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Understanding Continuance Intention of Generative AI in Education: An ECM-Based Study for Sustainable Learning Engagement

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  • Young Mee Jung

    (Department of Aviation Tourism, Hanseo University, Seosan-si 31962, Republic of Korea)

  • Hyeon Jo

    (HJ Institute of Technology and Management, Seoul 06134, Republic of Korea)

Abstract

Rapid advancements in artificial intelligence (AI) have led to the emergence of generative AI models like generative AI that produce human-like responses and support a wide range of applications. This study explores the key factors influencing the continuance intention of generative AI among university students, drawing on established theoretical frameworks including the expectancy confirmation model and technology acceptance model. Using data collected from 282 users, structural equation modeling was applied to examine relationships among knowledge application, perceived intelligence, perceived usefulness, confirmation, satisfaction, AI configuration, social influence, and continuance intention. The results show that both knowledge application and perceived intelligence significantly influence perceived usefulness and confirmation. Perceived usefulness was found to positively affect both satisfaction and continuance intention, while confirmation strongly influenced both perceived usefulness and satisfaction. Satisfaction emerged as a key predictor of continuance intention, as did social influence. However, AI configuration did not significantly impact continuance intention. The model explained 64.1% of the variance in continuance intention. These findings offer meaningful insights for improving the design, implementation, and promotion of AI-based language tools in educational settings.

Suggested Citation

  • Young Mee Jung & Hyeon Jo, 2025. "Understanding Continuance Intention of Generative AI in Education: An ECM-Based Study for Sustainable Learning Engagement," Sustainability, MDPI, vol. 17(13), pages 1-21, July.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:13:p:6082-:d:1693476
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    1. Hanjun Su & Nur Azlina Mohamed Mokmin, 2024. "Unveiling the Canvas: Sustainable Integration of AI in Visual Art Education," Sustainability, MDPI, vol. 16(17), pages 1-13, September.
    2. Farrukh Rafiq & Nikhil Dogra & Mohd Adil & Jei-Zheng Wu, 2022. "Examining Consumer’s Intention to Adopt AI-Chatbots in Tourism Using Partial Least Squares Structural Equation Modeling Method," Mathematics, MDPI, vol. 10(13), pages 1-15, June.
    3. Luis Alberto Holgado-Apaza & Nelly Jacqueline Ulloa-Gallardo & Ruth Nataly Aragon-Navarrete & Raidith Riva-Ruiz & Naomi Karina Odagawa-Aragon & Danger David Castellon-Apaza & Edgar E. Carpio-Vargas & , 2024. "The Exploration of Predictors for Peruvian Teachers’ Life Satisfaction through an Ensemble of Feature Selection Methods and Machine Learning," Sustainability, MDPI, vol. 16(17), pages 1-28, August.
    4. Stephen Gourlay, 2006. "Conceptualizing Knowledge Creation: A Critique of Nonaka's Theory," Journal of Management Studies, Wiley Blackwell, vol. 43(7), pages 1415-1436, November.
    5. Wynne W. Chin & Barbara L. Marcolin & Peter R. Newsted, 2003. "A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic-Mail Emotion/Adoption Study," Information Systems Research, INFORMS, vol. 14(2), pages 189-217, June.
    6. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    7. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    8. Tianqi Lin & Jianyang Zhang & Bin Xiong, 2025. "Effects of Technology Perceptions, Teacher Beliefs, and AI Literacy on AI Technology Adoption in Sustainable Mathematics Education," Sustainability, MDPI, vol. 17(8), pages 1-35, April.
    9. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    10. Eva A. M. van Dis & Johan Bollen & Willem Zuidema & Robert van Rooij & Claudi L. Bockting, 2023. "ChatGPT: five priorities for research," Nature, Nature, vol. 614(7947), pages 224-226, February.
    11. Ibrahim A. Elshaer & Sameer M. AlNajdi & Mostafa A. Salem, 2025. "Sustainable AI Solutions for Empowering Visually Impaired Students: The Role of Assistive Technologies in Academic Success," Sustainability, MDPI, vol. 17(12), pages 1-18, June.
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