IoT Applications for Recommended Methods of Physical Education Online Course Resources Based on Collaborative Filtering Technology

Abstract

Educational resources are available in different repositories and on the web. For example, these resources are in the form of courses, tutorials, simulations, tests, etc., and are available on the web. And these resources are constantly increasing. In this electronic age, it is necessary to develop systems to help people to find what they want and particularly what is more suitable to their personal subject interest. Recommender systems can help professors, researchers, and students to find the best educational resources suitable for his/her profile. The “e”-course characteristics and user profiles have to be considered, while providing the recommendations. A system can be developed where users can express a subject query to satisfy their information needs. During this stage, user characters and preferences are not considered and all users get the same results for that query. When the characteristics like language and preferences like practical and demonstrations are considered, then the information retrieval process should be improved by personalization. The set of characteristics and preferences of each user has to be stored and to be matched with e-course characteristics. There might be some characteristics that may be expressed using fuzzy values. It would be discussed how to find electronic educational resources that are suitable to the needs and characteristics of a user based on the user’s preferences and educational resources available. So, the present article recommended a method of physical education online course resources based on collaborative filtering technology.