Submission Opportunity:

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npj Science of Learning

Embodied Learning Collection

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Journal

npj Science of Learning

 

Collection

Embodied Learning

 

Editors

Liye Zou, PhD， Johan Mårtensson, PhD，Qian Yu, PhD，Myrto Mavilidi, PhD， Xiaoqing Gu, PhD，Markus Raab, PhD & Fred Paas, PhD

 

Submission deadline

10 January 2027

https://www.nature.com/collections/ddeibijijd

 

Embodied learning spans phenomena ranging from gesture and object manipulation to navigation, social interaction, and affective and interoceptive signals, with increasing relevance for classrooms and digital environments (e.g., VR/AR, tangible interfaces, wearables, robotics). At the same time, the field faces key open questions: Which embodied mechanisms are causal rather than correlational? How should embodiment be measured, including offline effects of stored movement experiences and online effects during movement across timescales? Under what conditions does embodied enrichment improve transfer, retention, and generalization? What moderators and mediators (e.g., learner characteristics, task demands, technology, movement parameters) shape outcomes? And what design principles support robust and equitable benefits across learners and contexts?

This Collection aims to bring together mechanistic, methodological, and applied contributions that advance theory and evidence on embodied learning across development and the lifespan, bridging cognitive neuroscience, educational psychology, learning sciences, and learning analytics. Original studies, meta-analyses, systematic/scoping review, narrative review, perspective are welcome.

 

Given the breadth of the field, we particularly encourage contributions that develop generalizable theoretical or measurement frameworks that bridge tasks, domains, and contexts (e.g., gesture, VR/AR, social embodiment, interoception). Such work can reduce fragmentation and improve comparability across studies. We also explicitly invite research on boundary conditions, including cases where embodiment does not enhance learning or may hinder it. Studies that clarify when, why, and for whom embodied approaches fail will strengthen both mechanistic understanding and practical guidance.

 

Topics of interest include (but are not limited to)

Mechanisms and theory: grounded/embodied cognition, enactivism, dynamical systems, predictive processing accounts; perception-action coupling; sensorimotor and interoceptive contributions to learning.

Gesture, action, and tool use in language, mathematics, STEM, and concept learning; multimodal communication in instruction.

Embodied learning in technology-rich environments: VR/AR/MR, haptics, tangible user interfaces, wearables, and robotics; design principles that operationalize embodiment.

 

Social embodiment: joint action, synchrony, collaboration, teacher–learner coupling, and socially situated embodied interaction.

Neurobiological and physiological substrates: motor and premotor systems, hippocampal and cortical dynamics, autonomic/affective physiology, neuromodulatory influences.

 

Measurement and analytics: motion capture, inertial sensors, eye tracking, speech/gesture coding, physiological sensing, multimodal learning analytics, computational modeling, and causal inference.

Individual differences and inclusion: development, aging, neurodiversity, motor differences, accessibility, and equity-relevant moderators. Outcomes and implementation: transfer/generalization, long-term retention, ecological validity, classroom deployment, scalability, and reproducibility/replication.

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