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

Author

Listed:
  • Ronghui Wu

    (Department of Smart Experience Design, Kookmin University, Seoul 02707, Republic of Korea)

  • Lin Gao

    (Department of Animation, Zhongyuan University of Technology, Zhengzhou 450007, China)

  • Jiaxin Li

    (Department of Animation, Zhongyuan University of Technology, Zhengzhou 450007, China)

  • Qianghong Huang

    (Department of Smart Experience Design, Kookmin University, Seoul 02707, Republic of Korea)

  • Younghwan Pan

    (Department of Smart Experience Design, Kookmin University, Seoul 02707, Republic of Korea)

Abstract

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.

Suggested Citation

  • Ronghui Wu & Lin Gao & Jiaxin Li & Qianghong Huang & Younghwan Pan, 2024. "Key Factors Influencing Design Learners’ Behavioral Intention in Human-AI Collaboration Within the Educational Metaverse," Sustainability, MDPI, vol. 16(22), pages 1-30, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:9942-:d:1521110
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    References listed on IDEAS

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    1. Bandura, Albert, 1991. "Social cognitive theory of self-regulation," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 248-287, December.
    2. Gaofeng Wang & Changhoon Shin, 2022. "Influencing Factors of Usage Intention of Metaverse Education Application Platform: Empirical Evidence Based on PPM and TAM Models," Sustainability, MDPI, vol. 14(24), pages 1-21, December.
    3. Mohammed Abdullatif Almulla & Waleed Mugahed Al-Rahmi, 2023. "Integrated Social Cognitive Theory with Learning Input Factors: The Effects of Problem-Solving Skills and Critical Thinking Skills on Learning Performance Sustainability," Sustainability, MDPI, vol. 15(5), pages 1-26, February.
    4. Clay M. Voorhees & Michael K. Brady & Roger Calantone & Edward Ramirez, 2016. "Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies," Journal of the Academy of Marketing Science, Springer, vol. 44(1), pages 119-134, January.
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