Artificial Intelligence Integration among Design Students in Malaysia

Abstract

Artificial intelligence (AI) is rapidly reshaping the creative industry, yet little is known on how Malaysian design students cope with it. Existing studies on AI literacy tend to focus on science and technology fields, leaving a significant gap of the creative arts. This study tackles that gap by exploring how thirty final-year undergraduate graphic design students from Universiti Teknologi MARA (UiTM), Puncak Alam weave AI into their academic work. Framed by Expectancy–Value Theory (EVT), this study captured student perspectives through six focus group discussions (each 60–90 minutes long), probing their experiences, attitudes, and the perceived costs and benefits of using AI. The findings reveal selective adoption. For instance, while 93% of participants use ChatGPT to spark ideas, few explored design-specific tools like Adobe Firefly or Photoshop Beta. Students consistently praised AI for boosting efficiency and aiding brainstorming but expressed heavy reservations about its impact on authenticity and originality. A clear disconnect presented, with institutional policies lagging behind the rapid realities of the design industry, forcing students to depend on other sources for guidance. From these discussions, four central themes emerged: authenticity concerns, perceived benefits and costs, institutional misalignment, and demand for guidance. The study highlights the need for immediate AI literacy initiatives supported by workshops and ethical guidelines, as well as longer-term curriculum reform and lecturer training. A discipline-specific model of critical AI integration is recommended to ensure that student preparedness for industry demands while safeguarding the originality and cultural heritage central to the design profession.

References

Ahmad, M. F., & Ghapar, W. R. G. W. A. (2019). The Era of Artificial Intelligence in Malaysian Higher Education: Impact and Challenges in Tangible Mixed-Reality Learning System toward Self Exploration Education (SEE). Procedia Computer Science, 163, 2–10. https://doi.org/10.1016/j.procs.2019.12.079

Alarie, B., & Cockfield, A. (2021). Will machines replace us? Machine-Authored Texts and the future of Scholarship. Law Technology and Humans, 3(2). https://doi.org/10.5204/lthj.2089

Berger, R. (2013). Now I see it, now I don’t: researcher’s position and reflexivity in qualitative research. Qualitative Research, 15(2), 219–234. https://doi.org/10.1177/1468794112468475

Bong, M. (2001). Role of Self-Efficacy and Task-Value in Predicting College Students’ Course Performance and Future Enrollment Intentions. Contemporary Educational Psychology, 26(4), 553–570. https://doi.org/10.1006/ceps.2000.1048

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa

Cetindamar, D., Kitto, K., Wu, M., Zhang, Y., Abedin, B., & Knight, S. (2022). Explicating AI literacy of employees at digital workplaces. IEEE Transactions on Engineering Management, 71, 810–823. https://doi.org/10.1109/tem.2021.3138503

Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00411-8

Chan, C. K. Y., & Zhou, W. (2023). Deconstructing Student Perceptions of Generative AI (GenAI) through an Expectancy Value Theory (EVT)-based Instrument. arXiv (Cornell University). https://doi.org/10.48550/arxiv.2305.01186

Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed). Thousand Oaks: SAGE.

Dehouche, N., & Dehouche, K. (2023). What’s in a text-to-image prompt? The potential of stable diffusion in visual arts education. Heliyon, 9(6), e16757. https://doi.org/10.1016/j.heliyon.2023.e16757

Eccles, J. S., & Wigfield, A. (2002). Motivational Beliefs, Values, and Goals. Annual Review of Psychology, 53(1), 109–132. https://doi.org/10.1146/annurev.psych.53.100901.135153

Fathallah, R. (2021). Pedagogies for Democratic Participation in Design Studios: Towards More Inclusive Group Work among Interior Design Students. International Journal of Art & Design Education, 40(4), 736–747. https://doi.org/10.1111/jade.12385

Fleischmann, K. (2024). Generative Artificial Intelligence in Graphic Design Education: A Student perspective. Canadian Journal of Learning and Technology, 50(1), 1–17. https://doi.org/10.21432/cjlt28618

Gilster, P. (1997). Digital Literacy. Wiley Computer.

