Triangulating Learning in Board Games

In this paper, we delve into the connections between multiple methods for investigating game-based learning. We focus on three, connected analyses related to a single case (uncovering computational thinking in the play of the collaborative strategic board game Pandemic). We describe an approach for connecting content analysis, learning analytics, and d/Discourse analysis into a framework that both meaningfully chains quantitative and qualitative methods, as well as provides a useful means to generate new hypotheses for future games and learning research.