A Mixed-Methods Approach for Studying Collaborative Learning Processes at Individual and Group Levels

Learning processes that unfold during small-group collaboration may impact conceptual outcomes for individual students. To study how learning processes unfolded for eighth grade students collaborating in an e-textbook research activity, we analyzed data sources at individual and group levels using multiple methods, including nonparametric tests, text mining, Markov modeling, and quantitative discourse analysis. Individual measures revealed learning gains on content tests and documentation of shared ideas during collaboration. Group measures revealed increased conceptual discourse over time and streamlining of the research process. Measures at each level indicated distinct paths of inquiry for students and groups; however, these differences were not associated with negative conceptual outcomes. These findings have implications for how we understand how collaborative learning processes unfold, especially between the individual and the group, and how we design support for collaboration and knowledge sharing.