Using Multimodal Learning Analytics to Identify Patterns of Interactions in a Body-Based Mathematics Activity
Carmen Smith, University of Vermont, United States ; Barbara King, Florida International University, United States ; Diana Gonzalez, University of Vermont, United States
Journal of Interactive Learning Research Volume 27, Number 4, ISSN 1093-023X Publisher: Association for the Advancement of Computing in Education (AACE), Chesapeake, VA
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.
Smith, C., King, B. & Gonzalez, D. (2016). Using Multimodal Learning Analytics to Identify Patterns of Interactions in a Body-Based Mathematics Activity. Journal of Interactive Learning Research, 27(4), 355-379. Chesapeake, VA: Association for the Advancement of Computing in Education (AACE).
© 2016 AACE