Group learning analysis and individual learning diagnosis from the perspective of Big Data

This paper takes a blended course as an example in moodle platform. As a case study, multiple methods including statistical analysis, visualization and social network analysis were used to analyze the process and results of online learning. With the concept of Big Data, it analyzes 22 classes of 1088 students and teachers from a comprehensive perspective. It includes the access behavior, resource utilization, self-test exercises, interactive behavior and academic point of view of group behavior characteristics of online learning. In addition, it offers a sample of the self-diagnostic study report, thereby providing a learning diagnosis and decision-making reference for learners, teachers and administrators.