Embodied learning taxonomy of sensorimotor engagement, gesture congruency, and immersion¶
Research Method · All research methods
Evidence · 4 claims (3 for, 1 against) · 2 studies (1 causal, 1 review),q2–q3· 0 of 2 report an effect size · 4 claims rest on one study
Description¶
The introduction reports, citing Johnson-Glenberg et al. and its 2017 update, an embodied learning taxonomy that "distinguishes components of embodied learning into three constructs": amount of sensorimotor engagement, congruence of gestures to content, and amount of immersion. Each construct spans four degrees, "the first degree being the lowest level of embodiment and the fourth degree being the highest." These formalized taxonomies and rubrics serve as design tools for XR learning designers and educators.
Accounts¶
- Embodied learning taxonomy distinguishing sensorimotor engagement, gesture congruency, and immersion across four degrees (as reported by Johnson-Glenberg and colleagues): The introduction reports, citing Johnson-Glenberg et al. and its 2017 update, an embodied learning taxonomy that "distinguishes components of embodied learning into three constructs": amount of sensorimotor engagement, congruence of gestures to content, and amount of immersion. Each construct spans four degrees, "the first degree being the lowest level of embodiment and the fourth degree being the highest." These formalized taxonomies and rubrics serve as design tools for XR learning designers and educators. (Jacob Fortman (2023))
- Immersion-interactivity framework of embodiment: The article proposes a 2x2 framework of embodiment for virtual learning environments built on the taxonomies of Johnson-Glenberg et al. (2014) and Skulmowski and Rey (2018). The immersion dimension ranges from low-immersion desktop or tablet simulations to high-immersion HMD-based VR, and the interactivity dimension ranges from incidental gestures (e.g., a laser pointer) to congruent gestures relevant to the learning task. The authors state: "In the context of VR, we propose a 2 × 2 framework of embodiment based on immersion and interactivity, building on these taxonomies." Unlike Johnson-Glenberg's ranked taxonomy, it does not specify whether immersion or interactivity matters more, and it predicts the greatest embodiment when both are high. (Klingenberg et al. (2024))
Claims¶
- Gesture mediated collaborative learning in an AR-headset astronomy task, including exploration, orientation, sharing and synthesizing AR perspectives, and sharing symbolic conception [+M]
- Young children collaboratively develop their own gestures to represent and explain challenging science concepts in a mixed-reality environment [+M]
- Neither immersion nor interactivity produced significant effects on transfer measures [-M]
- Learning in immersive VR produces higher self-reported presence, agency, location, body ownership, and embodied learning than learning via a PC screen [+M]
Related Research Methods¶
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Key Sources¶
- Jacob Fortman, Rebecca Quintana. (2023). Fostering collaborative and embodied learning with extended reality: Special issue introduction. International Journal of Computer-Supported Collaborative Learning. https://doi.org/10.1007/s11412-023-09404-1
- Klingenberg, S., Bosse, R., Mayer, R. E., & Makransky, G. (2024). Does Embodiment in Virtual Reality Boost Learning Transfer? Testing an Immersion-Interactivity Framework. Educational Psychology Review. https://doi.org/10.1007/s10648-024-09956-0
Page metadata
| Field | Value |
|---|---|
type |
research-method |
id |
embodied-learning-taxonomy-of-sensorimotor-engagement-gesture-congruency-and-immersion |
title |
Embodied learning taxonomy of sensorimotor engagement, gesture congruency, and immersion |
description |
The introduction reports, citing Johnson-Glenberg et al. |
status |
review |
generated |
by process:settle-candidates on 2026-10-18 |
trust |
unverified — no one has confirmed this page's content |
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