Research And Implementation Of Adaptive E-Learning System

e-Learning system, being a great product of modern information technology, is an important means for implementing education informationization. Many e-Learning systems have been developed in recent years. However, most of them are unable to organize and present education materials according to individual learner's knowledge and learning ability. Based on the above reason, it is extremely important to analyze and construct an adaptive e-Learning system that is capable of guiding students in accordance with their individual aptitute.Guided by the construction and design principles of modern education theory, this paper puts forward an adaptive algorithm for adaptive e-Learning systems based on detailed research of the deficiencies in current systems' adaptability. An adaptive e-Learning system is designed and implemented. The main work and achievements of this paper are as follows:1. Research and design of adaptive algorithm for adaptive e-Learning system. This paper puts forward an adaptive algorithm based on the 'Bayesian Network' through analyzing and researching current adaptive strategies and algorithms. It includes the designs of adaptive e-Learning system's prototype, teaching strategy, adaptability diagnosing strategy, knowledge presentation strategy, and adaptive learning path strategy, and so on.2. The research presents the adaptive e-Learning system design, including the design of system functional models, business flow, data flow, and logical design of database.3. Adaptive e-Learning system implementation using techniques like XML, SQL Server, ASP, JavaScript, and so on.The adaptive e-Learning system of this paper has been under two semesters' trial use on courses like 'multimedia technology and application', 'computer science overview', 'principles of computer network', 'object-oriented program design' in Ningbo University of Technology. These courses have covered more than ten classes both including undergraduates and junior college students. During the trial use, the system has been running steadily. Tests show that the system has met its expected performance with preferable adaptive learning effects. and fine system performance. The research of this paper has laid the base for true intellectual online learning system that is able to offer an individualized quality education for every student.