Comparing Embodied Teaching Strategies in Online Statistics

• In Event: Embodied Learning in Mathematics: Gesture, Drawing, and Model Manipulation for Enhanced Learning

Abstract

Introductory statistics is a gateway course that often impedes student progression to degree completion. Successfully learning statistics relies on spatial skills, and embodied learning tools (gestures and drawing) support learning of critical spatial STEM concepts. The efficacy of these tools for statistics learning has never been explored, especially in online environments. This study compares online video instruction with gestures to instruction with drawings on novice undergraduates’ (N = 61) understanding of standard deviation, a challenging spatial statistics concept. To assess the magnitude of their efficacy, we included a control condition without gestures or drawings. Results revealed gestures were marginally more effective than drawing, with similar perceived engagement. Findings have implications for online statistics pedagogy.

Authors

• Luke Rabelhofer, University of California - Riverside

• Kinnari Atit, University of California - Riverside

• Catherine Lussier, University of California - Riverside

• Annie Stanfield Ditta, University of California - Riverside

• Felipe Cruz, University of California - Riverside