Cognitive assessment evaluation based on Blue-Red trees Inference of Rule-Space Model and social network learning

It is getting important that learning reciprocally from social network to intelligent e-learning system. In this paper, we used the Rule-Space Model to infer reasonable Blue-Red trees of learning performance and their definitions through analyzing learning objects of courses within system. We can derive social network learning grouping algorithms from previous definitions. They include one-to-one group collaborative learning algorithms. Further, we use these algorithms to build a social network learning system and apply to the Online Learning and Test System based on Analysis of Learning Performance and Social Network Learning Feedback. Besides learners are able to self-learning through Recommended Table to the Remedial Learning Objects for the Course, they can find out reasonable mutual learning targets by the suggestion of Blue-Red Trees Database of Learning Performance from the Social Network Learning System. There are the same results to improve the self-learning direction of learners and remedy the weaker learning objects for the course by internal cyclic feedback, and can also improve learning materials and items of the ITE Licenses Course by external cyclic feedback.