LEVERAGING AI-BASED VISUAL LEARNING MEDIA TO ENHANCE ELEMENTARY STUDENTS’ READABILITY AND LEARNING MOTIVATION

Arief RUSLAN; Yori PUSPARANI; Wahyu ARNISA

doi:10.33068/iccd.v7i1.876

Arief RUSLAN Universitas Budi Luhur
Yori PUSPARANI Universitas Budi Luhur
Wahyu ARNISA Universitas Budi Luhur

DOI: https://doi.org/10.33068/iccd.v7i1.876

Keywords: Canva AI, Child-friendly Infographics, Elementary School, Readability, Visual Learning

Abstract

This study aims to explore the effectiveness of using Artificial Intelligence (AI) in the creation of child-friendly infographics through a case study at SDIT Nurul Amal. The background of this research is based on the need for visual learning media that are engaging, easy to understand, and appropriate for the cognitive development stage of elementary school students. The research method employed a qualitative approach with a simple experimental design, involving 30 fourth-grade students randomly divided into an experimental group using AI-generated infographics via Canva and a control group using manually designed infographics. The research instruments included comprehension tests, observations, student reflection sheets, and semi-structured interviews. The findings revealed that the experimental group achieved higher comprehension and retention scores compared to the control group. Observations and interviews further demonstrated that students were more enthusiastic, found it easier to grasp the content, and felt more motivated when engaging with AI-based infographics. In contrast, manual infographics presented readability challenges and often led to boredom. These results align with multimedia learning theory, which emphasizes the importance of combining text and visuals, and strengthen the notion that AI can serve as a creative collaborator in educational design. This study recommends the use of Canva AI in developing visual learning media in elementary schools to enhance readability, motivation, and student retention.

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References

Aguilera-Hermida, A. P., Lavigne, N. C., & Sellas, V. P. (2021). Students’ use and acceptance of infographics for learning. Australasian Journal of Educational Technology, 37(3), 1–22. https://doi.org/10.14742/ajet.6774
Bogaert, N., Desoete, A., & Aesaert, K. (2023). Development of the Reading Comprehension Strategies Questionnaire for late elementary schoolchildren. PLOS ONE, 18(1), e0280558. https://doi.org/10.1371/journal.pone.0280558
Cope, B., & Kalantzis, M. (2019). Making sense of the AI revolution in education. Educational Philosophy and Theory, 51(6), 587–603. https://doi.org/10.1080/00131857.2018.1526387
Day, E., Chow, J. C., Kalb, S., Goldberg, S., & Weisleder, A. (2024). How does the format of informative materials influence children’s comprehension, motivation, and attention? Education Sciences, 14(8), 854. https://doi.org/10.3390/educsci14080854
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Boston: Center for Curriculum Redesign.
Kim, J., Park, H., & Lee, S. (2020). AI-based automated design system for poster generation. Design Studies, 67, 102–118. https://doi.org/10.1016/j.destud.2020.03.001
Kumar, V., Singh, A., & Sharma, R. (2019). AI-driven educational content design for personalized learning. International Journal of Educational Technology in Higher Education, 16(1), 1–15. https://doi.org/10.1186/s41239-019-0177-8
Lee, S. J., & Kwon, K. (2024). A systematic review of AI education in K-12 classrooms from 2018 to 2023: Topics, strategies, and learning outcomes. Computers and Education: Artificial Intelligence, 6, 100211. https://doi.org/10.1016/j.caeai.2024.100211
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence Unleashed: An argument for AI in Education. London: Pearson.
Nugroho, A., & Suryanto, T. (2018). Efektivitas media visual dalam meningkatkan minat belajar siswa sekolah dasar. Jurnal Pendidikan Dasar Indonesia, 3(2), 112–121.
Prastowo, A. (2020). Visual learning strategies for elementary school students: An Indonesian case study. Indonesian Journal of Education Research, 4(1), 23–34.
Read, J. C., & Markopoulos, P. (2017). Child-computer interaction. International Journal of Child-Computer Interaction, 13, 1–4. https://doi.org/10.1016/j.ijcci.2017.05.002
Sun, Y., Wang, Y., & Zhao, J. (2021). Visualization with AI in elementary education: Enhancing conceptual understanding. Computers & Education, 168, 104198. https://doi.org/10.1016/j.compedu.2021.104198
Sutthiworapon, S., Vichitkunakorn, P., Choomalee, K., & Ngamchaliew, P. (2024). Effect of online infographics for enhancing health literacy among patients with type 2 diabetes in primary care unit during the COVID-19 pandemic: A randomized controlled trial. BMC Primary Care, 25, 87. https://doi.org/10.1186/s12875-024-02335-2
Yamamoto, T., & Nakano, Y. (2020). Child-friendly design principles for educational interfaces. International Journal of Child-Computer Interaction, 24, 100–112. https://doi.org/10.1016/j.ijcci.2020.100182
Yim, I. H. Y., Wong, M. S., Chai, C. S., Looi, C. K., & Chen, W. (2025). Artificial intelligence learning tools in K-12 education: A systematic review. Smart Learning Environments, 12, 27. https://doi.org/10.1186/s40561-025-00273-1
Zhang, H., & Li, Y. (2021). The role of visual simplification in elementary education infographics. Journal of Visual Literacy, 40(2), 91–109. https://doi.org/10.1080/1051144X.2021.1903621
Zhao, K., Liu, J., & Chen, H. (2022). Generative AI for educational illustrations: A user study with children. Computers in Human Behavior, 135, 107383. https://doi.org/10.1016/j.chb.2022.107383