Key Factors Influencing Design Learners’ Behavioral Intention in Human-AI Collaboration Within the Educational Metaverse

钥匙(锁) 虚拟实境 知识管理 心理学 计算机科学 人机交互 虚拟现实 计算机安全
作者
R. Wu,Lin Gao,Jiaxin Li,Qianghong Huang,Younghwan Pan
出处
期刊:Sustainability [Multidisciplinary Digital Publishing Institute]
卷期号:16 (22): 9942-9942
标识
DOI:10.3390/su16229942
摘要

This study investigates the key factors which influence design learners’ behavioral intention to collaborate with AI in the educational metaverse (EMH-AIc). Engaging design learners in EMH-AIc enhances learning efficiency, personalizes learning experiences, and supports equitable and sustainable design education. However, limited research has focused on these influencing factors, leading to a lack of theoretical grounding for user behavior in this context. Drawing on social cognitive theory (SCT), this study constructs a three-dimensional theoretical model comprising the external environment, individual cognition, and behavior, validated within an EMH-AIc setting. By using Spatial.io’s Apache Art Studio as the experimental platform and analyzing data from 533 design learners with SPSS 27.0, SmartPLS 4.0, and partial least squares structural equation modeling (PLS-SEM), this study identifies those rewards, teacher support, and facilitating conditions in the external environment, with self-efficacy, outcome expectation, and trust in cognition also significantly influencing behavioral intention. Additionally, individual cognition mediates the relationship between the external environment and behavioral intention. This study not only extends SCT application within the educational metaverse but also provides actionable insights for optimizing design learning experiences, contributing to the sustainable development of design education.
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