The widespread use of computing and communications technologies has enabled the popularity of social networks oriented to learn. In this work, we study the nature and strength of associations between students using an online social network embedded in a learning management system. With datasets from two offerings of the same course, we mined the sequences of questions and answers posted by the students to identify structural properties of the social graph, patterns of collaboration among students and factors influencing the final achievements. The results show some hints to pursue and investigate deep user analytics in online social learning systems, e.g., to build accurate prediction models for the success of effectiveness of the learning tasks based on the patterns of students' participation in the platform.
['M. E. Sousa-Vieira', 'José C. López-Ardao', 'Manuel Fernández-Veiga', 'Miguel Rodríguez-Pérez', 'Cándido López-García']
Mining relationships in learning-oriented social networks