Generative AI in Project-Based 3D Modelling: Effects on Creativity, Critical Thinking, and Workflow
DOI:
https://doi.org/10.24059/olj.v30i1.4769Keywords:
Generative AI, creativity, critical thinking, process and workflow, 3D ModellingAbstract
Generative Artificial Intelligence (AI) has sparked significant debate within creative industries and educational settings. This study examined the effect of integrating Generative AI (Gen-AI) tools into Project-Based 3D Modelling on students' creativity, critical thinking, processes, and workflows. A mixed-method research design with a sequential explanatory approach was employed, involving 19 students from a Malaysian creative arts institution specializing in 3D design, selected through convenience sampling. Quantitative data were gathered from students' creative scores based on Amabile’s Componential Model for Creativity and timeline worksheets documenting the time spent on artwork creation. Qualitative data were collected through interviews to assess critical thinking and through self-reflection forms to evaluate processes and workflows. Insights were also gained from two industry experts regarding their use of Gen-AI tools. Findings indicated that Gen-AI tools enhanced creativity and accelerated the creative process, thereby improving workflow efficiency. However, mixed reactions were observed regarding the implementation of Gen-AI tools in education, highlighting concerns about academic integrity and ethical considerations. This study provides valuable insights into the opportunities and challenges associated with the use of Gen-AI tools in educational contexts.
References
Anam, A. F. C., & Fathoni. (2023). Leveraging generative AI solutions in art and design education: Bridging sustainable creativity and fostering academic integrity for innovative society. E3S Web of Conferences, 426, Article 01102. https://doi.org/10.1051/e3sconf/202342601102
Amabile, T. M., & Pratt, M. G. (2016). The dynamic componential model of creativity and innovation in organizations: Making progress, making meaning. Research in Organizational Behavior, 36, 157-183. https://doi.org/10.1016/j.riob.2016.10.001
Baidoo-Anu, D., & Owusu Ansah, L. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. SSRN. https://doi.org/10.2139/ssrn.4337484
Bender, S. M. (2023). Coexistence and creativity: screen media education in the age of artificial intelligence content generators. Media Practice and Education, 24(4), 351–366. https://doi.org/10.1080/25741136.2023.2204203
Betker, J., Goh, G., Jing, L., Brooks, T., Wang, J., Li, L., Ouyang, L., Zhuang, J., Lee, J., Guo, Y., Manassra, W., Dhariwal, P., Chu, C., Jiao, Y., & Ramesh, A. (2023). Improving image generation with better captions. OpenAI. https://cdn.openai.com/papers/dall-e-3.pdf
Bhaduri S., Van Horne, K., & Sumner, T. (2019). Designing an Informal Learning Curriculum to develop 3D modeling knowledge and improve spatial thinking skills. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1-8. https://doi.org/10.1145/3290607.3299039
Brookhart, S. M. (2010). How to assess higher-order thinking skills in your classroom. ASCD.
Cheng, M. (2022). The creativity of artificial intelligence in art. Proceedings, 81(1), Article 110. https://doi.org/10.3390/proceedings2022081110
Chiu, T. K. F. (2023). The impact of Generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney. Interactive Learning Environments, 1–17. https://doi.org/10.1080/10494820.2023.2253861
Chiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023). Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence, 4, Article 100118. https://doi.org/10.1016/j.caeai.2022.100118
Creswell, J. W., & Clark, V. L. P. (2007). Designing and conducting mixed methods research. Sage Publications.
