Fostering Sustainable Learning via Embodied Intelligence: The E3-HOT Framework for Higher-Order Thinking in the AI Era

Artificial intelligence (AI) can help students accelerate assignment completion, but it may also foster cognitive outsourcing and learning detached from authentic contexts. This paper presents E3-HOT, a conceptual framework that leverages embodied intelligence to sustain learners’ cognitive agency and higher-order thinking for sustainable learning, aligned with SDG 4 (Sustainable Development Goal 4) and its emphasis on inclusive and equitable quality education and lifelong learning. Using an iterative conceptual synthesis, we distill three embodied pathways—situational embedding, embodied participation, and cognitive creation—and translate them into a practical system design with a three-module E3 core. It includes a virtual–real integrated learning environment for rich scenarios, embodied interaction for action and sensing, and an intelligent core that provides bounded and teacher-controlled support. To facilitate equitable adoption across resource-diverse settings, we specify multi-fidelity enactment options and an auditable set of evidence artifacts for subsequent expert review and future validation studies. We further provide an illustrative university human–AI design project that outlines a week-by-week workflow and corresponding evidence plan, presented as a worked example rather than a report of an implemented study. E3-HOT offers a traceable design-and-evidence blueprint without claiming measured learning gains.

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Publication Details

Journal
Sustainability
Published
2026-04-02
DOI
https://doi.org/10.3390/su18073469
Primary Topic
Embodied and Extended Cognition
Type
article
Field-Weighted Citation Impact
0.00
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article

Fostering Sustainable Learning via Embodied Intelligence: The E3-HOT Framework for Higher-Order Thinking in the AI Era

Hanzi Zhu, Xin Jiang, Xiaolei Zhang, Huiying Xu et al.
Sustainability
Embodied and Extended Cognition
article

Fostering Sustainable Learning via Embodied Intelligence: The E3-HOT Framework for Higher-Order Thinking in the AI Era

Hanzi Zhu, Xin Jiang, Xiaolei Zhang, Huiying Xu, Zhendong Chen, Xinzhong Zhu, Deang Su
article en

Abstract

Artificial intelligence (AI) can help students accelerate assignment completion, but it may also foster cognitive outsourcing and learning detached from authentic contexts. This paper presents E3-HOT, a conceptual framework that leverages embodied intelligence to sustain learners’ cognitive agency and higher-order thinking for sustainable learning, aligned with SDG 4 (Sustainable Development Goal 4) and its emphasis on inclusive and equitable quality education and lifelong learning. Using an iterative conceptual synthesis, we distill three embodied pathways—situational embedding, embodied participation, and cognitive creation—and translate them into a practical system design with a three-module E3 core. It includes a virtual–real integrated learning environment for rich scenarios, embodied interaction for action and sensing, and an intelligent core that provides bounded and teacher-controlled support. To facilitate equitable adoption across resource-diverse settings, we specify multi-fidelity enactment options and an auditable set of evidence artifacts for subsequent expert review and future validation studies. We further provide an illustrative university human–AI design project that outlines a week-by-week workflow and corresponding evidence plan, presented as a worked example rather than a report of an implemented study. E3-HOT offers a traceable design-and-evidence blueprint without claiming measured learning gains.

SustainabilityVol. 18(7)
Zhejiang Normal University (CN), Hangzhou Normal University (CN)
Quality Education
Openalex Percentile: Top 27%
Embodied and Extended Cognition
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