Technology plays an important role in the development of students who can search for the concepts which they learn in the books on the Internet and find out more information on them. This will increase the depth of their knowledge.
According to some researches, students tend to be more active and more participative when technology is being integrated in their lesson resulting to better comprehension and good performance.
Using technology in the learning process can facilities automatic detection of the learner's learning styles which can help the learner to develop his coping strategies to compensate for his/her weaknesses, capitalize on his/her strengths, improve the quality of the learning process and make it more effective.
This research presents an automatic tool for detecting learning styles in a learning environment by analyzing the content of the learner's favorite WebPages using social bookmarking services(www.tagme1.com) and shows that how actual behavior of the learners during the learning process can be used as an effective source for detecting their learning styles based on Felder-Silverman learning style model (FSLSM).