In March 2025, Professor Liye Zou’s team from the School of Psychology, Shenzhen University, published a paper in Nature Human Behaviour (2023 Impact Factor = 22.3) titled “The Synergy of Embodied Cognition and Cognitive Load Theory for Optimized Learning.” This study proposed a synergistic mechanism model integrating embodied cognition and cognitive load theory, constructing a theoretical framework that emphasizes the role of mind–body integration in optimizing learning outcomes.
1. Research Background
Cognitive Load Theory (CLT), an important framework in educational psychology for optimizing learning outcomes, reveals how the allocation of human cognitive resources influences learning efficiency. CLT divides cognitive load into three dimensions—intrinsic load, extraneous load, and germane load—and emphasizes that learning effectiveness depends on how learners manage cognitive load to maximize the use of their limited cognitive resources. Educators can promote deep learning and the formation of long-term memory by employing effective instructional strategies to reduce unnecessary cognitive load.
Meanwhile, Embodied Cognition theory highlights the positive role of bodily actions in learning, challenging the traditional brain-centered perspective of education. Recent studies suggest that integrating CLT with embodied cognition theory not only optimizes cognitive load but also enhances academic performance. Particularly in digital and hybrid learning contexts, technologies such as Augmented Reality (AR) and Virtual Reality (VR) have demonstrated potential in reducing cognitive load and offering innovative approaches to instructional design.
Against this backdrop, educators and researchers are called to re-examine the critical role of the body in learning, promote interdisciplinary integration, and lay the groundwork for innovative educational models of the future.
2. Cognitive Load Theory: Theoretical Foundations and Applications
CLT originates from research on working memory, highlighting its limited capacity and underscoring the importance of designing instruction that accounts for these constraints to avoid cognitive overload. Early studies demonstrated that working memory not only has storage limitations but must also engage in processing functions; once its capacity is exceeded, information cannot be effectively integrated, leading to reduced learning outcomes. However, by organizing information into single cognitive units (chunking), learners are able to process information more efficiently.
Since the introduction of CLT, many strategies have been developed to mitigate cognitive overload. Yet, traditional models have not sufficiently accounted for the dynamic changes in cognitive load, including—but not limited to—the influences of motivation, prior knowledge, and external distractions. Integrating embodied cognition with CLT provides a more comprehensive framework, as it considers how body–environment interactions can support working memory. This integration offers a more holistic theoretical model for optimizing learning outcomes and, in turn, enhancing instructional effectiveness.
3. Embodied Cognition: Extending Learning Beyond the Brain
Embodied cognition challenges traditional conceptions of learning by emphasizing the crucial role of the body and its interactions with the environment in cognitive processes. It posits that cognition is not confined to neural activity alone but emerges from the synergistic interplay among the brain, body, and environment. Gestures, object manipulation, and whole-body movements are not merely external expressions of thought; they are essential mechanisms for perceiving, processing, and applying information.
By integrating bodily movements with learning content, embodied learning enhances emotional engagement and multisensory interaction, thereby increasing learning motivation and attention. The theoretical foundations of embodied cognition draw upon ecological psychology, situated cognition, and dynamic cognition, all of which highlight the embeddedness of cognition within physical and social environments. These perspectives provide a solid theoretical basis for embodied learning and its role in optimizing educational practices.
4. Empirical Evidence of Embodied Cognition in Learning
Empirical studies have shown that embodied cognition can effectively reduce extraneous cognitive load through bodily actions, while also promoting abstract reasoning and enhancing germane load. By incorporating gestures, object manipulation, and whole-body movements, educators can provide cognitive scaffolding that helps learners better understand and retain abstract concepts.
Gestures as cognitive scaffolds. Gestures serve as powerful tools for concrete mental representation, enabling learners to process and communicate abstract concepts. For example, in mathematics learning, students who use gestures to represent graph relationships demonstrate stronger comprehension and memory of concepts compared to those who rely solely on verbal explanations. In physics education, using gestures to simulate object trajectories facilitates deeper understanding of motion principles and mechanics.
