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A Generic Model of Student-Based Adaptive Intelligent Web-Based Learning Environment

Intelligent e-learning systems intend to improve the quality of e-learning services and overcome the main shortcomings of e-learning technologies that presented the same learning material to all learners; “one-size fits-all” approach. In this paper, the suitable architectural design is proposed and the development modules of intelligent, adapted student-centered Web-based e-learning system are explained. It addresses students' diversity with different intellectual levels, different learning styles, so as to improve the learnt concepts and support the learners to achieve their learning goals effectively. The course contents are adapted and tailored to the characteristics of each learner. Each student has to answer two sets of well-selected tests to determine his background knowledge. These tests are randomly generated via an adapted rule-based reasoning engine utilizing questions repository and student and domain modules. Furthermore, the system will remember the last three sessions of the learning process for each student, even it is not completed, henceforward; the student can accomplish learning process from his last session. According to the experimental results, most of the students recommended to use it. Students were satisfied with the intelligent Web-based learning environment regarding the usefulness and efficiency. It helps to improve students’ knowledge level and academic progress.