Dawson, P. (2017). Assessment rubrics: towards clearer and more replicable design, research and practice. Assess. Eval. High. Educ. 42, 347–360. https://doi.org/10.1080/02602938.2015.1111294
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), Article e16757. https://doi.org/10.1016/j.heliyon.2023.e16757
Dobrev, D. (2005). Formal definition of AI. International Journal "Information Theories & Applications, 12(3), 277–285. https://doi.org/10.48550/arXiv.1209.4838
Double, K., El Masri, Y., McGrane, J., & Hopfenbeck, T. (2023). Do IB students have higher critical thinking? A comparison of IB with national education programs. Thinking Skills and Creativity, 50, Article 101416. https://doi.org/10.1016/j.tsc.2023.101416
Ellerton, P. (2022). On critical thinking and content knowledge: A critique of the assumptions of cognitive load theory. Thinking Skills and Creativity, 43, Article 100975. https://doi.org/10.1016/j.tsc.2021.100975
Epstein, Z., Hertzmann, A., Akten, M., Farid, H., Fjeld, J., Frank, M. R., Groh, M., Herman, L., Leach, N., Mahari, R., Pentland, A. S., Russakovsky, O., Schroeder, H., & Smith, A. (2023). Art and the science of generative AI: Understanding shifts in creative work will help guide AI’s impact on the media ecosystem. Science, 380(6650), 1110-1111. https://doi.org/10.1126/science.adh4451
Esling, P., & Devis, N. (2020). Creativity in the era of artificial intelligence [Keynote paper]. JIM Conference. https://doi.org/10.48550/arXiv.2008.05959
Facione, P. A. (2015). Critical thinking: What it is and why it counts (6th ed.). Insight Assessment. https://www.researchgate.net/publication/251303244_Critical_Thinking_What_It_Is_and_Why_It_Counts
Facione, P. A., Facione, N. C., & The California Academic Press. (1994). Holistic critical thinking scoring rubric (Version 2.0). The Critical Thinking Community. https://teaching.temple.edu/sites/teaching/files/resource/pdf/Holistic%20Critical%20Thinking%20Scoring%20Rubric.v2%20%5BAccessible%5D.pdf
Grassini, S. (2023). Shaping the future of education: Exploring the potential and consequences of AI and ChatGPT in educational settings. Education Sciences, 13(7), Article 692. https://doi.org/10.3390/educsci13070692
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative adversarial networks. In Advances in Neural Information Processing Systems (Vol. 3). Communications of the ACM, 63(11), 139-144. https://doi.org/10.1145/3422622
Han, A., & Cai, Z. (2023). Design implications of generative AI systems for visual storytelling for young learners. In IDC ‘23: Proceedings of the 22nd Annual ACM Interaction Design and Children Conference (pp. 470–474). https://doi.org/10.1145/3585088.3593867
Huang, T.-C., Chen, M.-Y., & Lin, C.-Y. (2019). Exploring the behavioral patterns transformation of learners in different 3D modeling teaching strategies. Computers in Human Behavior, 92, 670–678. https://doi.org/10.1016/j.chb.2017.08.028
Hutson, J., & Cotroneo, P. (2023). Generative AI tools in art education: Exploring prompt engineering and iterative processes for enhanced creativity. Metaverse: Exploring Arts, Humanities, and Sciences, 4(1) Article 2164. https://doi.org/10.54517/m.v4i1.2164
Hutson, J., & Harper-Nichols, M. (2023). Generative AI and algorithmic art: Disrupting the framing of meaning and rethinking the subject-object dilemma. Global Journal of Computer Science and Technology, 23(D1), 55–61. https://doi.org/10.34257/GJCSTDVOL23IS1PG55
Hutson, J., & Lang, M. (2023). Content creation or interpolation: AI generative digital art in the classroom. Metaverse: Exploring Arts, Humanities, and Sciences, 4(1), Article 2158. https://doi.org/10.54517/m.v4i1.2158
Hutson, J., & Robertson, B. (2023). Exploring the educational potential of AI generative art in 3D design fundamentals: A case study on prompt engineering and creative workflows. Global Journal of Human-Social Science: Arts & Humanities, 23(A2), 1–11. https://socialscienceresearch.org/index.php/GJHSS/article/view/103669
Jeon, K., Jarrett, O., & Ghim, H. (2014). Project-based learning in engineering education: Is it motivational? International Journal of Engineering Education, 30(2), 438–446. https://www.researchgate.net/publication/285579124_Project-Based_Learning_in_Engineering_Education_Is_it_motivational
Kaufman, S. B. (2007). Review of Explaining creativity: The science of human innovation, by R. K. Sawyer. Psychology of Aesthetics, Creativity, and the Arts, 1(1), 47–48. https://doi.org/10.1037/1931-3896.1.1.47
Kleon, A. (2012). Steal like an artist: 10 things nobody told you about being creative. Workman Publishing. https://austinkleon.com/steal/