Object manipulation in STEM education. Manipulating physical objects bridges the gap between theoretical knowledge and practical understanding. In chemistry learning, assembling molecular models provides a more intuitive grasp of chemical bond formation compared to relying solely on diagrams. Emerging technologies such as Virtual Reality (VR) and Augmented Reality (AR) also offer innovative pathways for embodied learning, enabling immersive experiences that help students internalize complex concepts.
Whole-body movement. Whole-body movement has significant effects on cognition, behavior, and emotion. In early literacy education, children who act out word meanings or storylines in the classroom exhibit superior vocabulary retention and comprehension. Research further shows that embedding learning tasks into physical activities can substantially improve young children’s mathematical skills and foreign language acquisition—particularly benefiting learners who struggle in traditional instructional settings.
Figure 1. Empirical studies on embodied cognition and cognitive load theory in the field of education
5. The Synergistic Integration Model of Embodied Cognition and Cognitive Load
In research combining Embodied Cognition with Cognitive Load Theory (CLT), the Relevance–Integration model represents an important breakthrough. This model categorizes embodied actions (e.g., gestures, object manipulation, or whole-body movements) according to their relevance to the learning task and the degree to which they are integrated with cognitive processes. When bodily actions are highly relevant and closely synchronized with instructional content, they are most effective in reducing extraneous load and enhancing germane load. In contrast, low-relevance or poorly integrated movements may increase ineffective cognitive demands.
Based on this classification, researchers can more precisely evaluate how to design embodied instructional activities aligned with CLT principles, thereby maximizing learning outcomes while balancing cognitive demands and bodily involvement. However, this integration also faces challenges, including cultural and contextual adaptability, load calibration (e.g., avoiding excessive bodily activity during tasks with already high intrinsic load), and large-scale implementation. To address these challenges, multidisciplinary collaboration and advanced measurement techniques—such as functional near-infrared spectroscopy (fNIRS) and AI-based analysis—should be employed to continuously refine assessment methods and intervention strategies (Fig. 2).
Ultimately, such efforts aim to enable more learners across diverse educational settings to benefit from this approach and to realize a truly holistic learning experience centered on the interaction of body, environment, and cognition.
Figure 2. Integrated models of embodied cognition and cognitive load in education
(a) Future challenges for applications of embodied cognition;
(b) The Relevance–Integration model;
(c) The role of the embodied cognition–cognitive load synergistic framework in educational practice
6. Author Contributions
Both the first author and the corresponding author of this paper are Professor Liye Zou. Other key contributors include Zhihao Zhang (Ph.D. candidate at Shenzhen University), Dr. Myrto Mavilidi (Research Fellow, University of Wollongong, Australia), Yanxia Chen (Ph.D. candidate at Shanghai Jiao Tong University), Dr. Fabian Herold (University of Potsdam, Germany), as well as Professor Kim Ouwehand and Professor Fred Paas (Erasmus University Rotterdam, the Netherlands).
In addition, Zijun Liu provided support for the illustration of the paper, while Dr. Benjamin Tari and Professor Justin Haegele offered valuable suggestions to improve the readability of the manuscript.
7. Funding
This research was supported by the following grants:
lMOE Humanities and Social Sciences Research Planning Fund (23YJA880093)
lChina Postdoctoral Science Foundation (2022M711174)
lScience and Technology Innovation Project, General Administration of Sport of China (23KJCX057)
lNational Center for Mental Health and Prevention of Mental Disorders / China Education Development Foundation (Z014)
lMajor Project of the 14th Five-Year Plan for Educational Science, Shenzhen (ZDZB22014)
lKey Technology Research Project, Shenzhen Science and Technology Innovation Commission (202307313000096)
lExcellence Major Project, Shenzhen University (ZYZD2305)
