Research On The Recommendation Of Personalized Network Learning Resources Based On Learning Theory And Web Mining

Recent years, with the rapid development of information technology and networktechnology widely used in different kinds of learning and educational websites havesprung up one after another in large numbers, e-learning is becoming one of the majorlearning styles of today’s society, it breaks the restrictions of the time and space tolearners; opens up a new way of acquiring knowledge for learners; provides learnerswith opportunities of lifelong learning. As a result, learners can read and learnresources on the Internet and in the non-linear hypermedia environment according totheir interests and needs and by virtue of their preferred learning styles, this method oflearning has greatly increased the learning audience and promote the learners’enthusiasm of the independent study.The current network learning methods are still subject to the limitations of thetraditional teaching mode of thinking and learning methods, network teachingresources provided to learners to browse and to learn are just simple text links to show,the traditional service model of "people find information" has difficulties to adapt tothe needs of the learners about teaching resources on the Internet environment.Because of the different on every learner’s learning interests, needs, styles and so on,learners won’t be able to carry out effective personalized learning in traditionalnetwork service model. Therefore, this paper carries out in-depth study on how toachieve the personalized learning resources recommended problems on differentnetwork learners and uses the combination of theories and methods of moderneducation technology and web mining techniques, to provide good learning resourcesfor autonomous learning under the network environment.This paper analysis the existing limitations of network learning and evaluate thenetwork personalized learning resources recommendation technology research statusand method in Chinese and abroad. It combines network learning theory, thehumanistic learning theory, learning style theory and so on in instructional technologyand designs the frame of the personalized recommendation system, through a staticcollection of different learners’ backgrounds, learning levels, learning styles andlearning interests and so on, provides learning resources through personalized onlinelearning analysis. In addition，by association rule mining web log analysis，this systemcan have a real-time dynamic discovery about the changes of learners’ interests, the offsets of learners’ learning styles and the changes of knowledge fields, based on theview of knowledge, view of students, view of learning of constructivism and so on tolay the foundation personalized learning resources recommendation services for thelearners. This paper uses web mining technology and network personalizedrecommendation services technology, develops a system of personalized networklearning resources recommendation based on web mining. This system has a collectionof static data and dynamic data mining capabilities, provides the personalized learningresources for students in autonomous learning under the network environment andmeets the learning needs of different users. In view of the interests of individualdifferences learners, this paper presents the teaching resources in visual ways oflearning styles to learners who have individual different interests and usescontent-based and collaborative filtering recommendation technology to support thelearning process, so as to stimulate learners’ interests and enthusiasm and increaselearners’ initiative and the dominant position of the network. Apply the C#softwaredevelopment tool and SQL Server2005data base system to realize the personalizednetwork learning resource recommendation model and experimental system, theexperimental results show that, the learning efficiency and resources sharing are clearlypromoted.