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Impact of intelligent learning assistants on creativity of university students: a self-determination theory perspective

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  • Harman Preet Singh

    (University of Ha’il)

  • Azira Ab Aziz

    (University of Ha’il)

Abstract

In recent times, Artificial Intelligence (AI) has been increasingly adopted in the educational domain. Intelligent learning assistants (ILAs) have emerged as a transformative AI tool enabling autonomous, personalized, and collaborative learning among students and enhancing their learning ability. However, prior research has not examined the impact of ILAs on enhancing student creativity. This research uses self-determination theory (SDT) as a theoretical lens to examine the impact of ILAs-enabled autonomy, competence, and relatedness on student creativity. The empirical analysis of 304 surveys of university students in Saudi Arabia indicates that ILAs-enabled autonomy, competence, and relatedness positively impact students’ creativity. This study enriches the literature by informing the potential of ILAs-enabled autonomy, competence, and relatedness to enhance student creativity. The study contributes to the theory by extending applications of SDT in the AI-based educational domain. The study has important implications for higher education institutions to leverage AI tools (like ILAs) to enhance student creativity. Policymakers can utilize the study findings to promote an enabling environment for effectively utilizing AI tools (like ILAs) in the education sector to increase student creativity. Nonetheless, meticulous implementation of ILAs is essential to prevent inadvertent infringement on student autonomy, competence, or relational engagement.

Suggested Citation

  • Harman Preet Singh & Azira Ab Aziz, 2025. "Impact of intelligent learning assistants on creativity of university students: a self-determination theory perspective," Future Business Journal, Springer, vol. 11(1), pages 1-18, December.
    • Handle: RePEc:spr:futbus:v:11:y:2025:i:1:d:10.1186_s43093-025-00544-4
    DOI: 10.1186/s43093-025-00544-4
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    References listed on IDEAS

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    1. Anthony Zeimbekakis & Elizabeth D. Schifano & Jun Yan, 2024. "On Misuses of the Kolmogorov–Smirnov Test for One-Sample Goodness-of-Fit," The American Statistician, Taylor & Francis Journals, vol. 78(4), pages 481-487, October.
    2. Harman Preet Singh & Hilal Nafil Alhulail, 2023. "Information Technology Governance and Corporate Boards’ Relationship with Companies’ Performance and Earnings Management: A Longitudinal Approach," Sustainability, MDPI, vol. 15(8), pages 1-24, April.
    3. Rouye Pan & Zihan Qin & Lan Zhang & Ligao Lou & Huiju Yu & Junfeng Yang, 2023. "Exploring the impact of intelligent learning tools on students’ independent learning abilities: a PLS-SEM analysis of grade 6 students in China," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-11, December.
    4. Yaquelin Verenice Pantoja-Pacheco & Javier Yáñez-Mendiola, 2024. "Method for the Statistical Analysis of the Signals Generated by an Acquisition Card for Pulse Measurement," Mathematics, MDPI, vol. 12(6), pages 1-24, March.
    5. Harman Preet Singh & Ajay Singh & Fakhre Alam & Vikas Agrawal, 2022. "Impact of Sustainable Development Goals on Economic Growth in Saudi Arabia: Role of Education and Training," Sustainability, MDPI, vol. 14(21), pages 1-25, October.
    6. Ajay Singh & Harman Preet Singh & Fakhre Alam & Vikas Agrawal, 2022. "Role of Education, Training, and E-Learning in Sustainable Employment Generation and Social Empowerment in Saudi Arabia," Sustainability, MDPI, vol. 14(14), pages 1-25, July.
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