Introducing a new intelligent adaptive learning content generation method

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.