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One consistent area of need for students with autism spectrum disorders is in the area of social competence. However, the increasing need to provide qualified teachers to deliver evidence-based practices in areas like social competence leave schools, such as those found in rural areas, in need of support. Distance education and in particular, 3D Virtual Learning, holds great promise for supporting schools and youth to gain social competence through knowledge and social practice in context. iSocial, a distance education, 3D virtual learning environment implemented the 31-lesson social competence intervention for adolescents across three small cohorts totaling 11 students over a period of 4 months. Results demonstrated that the social competence curriculum was delivered with fidelity in the 3D virtual learning environment. Moreover, learning outcomes suggest that the iSocial approach shows promise for social competence benefits for youth.

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This exploratory study focuses on the design and evaluation of teaching analytics that relate social learning structure with performance measures in a massive open online course (MOOC) prototype environment. Using reflexive analysis of online learning trace data and qualitative performance measures we present an exploratory empirical study that: (a) rigorously evaluates a novel, multi‐dimensional performance construct; (b) describes differences in small group dynamics and structure; and (c) draws a connection between learning performance and group structure. Performance is operationalized using a combination of knowledge construction measurement from discussion boards, rigorous analysis of student work products and several indicators of small group identity in the course examined. Interview and observational data are used to develop an approach for deriving and validating a model of the social structure of students in the course using traces of interaction data. The connection between performance and structure is developed at the small group unit of analysis. Implications for MOOC design, scaling MOOC analytics and a vision for developing social sensors in MOOC environments are presented in the discussion and conclusion.