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Using learning analytics to track learning process in virtual math teams (VMT) online environment

Afacan Adanır, Gülgün
The study has been conducted in the context of a graduate level Research Methods & Statistics course during 2013-2014 fall term in a large state university in Turkey. Aiming to introduce basic concepts of empirical research and experimental design, the course was structured in a way that the instruction was provided face-to-face and assignments were collaboratively completed online. There were 15 registered students in the course. Each registered student was assigned to a learning group and five teams were constructed in total. All teams were required to complete course assignments by collaboratively working online in a computer supported collaborative learning environment called Virtual Math Teams (VMT). For the solutions of the assignments, teams interacted in the chat environment and provided solutions as the wiki output. In this study, we employ a socio-technical approach to analyze the collaborative learning process taking place in the VMT that offers chat and wiki features. More specifically, we explored the use of learning analytic methods to investigate learning groups’ conceptual development in chat and wiki environments in the context of a semester long statistics course. We employed both quantitative and qualitative methods to analyze chat logs and wiki outputs. For the analysis of chat logs, our approach consists of segmentation analysis to divide chat logs into segments, topic detection for identifying focus of segments, and interaction analysis of episodes for tracking learners’ development of concepts. For the analysis of wiki content, we employed the content analysis and revealed the sufficiency of the content for the solution of the question. In addition, we compared the wiki content with the solutions proposed in the chat environment, hence explored the additions or removals in the finalized solution provided in the wiki environment.