A comparative study of characteristics and preferences to learner models in educational adaptive hypermedia systems

Educational adaptive hypermedia systems are online learning that aim to tailor the experience characteristics and needs of individual learners. These use a variety techniques, including data analysis, machine learning, dynamic user interface, provide more effective personalized for each learner. The learner models in their designed help them better understand experience, do this take into account learner, such as style, education level, prior knowledge goals. Our work consists making comparative study its at functional level educational order conclude most model can improve academic results make accessible all learners, prove based on styles allows adaptation systems, development will be devoted next article.