Julianna Washington

This article explores the use of Extended Reality (XR) technologies, such as Augmented Reality (AR) and motion capture, in mathematics instruction, specifically focusing on geometry learning. Our research highlights the challenges students face in learning geometry due to its abstract nature and the potential of XR technologies to create interactive and immersive learning experiences. We emphasize the role of embodied learning and gestures in mathematics education and how XR technologies can support equitable teaching practices. The embodied motions in XR allow for knowledge to be instantiated in physical ways, positioning all students as competent doers of mathematics. Two case illustrations are provided to demonstrate the power of XR technologies in teaching geometry. This article concludes with recommendations for teachers and researchers to incorporate gestures in mathematics instruction and leverage XR technologies to enhance students' understanding of mathematical concepts.

Augmented Reality (AR) technologies allow for holograms to be layered over the real-world, “augmenting” human vision by adding technical information or illustrations onto 3D space. Although AR-based applications are showing positive effects in many systematic reviews and meta-analyses, well-designed, rigorous studies with strong control conditions are lacking. Further, many experimental studies lack process data to illuminate what is happening as students engage with AR. In this pre-registered study, we conducted an experiment where n = 120 high school students were assigned to reason about identical geometry simulations collaboratively either using tablets or AR head‐mounted displays (HMDs). We look at their learning and how it was impacted by the dimensionality (2D or 3D) of the shapes they explored, as well as how they engaged with virtual objects using gestures and epistemic actions. AR HMDs were more effective for students getting an initial sense of 3D shapes, but less effective for 2D shapes. For gaining insights into the workings of shapes and formulating justifications of conjectures, we see no evidence AR is more effective, and trends indicating AR may be detrimental to eliciting generalizations. Further, process data showed that students using tablets are more likely to manipulate the geometric shapes in the simulations, while students using the AR HMDs are more likely to use dynamic gestures that simulate these manipulations, which are less constrained by the objects’ actual properties. Implications for the future design and use of AR in education are given.

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