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<p>This quasi-experimental study integrates embodied cognition, constructionism, and culturally sustaining teaching to address the three-dimensional needs of cognitive development, practical competence, and cultural understanding, operationalized through the Child-Centered Guided Scaffolding AI Framework (CGS-AI). Based on this framework, we developed an AI-supported Intelligent Learning Companion called “Little Bean Companion,” which guides elementary students in learning about traditional cultural architecture and building miniature physical architectural models. The system integrates Vygotsky’s dynamic scaffolding support, Constructionism, and child-centered interaction design principles. A total of 38 fourth-grade students participated in this quasi-experimental study designed to quantitatively evaluate the effectiveness of our developed system. Based on existing class arrangements, students were assigned to an experimental group (<i>n</i> = 20) and a control group (<i>n</i> = 18). The experimental group used the Intelligent Learning Companion for architecture-themed learning over a one-month period totaling 7 class hours, while the control group received traditional teacher-led instruction. Results showed that the experimental group performed significantly better than the control group in the post-test of the Course Knowledge Test (Adj. M = 88.32 vs. 80.59, <i>p</i>&lt;.001), with a particularly pronounced difference in multiple-choice questions requiring knowledge transfer and application. In the Architectural Model Evaluation, the experimental group not only had a higher median score (92 vs. 86) but also exhibited a “high-score clustering” phenomenon. Structural analysis of learning motivation revealed that while all four dimensions showed improvement, the effect size for mastery-goal orientation exceeded that of performance-goal orientation, perceived enjoyment, and self-efficacy. These students were able to externalize abstract knowledge principles into concrete physical operations when constructing miniature physical architectural models, and through heuristic dialogue with the Intelligent Learning Companion, they established deep connections between cultural concepts and engineering practice. The study demonstrates that when AI transforms from an “information tutor” to a “constructionist partner,” it can effectively promote children’s embodied learning, cultural understanding, and learning motivation.</p>

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Beyond tutoring: a child-centered AI framework for embodied construction in culturally-grounded steam education

  • 期刊论文

  • 发表日期：

    2026年5月16日

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  • Wuwen Zhang,
  • Haoyuan Yu,
  • Mengyi Xia,
  • Min Yang,
  • Jinsheng Ja

摘要

This quasi-experimental study integrates embodied cognition, constructionism, and culturally sustaining teaching to address the three-dimensional needs of cognitive development, practical competence, and cultural understanding, operationalized through the Child-Centered Guided Scaffolding AI Framework (CGS-AI). Based on this framework, we developed an AI-supported Intelligent Learning Companion called “Little Bean Companion,” which guides elementary students in learning about traditional cultural architecture and building miniature physical architectural models. The system integrates Vygotsky’s dynamic scaffolding support, Constructionism, and child-centered interaction design principles. A total of 38 fourth-grade students participated in this quasi-experimental study designed to quantitatively evaluate the effectiveness of our developed system. Based on existing class arrangements, students were assigned to an experimental group (n = 20) and a control group (n = 18). The experimental group used the Intelligent Learning Companion for architecture-themed learning over a one-month period totaling 7 class hours, while the control group received traditional teacher-led instruction. Results showed that the experimental group performed significantly better than the control group in the post-test of the Course Knowledge Test (Adj. M = 88.32 vs. 80.59, p<.001), with a particularly pronounced difference in multiple-choice questions requiring knowledge transfer and application. In the Architectural Model Evaluation, the experimental group not only had a higher median score (92 vs. 86) but also exhibited a “high-score clustering” phenomenon. Structural analysis of learning motivation revealed that while all four dimensions showed improvement, the effect size for mastery-goal orientation exceeded that of performance-goal orientation, perceived enjoyment, and self-efficacy. These students were able to externalize abstract knowledge principles into concrete physical operations when constructing miniature physical architectural models, and through heuristic dialogue with the Intelligent Learning Companion, they established deep connections between cultural concepts and engineering practice. The study demonstrates that when AI transforms from an “information tutor” to a “constructionist partner,” it can effectively promote children’s embodied learning, cultural understanding, and learning motivation.