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Students' mindset to adopt AI chatbots for effectiveness of online learning in higher education

Author

Listed:
  • Muhammad Khalilur Rahman

    (Universiti Malaysia Kelantan)

  • Noor Azizi Ismail

    (Universiti Malaysia Kelantan)

  • Md Arafat Hossain

    (Southeast University)

  • Mohammad Shahadat Hossen

    (Universiti Sultan Zainal Abidin)

Abstract

The rapid incorporation of Artificial Intelligence (AI) technologies into higher education is shifting the focus toward understanding students’ perspectives and factors affecting the adoption of AI chatbots to maximize their use in online and virtual educational environments. This study fills an important gap in the literature by examining direct and mediated relationships of key constructs such as AI perceived usefulness, AI perceived ease of use, and AI technical competency toward AI chatbot usage. This study aims to investigate students’ mindsets regarding adopting AI chatbots for the effectiveness of online learning in higher education. Data were collected from 429 university students and analyzed using the partial least squares-based structural equation modeling (PLS-SEM) technique. The results revealed that perceived usefulness (PU), perceived ease of use (PEU), and tech competency (TC) have a significant impact on AI capability. Subjective norm (SN) has no significant impact on AI chatbot capability. The capability of AI chatbots significantly influences the adoption of AI chatbots for learning effectiveness. The findings indicated that AI chatbot capability mediates the effect of PU, PEU, and TC on the adoption of AI chatbots; however, there is no mediating effect in the relationship between SN and AI chatbot capability. Facilitating conditions moderate the effect of PU and TC on AI chatbot capability. This research addresses a new insight into AI chatbot adoption within the context of higher education, particularly demonstrating the mediating and moderating function of AI chatbot capability and adoption on students’ PU, PEU, and understanding of tech-competent concepts.

Suggested Citation

  • Muhammad Khalilur Rahman & Noor Azizi Ismail & Md Arafat Hossain & Mohammad Shahadat Hossen, 2025. "Students' mindset to adopt AI chatbots for effectiveness of online learning in higher education," Future Business Journal, Springer, vol. 11(1), pages 1-25, December.
  • Handle: RePEc:spr:futbus:v:11:y:2025:i:1:d:10.1186_s43093-025-00459-0
    DOI: 10.1186/s43093-025-00459-0
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    References listed on IDEAS

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    1. 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.
    2. Eun-Jung Kim & Jinkyung Jenny Kim & Sang-Ho Han, 2021. "Understanding Student Acceptance of Online Learning Systems in Higher Education: Application of Social Psychology Theories with Consideration of User Innovativeness," Sustainability, MDPI, vol. 13(2), pages 1-14, January.
    3. Yu Chen & Scott Jensen & Leslie J. Albert & Sambhav Gupta & Terri Lee, 2023. "Artificial Intelligence (AI) Student Assistants in the Classroom: Designing Chatbots to Support Student Success," Information Systems Frontiers, Springer, vol. 25(1), pages 161-182, February.
    4. Pathak, Kanishka & Prakash, Gyan & Samadhiya, Ashutosh & Kumar, Anil & Luthra, Sunil, 2025. "Impact of Gen-AI chatbots on consumer services experiences and behaviors: Focusing on the sensation of awe and usage intentions through a cybernetic lens," Journal of Retailing and Consumer Services, Elsevier, vol. 82(C).
    5. Shehawy, Yasser Moustafa & Faisal Ali Khan, Syed Md & Ali M Khalufi, Nasser & Abdullah, Riyaz Sheikh, 2025. "Customer adoption of robot: Synergizing customer acceptance of robot-assisted retail technologies," Journal of Retailing and Consumer Services, Elsevier, vol. 82(C).
    6. Muhammad Khalilur Rahman & Md Abu Issa Gazi & Miraj Ahmed Bhuiyan & Md Atikur Rahaman, 2021. "Effect of Covid-19 pandemic on tourist travel risk and management perceptions," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-18, September.
    7. Marko Sarstedt & Yide Liu, 2024. "Advanced marketing analytics using partial least squares structural equation modeling (PLS-SEM)," Journal of Marketing Analytics, Palgrave Macmillan, vol. 12(1), pages 1-5, March.
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