Students’ Perceptions of the Utilization of Artificial Intelligence in the Learning Process
DOI:
https://doi.org/10.58258/jime.v12i2.10354Keywords:
Student perception, Economic education, Artificial Intelligence Utilization, Learning Process.Abstract
This study aims to explore the perceptions of Economic Education students at Muhammadiyah University of Sampit regarding the utilization of artificial intelligence (AI) in the learning process. The integration of AI in higher education has become a global phenomenon that is transforming learning paradigms; however, understanding of how students evaluate and interpret this technology remains limited, particularly within the context of Economic Education in Indonesia. This study involved 15 students selected through purposive sampling and employed a descriptive qualitative approach grounded in the Technology Acceptance Model (TAM). Data were collected through semi-structured interviews and analyzed thematically using NVivo 12 Pro.The findings reveal that students perceive AI as enhancing learning effectiveness, being easy to use, and fostering academic motivation and independence. Four major themes emerged: perceived usefulness, perceived ease of use, attitude toward using, and behavioral intention to use. The acceptance of AI was found to encompass not only technological dimensions but also social-emotional aspects. This study reinforces the relevance of TAM within the Indonesian higher education context and provides implications for developing ethical, creative, and adaptive technology-based learning policies aligned with students’ needs in the digital era.References
Aldraiweesh, A. A., & Alturki, U. (2025). The Influence of Social Support Theory on AI Acceptance: Examining Educational Support and Perceived Usefulness Using SEM Analysis. IEEE Access, 13(January), 18366–18385. https://doi.org/10.1109/ACCESS.2025.3534099
Balay-odao, E. M., Omirzakova, D., Bolla, S. R., Almazan, J. U., & Cruz, J. P. (2025). Health professions students’ perceptions of artificial intelligence and its integration to health professions education and healthcare: a thematic analysis. AI and Society, 40(3), 1863–1873. https://doi.org/10.1007/s00146-024-01957-5
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly: Management Information Systems, 13(3), 319–339. https://doi.org/10.2307/249008
Fawaz, M., El-Malti, W., Alreshidi, S. M., & Kavuran, E. (2025). Exploring Health Sciences Students’ Perspectives on Using Generative Artificial Intelligence in Higher Education: A Qualitative Study. Nursing and Health Sciences, 27(1). https://doi.org/10.1111/nhs.70030
Hasija, A., & Esper, T. L. (2022). In artificial intelligence (AI) we trust: A qualitative investigation of AI technology acceptance. Journal of Business Logistics, 43(3), 388–412. https://doi.org/10.1111/jbl.12301
Labrague, L. J., & Al Harrasi, M. (2025). Nursing students’ perceptions of artificial intelligence (AI) using the technology acceptance model: A systematic review. Teaching and Learning in Nursing, 20(3), 274–282. https://doi.org/10.1016/j.teln.2025.02.032
Lee, J. W. Y., Tan, J. Y., & Bello, F. (2025). Technology Acceptance Model in Medical Education: Systematic Review. JMIR Medical Education, 11, 1–17. https://doi.org/10.2196/67873
Marrone, R., Zamecnik, A., Joksimovic, S., Johnson, J., & De Laat, M. (2025). Understanding Student Perceptions of Artificial Intelligence as a Teammate. Technology, Knowledge and Learning, 30(3), 1847–1869. https://doi.org/10.1007/s10758-024-09780-z
Mostafa, A. El, Rachid, J., & Fatima, S. (2024). The Integration Of Artificial Intelligence In Regional Centers For Education And Training Professions (Crmefs): A Qualitative Exploratory Study Of The Technology Acceptance Model (Tam). IOSR Journal of Business and Management (IOSR-JBM), 26(4), 21–34. https://doi.org/10.9790/487X-2604012134
Nezhad, M. S., Abdi, A., & Ahmadi, M. (2025). Exploring the experiences and perceptions of nursing students in utilizing artificial intelligence: a descriptive phenomenological study. BMC Nursing, 24(1), 740. https://doi.org/10.1186/s12912-025-03392-3
Pisica, A. L., & Zaharia, R. M. (2024). Implementing AI in Higher Education - Qualitative Inquiry on International Stuents’ Perspectives (pp. 388–394).
Rosli, M. S., Saleh, N. S., Md. Ali, A., Abu Bakar, S., & Mohd Tahir, L. (2022). A Systematic Review of the Technology Acceptance Model for the Sustainability of Higher Education during the COVID-19 Pandemic and Identified Research Gaps. Sustainability (Switzerland), 14(18). https://doi.org/10.3390/su141811389
Sari, W. D. (2025). Exploring Teacher Perceptions of Deep Learning for Professional Development: A Technology Acceptance Model Approach. Jurnal Ilmu Pendidikan (JIP), 31(1), 115–124. https://journals.um.ac.id/index.php/jip/article/view/78%0Ahttps://journals.um.ac.id/index.php/jip/article/download/78/62
Slimi, Z., Benayoune, A., & Alemu, A. E. (2025). Students’ Perceptions of Artificial Intelligence Integration in Higher Education. European Journal of Educational Research, 14(1), 249–265. https://scholar.archive.org/work/fxr3w63xnzgx3hpxvzuotnab44/access/wayback/https://pdf.eu-jer.com/EU-JER_13_2_573.pdf
Verboom, A. D. P. R., Pais, L., Zijlstra, F. R. H., Oswald, F. L., & Santos, N. R. dos. (2025). Perceptions of artificial intelligence in academic teaching and research: a qualitative study from AI experts and professors’ perspectives. International Journal of Educational Technology in Higher Education, 22(1). https://doi.org/10.1186/s41239-025-00546-w
Wicaksono, A., Barunastra, F. I., Suhari, M. C. J. G., & Jingga, F. (2024). Students Level of Trust in the Use of AI Chatbots in Higher Education: A Quantitative Analysis Adopting Technology Acceptance Model. Proceedings of International Conference on Contemporary Computing and Informatics, IC3I 2024, 305–310. https://doi.org/10.1109/IC3I61595.2024.10829196
Xu, X., Su, Y., Zhang, Y., Wu, Y., & Xu, X. (2024). Understanding learners’ perceptions of ChatGPT: A thematic analysis of peer interviews among undergraduates and postgraduates in China. Heliyon, 10(4), e26239. https://doi.org/10.1016/j.heliyon.2024.e26239
Zakour, S. Ben, & Selmi, N. (2025). Artificial Intelligence in Education: A Thematic and Descriptive Analysis. Pakistan Journal of Life and Social Sciences (PJLSS), 23(1), 7186–7193. https://doi.org/10.57239/pjlss-2025-23.1.00559
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