Bridging the Physical Learning Divides: A Design Framework for Embodied Learning Games and Simulations

This paper proposes a unified design framework for embodied learning games and simulations, motivated by the inconsistent and often conflicting definitions of "embodiment" across human-computer interaction, learning sciences, and related fields. These inconsistencies have made existing systems difficult to compare and analyze. The authors derive their framework from a literature review of 48 published embodied learning designs, reducing an initial set of 25 candidate dimensions to seven through open coding and refining them with feedback from experts in HCI, game design, and learning science. These seven dimensions are organized into three groups: physical body and interactions, social interactions, and the world of interaction. The core analytical dimensions, Physicality and Transforms, along with Correspondence, form the backbone of the framework.

Applying the framework to the 48 systems, the authors sort most designs into nine categories, with 42 of the 48 fitting clearly into a single category. The analysis reveals that certain design spaces may be problematic. In particular, combining surrogate embodiment with PDt transforms in virtual environments appears to generate extraneous cognitive load, as learners struggled to track a physical avatar's position within the Tangible Earth system. The framework also exposes underexplored regions of the design space, which the authors map in a two-dimensional matrix of Physicality and Transforms.

The gap analysis identifies several promising unexplored pairings, including Surrogate combined with PPt and Surrogate combined with DPt. Illustrative concepts include physically embodied board games and asymmetric computational thinking games. The authors conclude that the framework provides a systematic means of analyzing where and how embodiment occurs in educational systems. They identify building and empirically evaluating systems that fill these gaps as the primary direction for future research.