@ejournal.net
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.

IJMLC 2012 Vol.2(5):552-555 ISSN: 2010-3700

Optimization of Educational Systems Using Knapsack Problem

Nasim Zandi Atashbar and Fahimeh Rahimi
Abstract—The problem of automatically integrating adaptive content into different courses and curricula, thus exploiting the potential of the Internet in education is important. Learners' knowledge level is approached through a qualitative model of the level of performance that learners exhibit with respect to the concepts which are studied and are used to adapt the lesson contents and the navigation support. Learners' individual traits and especially their learning style represent the way learners perceive and process information, and are exploited to adapt the presentation of the educational material of a lesson. This paper proposes a new method to help learners find educational contents more adapted to their personalities in an efficient manner.

Index Terms—Adaptive learning, Bayesian networks, 0/1 Knapsack, Branch and bound algorithm, Sequencing, Elearning.

The authors are with Isfahan Mathematics House, Isfahan, Iran (email: nasim.zandi@yahoo.com; f_rahimi913@yahoo.com).


Cite:Nasim Zandi Atashbar and Fahimeh Rahimi, "Optimization of Educational Systems Using Knapsack Problem," International Journal of Machine Learning and Computing vol.2, no. 5, pp. 552-555, 2012.

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