Hennink, M., & Kaiser, B. N. (2021). Sample sizes for saturation in qualitative research: A systematic review of empirical tests. Social Science & Medicine, 292, 114523. https://doi.org/10.1016/j.socscimed.2021.114523

Kim, J., Lee, H., & Cho, Y. H. (2022). Learning design to support student-AI collaboration: perspectives of leading teachers for AI in education. Education and Information Technologies, 27(5), 6069–6104. https://doi.org/10.1007/s10639-021-10831-6

Liang, J. (2024). Enhanced Art Design Education: Integrating Artificial Intelligence for Resource Optimization and Innovative Teaching. Atlantis Highlights in Social Sciences, Education and Humanities/Atlantis Highlights in Social Sciences, Education and Humanities, 239–247. https://doi.org/10.2991/978-94-6463-560-7_29

Liao, J., Kumar, S., & Furuoka, F. (2025). Bridging the Digital Divide: How Internet Access Shapes Human Capital Development and Economic Inequality. E-Bangi Journal of Social Science and Humanities, 22(2). https://doi.org/10.17576/ebangi.2025.2202.03

Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–16. https://doi.org/10.1145/3313831.3376727

Ministry of Digital. (2025). National AI Office. Ai.gov.my. https://ai.gov.my

Mocănașu, D. R. (2020). Determining the Sample Size in Qualitative Research. International Multidisciplinary Scientific Conference on the Dialogue between Sciences & Arts, Religion & Education, 4(1), 181–187. https://doi.org/10.26520/mcdsare.2020.4.181-187

MyDIGITAL. (2025). AI untuk Rakyat | Self learning online program. Ai.gov.my. https://aiur.ai.gov.my/#/home

Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Shen, M. Q. (2021). Conceptualizing AI literacy: An            exploratory review. Computers and Education Artificial Intelligence, 2(1).       https://doi.org/10.1016/j.caeai.2021.100041

Perpustakaan Tun Abdul Razak, Jabatan Arkib Universiti. (2018). Sejarah fakulti –Kajian Seni Lukis & Seni Reka - UiTM Institutional Repository. https://ir.uitm.edu.my/id/eprint/61497/1/61497.pdf

Putwain, D., Sander, P., & Larkin, D. (2012). Academic self‐efficacy in research‐related skills and behaviours: Relations with learning‐related emotions and academic success. British Journal of Educational Psychology, 83(4), 633–650. https://doi.org/10.1111/j.2044-8279.2012.02084.x

Russell, S., & Norvig, P. (2021). Artificial intelligence: A Modern approach (4th ed.). Prentice Hall.

Tien, Y. T., & Chen, R. (2024, March). Challenges of Artificial Intelligence in Design Education. In Proceedings of the 2024 15th International Conference on E-Education, E-Business, E-Management and E-Learning (pp. 123-126). https://doi.org/10.1145/3670013.3670044

Touretzky, D., Gardner-McCune, C., Martin, F., & Seehorn, D. (2019). Envisioning AI for K-12: What Should Every Child Know about AI? Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 9795–9799. https://doi.org/10.1609/aaai.v33i01.33019795

Vartiainen, H., & Tedre, M. (2023). Using artificial intelligence in craft education: crafting with text-to-image generative models. Digital Creativity, 34(1), 1–21. https://doi.org/10.1080/14626268.2023.2174557

Wang, F., King, R. B., Chai, C. S., & Zhou, Y. (2023). University students’ intentions to learn artificial intelligence: the roles of supportive environments and expectancy–value beliefs. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00417-2

Xu, J., Wan Mahmud, W. A., Hassim, N., & Li, C. (2025). Reasons for Establishing Film Festivals: A Systematic Literature Review. E-Bangi Journal of Social Science and Humanities, 22(2). https://doi.org/10.17576/ebangi.2025.2202.07

Yusoff, S. M., Marzaini, A. F. M., Hao, L., Zainuddin, Z., & Basal, M. H. (2025). Understanding the role of AI in Malaysian higher education curricula: an analysis of student perceptions. Discover Computing, 28(1). https://doi.org/10.1007/s10791-025-09567-5

Zailuddin, M. F. N. O., Harun, N. A. N., Rahim, H.A. A., Kamaruzaman, A. F., Berahim, M. H., Harun, M. H., & Ibrahim, Y. (2024). Redefining creative education: a case research analysis of AI in design courses. Journal of Research in Innovative Teaching & Learning, 17(2), 282–296. https://doi.org/10.1108/jrit-01-2024-0019