A systematic review of visual representations for analyzing collaborative discourse

Visual analytics combines automated data analysis and human intelligence through visualisation techniques to address the complexity of current real-world problems. This review uses the lens of visual analytics to examine four dimensions of visual representations for analysing collaborative discourse: goals, data sources, visualisation designs, and analytical techniques based on 89 studies. We found visual analysis approaches to be suitable and advantageous for decomposing the temporality of collaborative discourse. However, it has been challenging for current research to simultaneously consider learning theories and follow visualisation design principles when adopting visualisations to analyse collaborative discourse. At the same time, existing visual analysis approaches have mainly targeted learners or researchers in online contexts and mainly focused on mirroring collaborative discourse rather than providing advanced affordances such as alerting or advising. Informed by these findings, we propose a possible future research agenda and offer suggestions for the features of successful collaboration to guide the design of advanced affordances.