Design And Realization Of Personal Educational Resource Recommendation System

With the continuous development of computer and Internet technology, digital education plays a more and more important role in people’s life and study. It goes without saying that educational resources are one of the most important part for digital education, but the educational resources have not been given the due attention: on one hand, there are more and more learning resources on the internet, which can be described as "massive", thus it is difficult for the learners to find the suitable learning resources; on the other hand, all the learners see the same resource, which is not personalized.So, How to help learners find the suitable learning resources? More and more educators have begun to pay close attention to recommendation system, because the recommendation system can push the interested information and resources to the users based on users’interests. Now the recommendation system has been widely used in the field of electronic commerce, and the application has achieved great success, education scholars and experts have also begun to explore the application of recommendation systems in the field of education. But there is a big difference between the field of education and the field of electronic commerce, and the recommendation system applied successfully in the field of electronic commerce cannot be applied directly in the field of network education, and the characteristics of the field of education should be under consideration, based on e-commerce.This study draws lessons from the domestic and foreign researches, and applies "data mining","personal recommendation" technology, which are widely used in the field of business, combined with the features of education to educational resources. The main contents of the paper include the following aspects:Firstly, this paper generalizes the concept of the personal learning theory and recommendation algorithm. According to the characteristics of education resource recommendation system, the personality characteristics of learners and learning style features are considered into the collaborative recommendation algorithm to recommend the suitable educational resources. These theories and technologies are the basis of the realization of the recommendation system. Secondly, this paper designs and develops the exampled system. To provide more convenience for learners and let the learners study resources anywhere and anytime, the exampled system operated on the mobile phones, i.e. the application runs on the clients with the Android operating system.Finally, this paper tests the effect in a small scale, and does some small changes of the system based on the basis of the experiments.At last, summarize the innovation and disadvantages of this study, which aims to give the further research more reference.