Personalize eLearning System using Three Parameters and Genetic Algorithms
Abstract: The growing interest of eLearning in educational setting has been exponentially proliferated focusing only on the development and delivery of content among learners. Many researches manage to develop learning materials and put it the web to become electronically accessible to everyone or selected groups of learners. Many researchers have focused on developing personalized eLearning mechanism to assists the learning process but few have considered multiple parameters. Moreover, personalized eLearning system seems to neglect how to maximize the learning due to exclusion of learner’s ability and difficulty level in the design and inappropriate learning sequence. With the employment of genetic algorithms, a personalized curriculum sequence based on the learner’s prior knowledge and background can be developed. Moreover, by extracting the learner’s learning style and preferred media a second level of personalization can be achieved to determine the proper learning sequence.