الفهرس 
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Abstract
The Internet technology has revolutionized the educational sector based on its advantage as an ocean of information. It has created new methods of learning and teaching that made the learning process simple, effective and more interesting. Moreover, according to many researches, learners tend to be more active when technology is integrated in their learning process, resulting in better comprehension and good performance. Recently, the adaptive systems have a significant role in developing the learning process. Among the major points of direct influence on making the learner’s environment more adaptable have been identifying the learner’s learning style that helps the learner to develop his/her coping strategies to compensate for weaknesses and capitalize on strengths. This thesis presents an automatic tool for detecting learning styles in a learning environment based on the concept of looking at what learners are really doing, when browsing the web and inferring their preferences and needs from their behavior and actions in the web using social bookmarking services. Also, it shows how the learners’ actual behavior during the learning process can be used as an effective source for detecting their learning styles based on Felder-Silverman Learning Style Model (FSLSM). This tool will help teachers to teach each student exclusively according to his/ her learning styles. Learners will be taught partly in the manner they prefer, which leads to an increased comfort level to learn. On the part of supervisors and administrators, this will help to improve the quality of the learning process.