Using multimodal learning analytics to identify patterns of interactions in a body-based mathematics activity
Article
Smith, C, King, B, Gonzalez, D. (2016). Using multimodal learning analytics to identify patterns of interactions in a body-based mathematics activity
. 27(4), 355-379.
Smith, C, King, B, Gonzalez, D. (2016). Using multimodal learning analytics to identify patterns of interactions in a body-based mathematics activity
. 27(4), 355-379.
Elementary students' difficulties with angles in geometry are well documented, but we know little about how they conceptualize angles while solving problems and how their thinking changes over time. In this study, we examined 26 third and fourth grade students completing a body-based angle task supported by the Kinect for Windows. We used fine-grained, multimodal data detailing students' actions and language to identify three common patterns of interactions during the task: the explore, dynamic, and static clusters. We found that students with higher learning gains spent significantly more time in the dynamic cluster than students with low learning gains. Implications for mathematics teaching and research using body-based tasks are discussed.
