The Impact of AI-assisted Tool on the Practical Skill Performance of Accounting Students in Higher Education: An Empirical Study
Dandan Qi ( Chongqing Business Vocational College, Chongqing, China )
Hao Huang ( Chongqing Business Vocational College, Chongqing, China )
https://doi.org/10.37155/2972-4856-0401-7Abstract
The accounting profession is undergoing significant transformation driven by artificial intelligence (AI), creating an urgent need to modernize accounting education. However, traditional teaching methods often lack scalability and authentic contextualization for practical skill development. While AI-based teaching assistants show promise, empirical evidence of their effectiveness in accounting education remains scarce. This study investigates the impact of an AI-assisted tool on students' practical accounting skills. A quasi-experimental design was employed, involving 90 second-year accounting students assigned to an experimental group using an AI assistant or a control group receiving traditional instruction. The AI-assisted tool provided personalized feedback and adaptive exercises during a two-week intensive module. Results from independent samples t-test showed that the experimental group achieved significantly higher practical skill scores. Multiple regression analysis within the experimental group further revealed that self-efficacy, AI tool usage, and course satisfaction were significant positive predictors of performance. The study concludes that a well-designed AI teaching assistant can effectively enhance practical skill acquisition by acting as a dynamic scaffold. It highlights AI's role not only as a cognitive tool but as a multifunctional enabler that supports personalized, engaging, and effective skill development, offering valuable insights for innovating accounting pedagogy in the digital era.
Keywords
Artificial Intelligence; Accounting education; Practical skill; Empirical studyFull Text
PDFReferences
[2].Xu, X., et al., Enhancing self-regulated learning and learning experience in generative AI environments: The critical role of metacognitive support. British Journal of Educational Technology, 2025. 56(5): p. 1842-1863.
[3].Veerbeek, J., Fighting Fire with Fire: Journalistic Investigations of Artificial Intelligence Using Artificial Intelligence Techniques. Journalism Practice, 2025: p. 1-19.
[4].Inoue, A. and R. Tanaka, Do teachers’ college majors affect students’ academic achievement in the sciences? A cross-subfields analysis with student-teacher fixed effects. Education Economics, 2023. 31(5): p. 617-631.
[5].Ralph, V.R., et al., Beyond instructional practices: Characterizing learning environments that support students in explaining chemical phenomena. Journal of Research in Science Teaching, 2022. 59(5): p. 841-875.
[6].Pianon, K., P. Tep, and W. Thitayanuwat. Enhancing AI Literacy in Junior High School Students Through a Constructionist Project-Based Learning Approach. in 2025 10th International STEM Education Conference (iSTEM-Ed). 2025.
[7].Moats, D., et al., Making problems: interdisciplinary collaboration and AI ethics. Science as Culture, 2025: p. 1-26.
[8].Hutchinson, C., et al. Student Receptiveness to Circadian-Aware AI-Driven Scheduling. in 2025 Systems and Information Engineering Design Symposium (SIEDS). 2025.
[9].McGrew, H.C., et al., Telehealth Simulations with Generative Artificial Intelligence in Midwifery Education: Practice for Person-Centered and Culturally Responsive Care. Journal of Midwifery & Women's Health, 2025. 70(6): p. 932-938.
[10].Stephen, V.K., et al. Design and Application of Teaching System Using Artificial Intelligence Technology. in 2025 International Conference for Artificial Intelligence, Applications, Innovation and Ethics (AI2E). 2025.
[11].Santiago, C.M., ‘Generative AI made me do this’ exploring the potential of ChatGPT-assisted collaborative action research in science higher education: a case in the Philippines. Educational Action Research, 2025: p. 1-18.
[12].Ahlam, A., et al. Navigating AI Adoption: Challenges and Suggested Solutions for College Lecturers. in 2025 International Conference on Smart Learning Courses (SCME). 2025.
[13].Lampi, J.P., S.L. Armstrong, and P. Das, Normalizing the Productive Struggle: Reframing Reading Development in Postsecondary Contexts. Journal of Adolescent & Adult Literacy, 2026. 69(4): p. e70033.
[14].Horne, A. and E. Majola, Towards a humanising vocational pedagogy: reframing work integrated learning practices in a South African TVET college. Journal of Education and Work, 2026: p. 1-19.
