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Introducing a new intelligent adaptive learning content generation method

Haghshenas, E ; Sharif University of Technology | 2010

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  1. Type of Document: Article
  2. DOI: 10.1109/ICELET.2010.5708382
  3. Publisher: 2010
  4. Abstract:
  5. E-learning environments are being used more efficiently by the rapid growth in internet and multimedia technologies. Adaptive learning is a kind of learning environment which provides individual learning. It can customize the learning style according to the individual's personality and characteristics. Although there are a lot of e-learning systems having adaptive learning feature, they do not satisfy all adaptive learning aspects. This paper proposes a new method which tries to help learners find educational contents adapted to their personalities in an efficient manner. Our proposed method has four essential parts: 1) It finds out learner's features by Bayesian networks. 2) Then It tries to select the most appropriate adaptive learning objects with 0/1 knapsack problem in a limited amount of time determined by learner. 3) An ant colony optimization algorithm is proposed to solve 0/1 knapsack problem efficiently. 4) Selected learning objects are then sequenced in order to preserve the prerequisites. Also we created a software application based on this method called BehAmooz for learners to find and comprehend the educational contents effectively
  6. Keywords:
  7. 0/1 Knapsack ; Adaptive learning ; Ant Colony Optimization (ACO) ; Bayesian ; Sequencing ; Algorithms ; Artificial intelligence ; Bayesian networks ; Distributed parameter networks ; E-learning ; Inference engines ; Integer programming ; Intelligent networks ; Optimization ; Learning systems
  8. Source: 2010 2nd International Conference on E-Learning and E-Teaching, ICELET 2010, 1 December 2010 through 2 December 2010 ; December , 2010 , Pages 65-71 ; 9781424490110 (ISBN)
  9. URL: http://ieeexplore.ieee.org/document/5708382/?reload=true