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Modeling the in-class student social networks is a highly desired goal in educational literature. However, due to the difficulty to collect social data, most of the conventional studies can only be conducted in a qualitative way on a small-scale of dataset obtained through questionnaires or interviews. We propose to solve the problems of data collection, social network construction and analysis with multimedia technology, in the way that we can automatically recognize the positions and identities of the students in classroom and construct the in-class social networks accordingly. With the social networks and the statistics on a large-scale dataset, we have demonstrated that the pedagogical analysis for investigating the co-learning patterns among the students can be conducted in a quantitative way, which provides the statistical clues about why prior studies reach conflicting conclusions on the relation between the …