Learning Resources Personalized Recommendation Mechanism Based On Learner’s Interest In Digital Lifelong Learning

With the gradual attention in lifelong learning, the environment of digital lifelonglearning is gradually increased; the learning resources are more and more expansion andredundancy. But, at the same time, which brings learners confusion to find learning resources.How learners can find their interested learning resources is concerned by more and moreresearchers. Against this background, I proposed a personalized recommendation mechanismwhich could recommend learning resources for learners according to the learner’s interests inthe environment of digital life-long learning. The main contents are as follows:(1) Modeling of the learners’ interests and learning resource. Learner registered,according to the registration information of the learner, the system analyzes learner’s interests.While the learner’s interests will be manifested in the terms of learners’ behaviors of browsing,collecting, and downloading. The system automatically modifies learner’s interests accordingto the learner’s behavior, and models the learner’s interests. At the same time, according to thetitle, the author, the description and the keywords, the system could model learning resources,and calculate relevance between learner’s interests and learning resources(2) Recommending of learning resources. System will track the behaviors of the learner,and generate a web log. Through analysis and conversion, we can get learner’s records ofbehaviors of browsing, collecting, and downloading. Combined with learner’s registrationinformation, learner’s interests can be got. According to the relevance of the learner’s interestsmodel and learning resources model, learners are recommended the learning resources whichthey interested in.(3) Judgment of recommended results. After learners get the recommended results, thesystem will judge recommend results by itself. If the learner collects or downloads therecommended learning resources, it is considered that learners are satisfied with therecommended results. The system will continue to recommend learning resources. If thelearner does not click the resources or just click that, it is considered that learners are notsatisfied with the recommended results. Then the system will adjust the learner’s interests,and re-recommend other learning resources.