Evolutionary computation approaches to the Curriculum Sequencing problem
Natural Computing: an international journal
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The need for providing learners with web-based learning content that match their accessibility needs and preferences, as well as providing ways to match learning content to user's devices has been identified as an important issue in accessible educational environment. For a web-based open and dynamic learning environment, personalized support for learners becomes more important. In order to achieve optimal efficiency in a learning process, individual learner's cognitive learning style should be taken into account. Due to different types of learners using these systems, it is necessary to provide them with an individualized learning support system. In this paper a framework of individual web-based learning system is presented by focusing on learner's cognitive learning process, learning pattern and activities. Based on the learner-centered mode and cognitive learning theory, we demonstrate an online course design and development that supports the students with the learning flexibility and the adaptability. The proposed framework utilizes genetic algorithm for representing and extracting a dynamic learning process and learning pattern to support students' deep learning, efficient tutoring and collaboration in web-based learning environment. And experiments do prove that it is feasible to use the method to develop an individual Web-based learning system, which is valuable for further study in more depth.