Citation:

Indah Oktari Wijayanti, Fenny Marietza, Nila Aprila, Nikmah. "Students Trust, Acceptance, and Ethical Perception of Chatbox AI in Academic Activities: Evidence from Accounting Students at the University of Bengkulu" International Research Journal of Economics and Management Studies, Vol. 4, No. 12, pp. 149-156, 2025. Crossref. http://doi.org/10.56472/25835238/IRJEMS-V4I12P118

Abstract:

The rapid growth of Artificial Intelligence (AI) in higher education has introduced chatbot applications as intelligent learning support tools; however, students’ acceptance of this technology is influenced not only by technological functionality but also by ethical and psychological considerations. This study examines the relationship between ethical perception, trust, and acceptance of chatbot AI among accounting students at the University of Bengkulu. Data were collected from 200 valid respondents using purposive sampling and analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) with SmartPLS. The results reveal that ethical perception significantly influences trust and acceptance, while trust also has a significant effect on acceptance. Furthermore, trust partially mediates the relationship between ethical perception and acceptance, indicating that students’ ethical comfort enhances trust, which subsequently strengthens their willingness to adopt chatbot AI in academic activities. The findings confirm the integration of the Technology Acceptance Model (TAM), Trust Theory, and Ethical Decision-Making Theory, emphasizing that ethical and psychological aspects are essential determinants of AI adoption in education. This study provides theoretical contributions to AI adoption literature and practical implications for universities to design transparent, ethical, and trustworthy AI-based academic systems.

References:

[1] Abdullah, F., Ward, R., & Ahmed, E. (2022). Investigating the adoption of AI-based chatbots in higher education: The role of usefulness, ease of use, and user trust. Computers & Education, 185, 104522.
[2] Bandara, R., Fernando, M., & Akter, S. (2022). Managing AI-driven service failures and recovery: The role of perceived fairness and trust. Journal of Service Management, 33(4), 553–573.
[3] Bhattacherjee, A. (2002). Individual trust in online firms: Scale development and initial test. Journal of Management Information Systems, 19(1), 211–241.
[4] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
[5] Dwivedi, Y. K., Hughes, L., Baabdullah, A. M., Ribeiro-Navarrete, S., Giannakis, M., Al-Debei, M. M., & Wirtz, J. (2023). Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and research agenda. International Journal of Information Management, 71, 102642.
[6] Floridi, L., Cowls, J., King, T. C., & Taddeo, M. (2018). How do you design AI governance? Ethical AI principles in practice. Philosophy & Technology, 31(4), 1–25.
[7] Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90.
[8] Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (3rd ed.). SAGE.
[9] McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce. Information Systems Research, 13(3), 334–359.
[10] https://irjems.org/About.htmlOkonkwo, C. W., & Ade-Ibijola, A. (2021). Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2, 100033.
[11] Siau, K., & Wang, W. (2018). Building trust in artificial intelligence, machine learning, and robotics. ACM SIGMIS Database, 49(4), 38–58.
[12] Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
[13] Wirtz, J., Patterson, P., Kunz, W., Gruber, T., Lu, V., Paluch, S., & Martins, A. (2018). Brave new world: Service robots in the frontline. Journal of Service Management, 29(5), 907–931.
[14] Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(1), 1–27.
[15] Zhao, Y., Zhao, J., & Tay, B. (2022). Ethical AI in education: A review of policies, challenges, and future directions. Computers & Education, 176, 104366.

Keywords:

Chatbot AI, Ethical Perception, Trust, Technology Acceptance, Higher Education, Accounting Students.