Learning behaviour mining based on social network analysis

Social media have become a popular way to share and disseminate information, especially for young users. They bring new opportunities for education by providing a cooperative learning environment, which changes traditional instructional methods. In the cooperative learning environment, students can communicate and interact with each other and obtain new ideas from reflecting on others' thinking and observing others' behaviour. However, it is challenging for a teacher to organize group working in cooperative learning. Therefore, analyzing the social communication and deriving methodologies of learning behaviour mining can help understand the students' learning and thus provide suitable instructional strategies. In this paper, we design a cooperative learning system and propose algorithms of learning behaviour mining based on social network analysis, by which the teacher can understand more about group working activities, including the discussion contrition of each student, the grouping criteria according to students' characteristics, the evaluation strategies for team work, determination of active/passive or proficient/unproficient students, and detection of the group leader. These analyses provide teachers good suggestions for evaluating students' performances, setting up the group working and improving students' learning.