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.