[15].Wu, Z. and R. Huang, The impact of digital transformation on the quality of college English teaching: the mediating role of teachers’ support. Asia Pacific Journal of Education, 2025: p. 1-17.
[16].Bai, Y., An Analysis Model of College English Classroom Patterns Using LSTM Neural Networks. Wireless Communications and Mobile Computing, 2022. 2022(1): p. 6477883.
[17].Dawood, B.M.A.E., et al., Artificial Intelligence Technology Integration in Healthcare: Al Ahsa Nursing Students’ Attitudes and Readiness. Nursing Forum, 2025. 2025(1): p. 2848944.
[18].Esmond, B., Vocational teachers and workplace learning: integrative, complementary and implicit accounts of boundary crossing. Studies in Continuing Education, 2021. 43(2): p. 156-173.
[19].Babo, L., et al. Exploring HEIs Students' Perceptions of Artificial Intelligence on their Learning Process. in 2024 5th International Conference in Electronic Engineering, Information Technology & Education (EEITE). 2024.
[20].P. K, M., C.R. S, and C. V. D. A. AI-Driven Climate-Resilient Scheduling of V2G and G2V Operations in Higher Educational Institution Microgrids. in 2025 International Conference on Next Generation Computing Systems (ICNGCS). 2025.
[21].Muller, H. and A. du Plessis, The impact of a quality, technology-enhanced teaching support medium on student success in a first-year financial accounting module at an open distance learning institute. South African Journal of Accounting Research, 2013. 27(1): p. 37-57.
[22].Thottoli, M.M., et al., Enricher learning: Bridging the gap between academics and practicing accounting professionals. Journal of Education for Business, 2024. 99(5): p. 300-311.
[23].Aynalem, A., et al., Practice towards Hepatitis B Virus Infection Prevention and Its Associated Factors among Undergraduate Students at Hawassa University College of Medicine and Health Sciences, Hawassa, Sidama, Ethiopia, 2021: Cross-Sectional Study. International Journal of Hepatology, 2022. 2022(1): p. 2673740.
[24].Wu, J. Quality Evaluation Model of Artificial Intelligence General Education Online Course Based on AI Algorithm. in 2022 International Conference on Education, Network and Information Technology (ICENIT). 2022.
[25].Zhou, C. and F. Hou, Can AI Empower L2 Education? Exploring Its Influence on the Behavioural, Cognitive and Emotional Engagement of EFL Teachers and Language Learners. European Journal of Education, 2024. 59(4): p. e12750.
[26].Zheng, Y., Research on Mathematics Classroom Teaching Optimization Model Based on GA Neural Network. Mathematical Problems in Engineering, 2022. 2022(1): p. 5414306.
[27].Zargham, M. A Perspective on the Future of Higher Education. in 2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE). 2023.
[28].Zhao, Q., et al., Cultivation Design of Applied Undergraduates’ Engineering Innovation Ability Based on Virtualization Technology. Wireless Communications and Mobile Computing, 2022. 2022(1): p. 5500021.
[29].Sun, K., P. Cang, and W. Sun. A Comprehensive Framework for Developing AI General Education Courses in Higher Vocational Education. in 2025 7th International Conference on Computer Science and Technologies in Education (CSTE). 2025.
[30].Lin, J., J. Lin, and X. Luo. Barriers to Generative AI Adoption Among Higher Vocational Students: Understanding Hesitancy and Resistance. in 2025 5th International Conference on Artificial Intelligence and Education (ICAIE). 2025.
[31].Sabatini, J., et al., A framework of literacy development and how AI can 54(5): p. 1174-1203.
[32].transform theory and practice. British Journal of Educational Technology, 2023. Sivajyothi, M., et al. Employability Prediction using Facebook Prophet for Computer Science and Engineering Graduates. in 2023 International Conference on Sustainable Communication Networks and Application (ICSCNA). 2023.
[33].Zhang, P., et al., Initial performance predicts improvements in computerized cognitive training: Evidence from a selective attention task. PsyCh Journal, 2021. 10(5): p. 742-750.
Copyright © 2026 Dandan Qi,Hao Huang
Publishing time:2026-03-31
This work is licensed under a Creative Commons Attribution 4.0 International License