A Pattern Recognition Method of Personalized Adaptive Learning in Online Education

In order to effectively identify the pattern of personalized adaptive learning in online education and improve the recommendation satisfaction of personalized learning resources in online education platform, this paper studies the pattern recognition method of personalized adaptive learning in online education. The learning behavior pattern data in the online education platform are mined, preprocessed, clustered and made correlation analysis, and the obtained data are used to construct the learner’s personalized adaptive learning characteristics model; on this basis, the framework of learning pattern recognition model is constructed to recognize the personalized adaptive learning pattern from four aspects: cognitive level, learning style, interactive behavior pattern characteristics and online social learning characteristics. The experimental test results show that this method can effectively identify the personalized adaptive learning patterns of learners, including interactive learning behavior patterns and online social learning patterns. The personalized learning resources recommended by the online education platform according to the identification results of this paper have obtained the learners’ satisfaction score of a high level at 93.27%.