Students’ Perceptions of Artificial Intelligence in Tax Learning
DOI:
https://doi.org/10.52158/jaa.v4i2.1479Keywords:
artificial intelligence, student perception, tax learning, higher education, qualitative researchAbstract
The use of Artificial Intelligence (AI) in higher education has increased rapidly, with many students using AI-based applications independently to support learning. In regulation-based subjects such as taxation, this practice raises concerns related to learning accuracy, relevance to local regulations, and ethical use. This study aims to examine students’ perceptions of AI use in tax learning. A qualitative descriptive approach was employed involving undergraduate accounting and taxation students at the University of Lampung and the Lampung State Polytechnic who had taken taxation courses and used AI as a learning tool. Using purposive sampling, data were collected through an online questionnaire, resulting in 143 valid responses from an estimated eligible population of 809 students. The questionnaire included Likert-scale items and open-ended questions, with qualitative data analyzed using thematic analysis. The findings indicate that students perceive AI as a helpful learning support, particularly for understanding complex tax regulations, improving learning efficiency, and supporting independent study. However, concerns remain regarding information accuracy, limited relevance to Indonesian tax regulations, overreliance on AI, and academic integrity. This study concludes that AI can support tax learning when used as a complementary tool, supported by critical use and lecturer guidance.
Keywords: artificial intelligence; student perceptions; tax learning; higher education; qualitative research
References
[1] S. Russell and P. Norvig, Artificial Intelligence : A Modern Approach, 3rd Ed. New Jersey, 2010.
[2] R. Luckin, W. Holmes, M. Griffith, and L. B. Forcier, Intelligence Unleashed : An argument for AI in Education. London: Pearson, 2016. [Online]. Available: https://www.pearson.com/content/dam/corporate/global/pearson-dot-com/files/innovation/Intelligence-Unleashed-Publication.pdf
[3] L. Labadze, M. Grigolia, and L. Machaidze, “Role of AI chatbots in education: systematic literature review,” Int. J. Educ. Technol. High. Educ., vol. 20, no. 1, pp. 1–17, 2023, doi: 10.1186/s41239-023-00426-1.
[4] O. Zawacki-Richter, V. I. Marín, M. Bond, and F. Gouverneur, “Systematic review of research on artificial intelligence applications in higher education – where are the educators?,” Int. J. Educ. Technol. High. Educ., vol. 16, no. 1, 2019, doi: 10.1186/s41239-019-0171-0.
[5] L. Chen, P. Chen, and Z. Lin, “Artificial Intelligence in Education: A Review,” IEEE Access, vol. 8, pp. 75264–75278, 2020, doi: 10.1109/ACCESS.2020.2988510.
[6] E. Kasneci et al., “ChatGPT for good? On opportunities and challenges of large language models for education,” Learn. Individ. Differ., vol. 103, no. February, 2023, doi: 10.1016/j.lindif.2023.102274.
[7] X. Zhai et al., “A Review of Artificial Intelligence (AI) in Education from 2010 to 2020,” Complexity, vol. 2021, 2021, doi: 10.1155/2021/8812542.
[8] S. James and C. Alley, “Tax Compliance, Self-Assessment and Tax Administration,” J. Financ. Manag. Public Serv., vol. 2, no. 2, pp. 27–42, 2004.
[9] OECD, OECD Digital Education Outlook 2023: Towards an Effective Digital Education Ecosystem. OECD Publishing, 2023. doi: https://doi.org/10.1787/c74f03de-en.
[10] B. Apostolou, J. W. Dorminey, J. M. Hassell, and J. E. Rebele, “Accounting Education Literature Review (2016),” J. Account. Educ., vol. 39, no. 1, pp. 1–31, 2017, doi: 10.1016/j.jaccedu.2017.03.001.
[11] T. Karsenti, “Artificial Intelligence in Education: The Urgent Need to Prepare Teachers for Tomorrow’s Schools,” Form. Prof., vol. 27, no. 1, p. 105, 2019, doi: 10.18162/fp.2019.a166.
[12] A. Tlili et al., “What if The Devil is My Guardian Angel: ChatGPT as a Case Study of Using Chatbots in Education,” Smart Learn. Environ., vol. 10, no. 1, 2023, doi: 10.1186/s40561-023-00237-x.
[13] F. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Q., vol. 13, no. 3, pp. 319–340, 1989, [Online]. Available: http://www.jstor.org/stable/249008
[14] V. Braun and V. Clarke, “Using Thematic Analysis in Psychology,” Qual. Res. Psychol., vol. 3, no. 2, pp. 77–101, 2006, doi: https://doi.org/10.1191/1478088706qp063oa.
[15] R. Sajja, Y. Sermet, B. Fodale, and I. Demir, “Evaluating AI-Powered Learning Assistants in Engineering Higher Education: Student Engagement, Ethical Challenges, and Policy Implications,” pp. 1–27, 2025, doi: 10.48550/arxiv.2506.05699.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Panca Wisesa, Diajeng Fitri Wulan, Rindy Dwi Ladista, M. Muhayin A Sidik4
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This 