Kong, F. (2020). Application of artificial intelligence in modern art teaching. International Journal of Emerging Technologies in Learning (iJET), 15(13), 238–251. https://doi.org/10.3991/ijet.v15i13.15351
Kozbelt, A., Beghetto, R. A., & Runco, M. A. (2010). Theories of creativity. In J. C. Kaufman & R. J. Sternberg (Eds.), The Cambridge handbook of creativity (pp. 20–47). Cambridge University Press. https://doi.org/10.1017/CBO9780511763205.004
Ma, Y. (2023). Exploration of flipped classroom approach to enhance critical thinking skills. Heliyon, 9(11), Article e20895. https://doi.org/10.1016/j.heliyon.2023.e20895
Maguire, M., & Delahunt, B. (2017). Doing a thematic analysis: A practical, step-by-step guide for learning and teaching scholars. Dundalk Institute of Technology. https://www.researchgate.net/publication/349506918_Doing_a_Thematic_Analysis_A_Practical_Step-by-Step_Guide
Markauskaite, L., Marrone, R., Poquet, O., Knight, S., Martinez-Maldonado, R., Howard, S., Tondeur, J., De Laat, M., Buckingham Shum, S., Gašević, D., & Siemens, G. (2022). Rethinking the entwinement between artificial intelligence and human learning: What capabilities do learners need for a world with AI? Computers and Education: Artificial Intelligence, 3, Article 100056. https://doi.org/10.1016/j.caeai.2022.100056
Martínez-Villagrasa, B., Esparza, D., Llacer, T., & Cortiñas, S. (2020). Methodology for the analysis and self-reflection of design students about their competences. In L. Buck, E. Bohemia, & H. Grierson (Eds.), DS 104: Proceedings of the 22nd International Conference on Engineering and Product Design Education (E&PDE 2020) (pp. 1-9). VIA Design, VIA University. https://doi.org/10.35199/EPDE.2020.63
Mota-Valtierra, G., Rodríguez-Reséndiz, J., & Herrera-Ruiz, G. (2019). Constructivism-based methodology for teaching artificial intelligence topics focused on sustainable development. Sustainability, 11(17), Article 4642. https://doi.org/10.3390/su11174642
Notaro, A. (2020). State of the art: A.I. through the (artificial) artist’s eye. In Proceedings of EVA London 2020: Electronic Visualisation and the Arts (pp. 322-328). British Computer Society. https://doi.org/10.14236/ewic/EVA2020.58
Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, Article 100020. https://doi.org/10.1016/j.caeai.2021.100020
Ruslin, R., Mashuri, S., Sarib, M., Alhabsyi, F., & Syam, H. (2022). Semi-structured interview: A methodological reflection on the development of a qualitative research instrument in educational studies. International Journal of Scientific & Technology Research, 12(1), 22-29. https://www.iosrjournals.org/iosr-jrme/papers/Vol-12%20Issue-1/Ser-5/E1201052229.pdf
Shi, J., Jain, R., Duan, R., & Ramani, K. (2023). Understanding generative AI in art: An interview study with artists on G-AI from an HCI perspective. arXiv. https://doi.org/10.48550/arXiv.2310.13149
Sternberg, R. J., Kaufman, J. C., & Roberts, A. M. (2019). The relation of creativity to intelligence and wisdom. In J. C. Kaufman & R. J. Sternberg (Eds.), The Cambridge handbook of creativity (2nd ed., pp. 237–353). Cambridge University Press.
Supianto. (2025). Do rubrics kill creativity? Rethinking assessment practices in college teaching. College Teaching, 1–3. https://doi.org/10.1080/87567555.2025.2479144
Tahiru, F. (2021). AI in education: A systematic literature review. Journal of Cases on Information Technology, 23(1), 1–20. https://doi.org/10.4018/JCIT.2021010101
Tong, H., Türel, A., Şenkal, H., Yagci Ergun, S. F., Güzelci, O. Z., & Alaçam, S. (2023). Can AI function as a new mode of sketching: A teaching experiment with freshman. International Journal of Emerging Technologies in Learning (iJET), 18(18), 234–248. https://doi.org/10.3991/ijet.v18i18.42603
Tsai, C.-A., Song, M.-Y. W., Lo, Y.-F., & Lo, C.-C. (2023). Design thinking with constructivist learning increases the learning motivation and wicked problem-solving capability: An empirical research in Taiwan. Thinking Skills and Creativity, 50, Article 101385. https://doi.org/10.1016/j.tsc.2023.101385
Tunner, M., & Fauconnier, G. (1995). Conceptual integration and formal expression. Metaphor and Symbolic Activity, 10(3), 183–204. https://doi.org/10.1207/s15327868ms1003_3
Williamson, K., Given, L. M., & Scifleet, P. (2018). Qualitative data analysis. In K. Williamson & G. Johanson (Eds.), Research methods: Information, systems, and contexts (2nd ed., pp. 453–476). Chandos Publishing. https://doi.org/10.1016/B978-0-08-102220-7.00019-4
Zhai, X. (2022). ChatGPT user experience: Implications for education. SSRN. https://doi.org/10.2139/ssrn.4312418
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