Due to the diversity of e-learning usage in different disciplines (practical or theoretical, lifelong learning, formal versus informal education, etc) There are different and multipurpose platforms available in the market and in the educational sector. Personalization and Adaptation techniques are the most new factors that give e-learning environments effectiveness and efficiency. The main goal of this research is to help the academic institutions achieving their learning objectives via implementing new innovative teaching technologies in e-learning environments. To Achieving this goal, I will go through answering the main research question which is: how to personalize and adapt the learning material for each student? I build a framework that constitutes mainly from two components. One is the user Model that is based on mining student data to recommend a learning path for a given student. The second component is the adaptation and personalization engine that is responsible of live adaptation for student path according to his progress in the course. Then, I implemented the framework on the Moodle open-source virtual learning environment.
Keywords:
Data mining; Adaptation; Personalization; User Modelling; Intelligent Tutoring Systems; e-Learning