Adaptation of Artificial Intelligence Technology in Art Education to Prepare Prospective Elementary School Teachers
A Study of the 2022 Cohort of the Primary School Teacher Education Program at Universitas Halim Sanusi PUI
DOI:
https://doi.org/10.59653/ijmars.v4i01.2280Keywords:
Artificial Intelligence in Education, Art Education, Teacher Preparation, Digital Creativity, AI-Assisted LearningAbstract
The integration of Artificial Intelligence (AI) in education has become an increasingly important topic in contemporary educational research. Artificial Intelligence technologies provide opportunities to support innovative teaching methods, creative exploration, and the development of digital competencies among students and educators. In art education, AI-assisted tools enable learners to explore visual ideas, generate artistic concepts, and develop creative learning media using digital platforms. This research aims to examine the adaptation of Artificial Intelligence technology in art education to prepare prospective elementary school teachers from the 2022 cohort of the Primary School Teacher Education Program at Universitas Halim Sanusi PUI. The research uses a descriptive qualitative approach to understand how AI tools are used in learning activities, how students respond to the integration of technology in art learning, and how these technologies contribute to the development of creativity and digital competence among teacher candidates. Data were collected through classroom observations, interviews with students and lecturers, and documentation of student projects, including digital artworks and visual learning media created using AI-assisted tools. The results indicate that AI integration in art education encourages creative experimentation, improves digital literacy, and enables students to design innovative teaching materials suitable for elementary school classrooms. Students demonstrated enthusiasm when exploring AI-generated visual ideas and integrating them into artistic projects and instructional media. However, the research also identified several challenges, including unequal technological skills among students, ethical concerns regarding authorship of AI-generated images, and limitations in access to digital devices and stable internet connections. Despite these challenges, the findings suggest that Artificial Intelligence technology can significantly enrich art education and strengthen the competencies of prospective elementary school teachers when supported by appropriate pedagogical strategies and ethical awareness.
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References
Anderson, T., & Dron, J. (2017). Artificial intelligence and the future of teaching and learning. Educational Technology Research and Development, 65(4), 871–884. https://doi.org/10.1007/s11423-017-9537-0
Bond, M., Zawacki-Richter, O., & Nichols, M. (2019). Revisiting five decades of educational technology research. Computers & Education, 136, 1–16. https://doi.org/10.1016/j.compedu.2019.03.016
Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial intelligence trends in education. Procedia Computer Science, 136, 16–24. https://doi.org/10.1016/j.procs.2018.08.233
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
Chen, X., Zou, D., Cheng, G., & Xie, H. (2022). Artificial intelligence in education: A review. Educational Technology & Society, 25(1), 28–41. https://doi.org/10.30191/ETS.202201_25(1).0003
Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. Computers & Education: Artificial Intelligence, 4, 100131. https://doi.org/10.1016/j.caeai.2023.100131
Garcia, M., & Revilla, A. (2023). Digital creativity and art education in the age of AI. International Journal of Art & Design Education, 42(3), 450–465. https://doi.org/10.1111/jade.12452
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications. Center for Curriculum Redesign.
Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promises and implications for teaching and learning. Computers & Education: Artificial Intelligence, 3, 100097. https://doi.org/10.1016/j.caeai.2022.100097
Hwang, G. J., & Tu, Y. F. (2021). Roles and research trends of artificial intelligence in education. Educational Technology & Society, 24(3), 1–4. https://doi.org/10.30191/ETS.202107_24(3).0001
Kim, H. (2022). AI-assisted creativity in visual arts education. Journal of Creative Education, 13(4), 1120–1135. https://doi.org/10.4236/ce.2022.134069
Kong, S. C., Cheung, W. M., & Zhang, G. (2021). Evaluation of AI literacy in teacher education. Computers & Education, 168, 104192. https://doi.org/10.1016/j.compedu.2021.104192
Long, D., & Magerko, B. (2020). What is AI literacy? Proceedings of the ACM Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3313831.3376727
Luckin, R. (2021). AI for school teachers. Routledge.
Luckin, R., & Holmes, W. (2022). Ethics of AI in education. British Journal of Educational Technology, 53(4), 865–874. https://doi.org/10.1111/bjet.13203
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. (2016). Intelligence unleashed: An argument for AI in education. Pearson Education.
Mayer, R. (2021). Multimedia learning and artificial intelligence. Educational Psychology Review, 33(2), 443–456. https://doi.org/10.1007/s10648-020-09552-3
Mishra, P., & Mehta, R. (2020). Creativity, technology, and education. TechTrends, 64(3), 320–328. https://doi.org/10.1007/s11528-020-00492-1
Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020.
https://doi.org/10.1016/j.caeai.2021.100020
Pedro, F., Subosa, M., Rivas, A., & Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities. International Journal of Educational Technology in Higher Education, 16(1). https://doi.org/10.1186/s41239-019-0171-0
Roll, I., & Wylie, R. (2016). Evolution and revolution in AI in education. International Journal of Artificial Intelligence in Education, 26(2), 582–599. https://doi.org/10.1007/s40593-016-0110-3
Selwyn, N. (2020). Should robots replace teachers? AI and the future of education. Learning, Media and Technology, 45(1), 1–3. https://doi.org/10.1080/17439884.2019.1686016
Shin, D. (2021). The effects of explainability and causability on trust in artificial intelligence. Computers in Human Behavior, 118, 106–115. https://doi.org/10.1016/j.chb.2021.106653
Spector, J. M. (2018). Conceptualizing artificial intelligence in education. Educational Technology & Society, 21(4), 10–18. https://doi.org/10.30191/ETS.201810_21(4).0002
Tang, Y., & Li, H. (2023). Artificial intelligence supported learning environments. Education and Information Technologies, 28(5), 5623–5642. https://doi.org/10.1007/s10639-022-11240-5
Tuomi, I. (2018). The impact of artificial intelligence on learning and teaching. European Commission Joint Research Centre.
Wang, F., & Cheng, B. (2021). Artificial intelligence in education: A systematic review. Computers & Education, 172, 104229. https://doi.org/10.1016/j.compedu.2021.104229
Zawacki-Richter, O., Marín, V., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(39). https://doi.org/10.1186/s41239-019-0171-0
Zhai, X., Chu, X., Chai, C. S., & Jong, M. (2021). Artificial intelligence in education: A systematic review. Computers and Education: Artificial Intelligence, 2, 100017. https://doi.org/10.1016/j.caeai.2021.100017
Zhang, K., Aslan, A., & Porter, A. (2020). Artificial intelligence in education research. British Journal of Educational Technology, 51(5), 1804–1819. https://doi.org/10.1111/bjet.12990
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