ISSN: 2226-6348
Open access
This study examined the effectiveness of the Smart Learning Accounting Module on undergraduate students’ learning motivation in accounting. The study involved 40 third-year accounting students from a selected university in Xinjiang, China, and employed a quantitative one-group pre-test and post-test quasi-experimental design. The module was implemented over an eight-week intervention on transaction analysis and journal entries. Students’ learning motivation was measured using an ARCS-based questionnaire covering Attention, Relevance, Confidence, and Satisfaction. Data were analysed using descriptive statistics, reliability analysis, the Shapiro-Wilk normality test, and the Wilcoxon signed-rank test. The findings showed that overall learning motivation increased from a moderate level before the intervention (M = 3.319, SD = 0.486) to a high level after the intervention (M = 4.040, SD = 0.724). All four ARCS dimensions also improved. The Wilcoxon signed-rank test revealed a significant difference between pre-test and post-test motivation scores, Z = -4.954, p < .001, with a large effect size (r = .783). The findings suggest that the Smart Learning Accounting Module can enhance undergraduate students’ learning motivation in accounting.
Alyoussef, I. Y. (2023). Acceptance of e-learning in higher education: The role of task-technology fit with the information systems success model. Heliyon, 9(3), e13751. https://doi.org/10.1016/j.heliyon.2023.e13751
Apostolou, B., Churyk, N. T., Hassell, J. M., & Matuszewski, L. (2023). Accounting education literature review (2022). Journal of Accounting Education, 63, 100831. https://doi.org/10.1016/j.jaccedu.2023.100831
Barz, N., Benick, M., Dörrenbächer-Ulrich, L., & Perels, F. (2024). Students’ acceptance of e-learning: Extending the technology acceptance model with self-regulated learning and affinity for technology. Discover Education, 3, Article 114. https://doi.org/10.1007/s44217-024-00195-7
Bond, M., Khosravi, H., de Laat, M., Bergdahl, N., Negrea, V., Oxley, E., Pham, P., Chong, S. W., & Siemens, G. (2024). A meta systematic review of artificial intelligence in higher education: A call for increased ethics, collaboration, and rigour. International Journal of Educational Technology in Higher Education, 21, Article 4. https://doi.org/10.1186/s41239-023-00436-z
Churyk, N. T., Eaton, T. V., & Matuszewski, L. J. (2025). Accounting education literature review (2024). Journal of Accounting Education, 71, 100969. https://doi.org/10.1016/j.jaccedu.2025.100969
Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20, Article 22. https://doi.org/10.1186/s41239-023-00392-8
Dai, Z., Sun, C., Zhao, L., & Li, Z. (2021). Assessment of smart learning environments in higher educational institutions: A study using AHP-FCE and GA-BP methods. IEEE Access, 9, 35487–35500. https://doi.org/10.1109/ACCESS.2021.3062680
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Fang, W., & Nie, C. N. (2025). Inequalities in digital literacy: Exploring the disparity in tangible outcomes of internet use among college students in China. Frontiers in Communication, 10, Article 1601240. https://doi.org/10.3389/fcomm.2025.1601240
Fang, X., Ng, T. K., Leung, J. K. L., & Xu, H. (2024). The applications of the ARCS model in instructional design, theoretical framework, and measurement tool: A systematic review of empirical studies. Interactive Learning Environments, 32(10), 5919–5946. https://doi.org/10.1080/10494820.2023.2240867
Guo, C., & Wan, B. (2022). The digital divide in online learning in China during the COVID-19 pandemic. Technology in Society, 71, 102122. https://doi.org/10.1016/j.techsoc.2022.102122
Haji Moradkhani, H., Mashayekh, S., & Khodabandelou, R. (2023). Digital game-based learning in an introductory accounting course: Design and development of an instructional game. International Journal of Game-Based Learning, 13(1), 1–21. https://doi.org/10.4018/IJGBL.324073
Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022). Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers, 3, 275–285. https://doi.org/10.1016/j.susoc.2022.05.004
Howard, J. L., Bureau, J. S., Guay, F., Chong, J. X. Y., & Ryan, R. M. (2021). Student motivation and associated outcomes: A meta-analysis from self-determination theory. Perspectives on Psychological Science, 16(6), 1300–1323. https://doi.org/10.1177/1745691620966789
Keller, J. M. (2010). Motivational design for learning and performance: The ARCS model approach. Springer. https://doi.org/10.1007/978-1-4419-1250-3
Li, K. C., & Wong, B. T. M. (2021). Review of smart learning: Patterns and trends in research and practice. Australasian Journal of Educational Technology, 37(2), 189–204. https://doi.org/10.14742/ajet.6617
Ma, N., & Ruannakarn, P. (2024). The application of digital transformation in accounting education: A case study of Internet + technology improving academic performance. Higher Education Studies, 14(2), 62–72. https://doi.org/10.5539/hes.v14n2p62
Maiti, M., Priyaadharshini, M., & Harini, S. (2023). Design and evaluation of a revised ARCS motivational model for online classes in higher education. Heliyon, 9(12), e22729. https://doi.org/10.1016/j.heliyon.2023.e22729
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78. https://doi.org/10.1037/0003-066X.55.1.68
Sampaio, C., Régio, M., & Sebastião, J. R. (2024). The influence of students’ perceptions and motivation on accounting and taxation careers. Administrative Sciences, 14(1), Article 18. https://doi.org/10.3390/admsci14010018
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
Zhiping, C., & Yin, T. T. (2026). The Effectiveness of the Smart Learning Accounting Module on Undergraduate Students’ Learning Motivation in Accounting. International Journal of Academic Research in Progressive Education and Development, 15(3), 1498–1509.
Copyright: © 2026 The Author(s)
Published by HRMARS (www.hrmars.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode