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Developing an Adaptive and Personalized e-Learning Environment
(Englisch)
A New Way to Learning Innovation
Rawad K.M. Hammad

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Developing an Adaptive and Personalized e-Learning Environment

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Autor/Autorin: Hammad Rawad K.M.

Rawad Hammad Hammad is the director of eLearning Center at the Islamic Unviersity of Gaza and part-time lecturer at Information Technology College as well. Mr. Hammad obtained his master degree from Goldsmiths University of London in Cognitive Computing. His research contributions/interests are in cognition, AI, S.E ,elearning, and adaptive system
Due to the diversity of e-learning usage in different disciplines (practical or theoretical, lifelong learning, formal vs 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.
Due to the diversity of e-learning usage in different disciplines (practical or theoretical, lifelong learning, formal vs 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.

Über den Autor



Rawad Hammad Hammad is the director of eLearning Center at the Islamic Unviersity of Gaza and part-time lecturer at Information Technology College as well. Mr. Hammad obtained his master degree from Goldsmiths University of London in Cognitive Computing. His research contributions/interests are in cognition, AI, S.E ,elearning, and adaptive system


Klappentext



Due to the diversity of e-learning usage in different disciplines (practical or theoretical, lifelong learning, formal vs 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.



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