The Effectiveness of Mathematics Learning Media Developed with Artificial Intelligence (AI) Assistance in Training Basic Arithmetic Skills

Authors

  • Husnu Athoillah Institut Al Fithrah Surabaya, Indonesia
  • Risma Firda Diana Institut Al Fithrah Surabaya, Indonesia

DOI:

https://doi.org/10.61987/educazione.v3i2.2430

Keywords:

Artificial Intelligence, Arithmetic Skills, Elementary Mathematics, Mathematics Learning Media

Abstract

Limited integration of artificial intelligence into elementary mathematics instruction continues to constrain opportunities for students to develop basic arithmetic skills through engaging learning experiences. Addressing this challenge, the present study examined the effectiveness of AI-assisted mathematics learning media developed through the pedagogical integration of ChatGPT and Canva AI for second-grade students. A quantitative pre-experimental approach employing a one-group pretest-posttest design was implemented with 25 participants selected through purposive sampling. Data were collected using expert validation sheets and students' arithmetic achievement tests. The learning media and assessment instruments were first evaluated for validity, after which students completed pretest and posttest assessments. Data analysis was performed using descriptive statistics, normality testing, and the Wilcoxon Signed-Rank Test. Expert evaluation classified both the learning media and the assessment instrument as highly valid, confirming their suitability for classroom implementation. Students' arithmetic achievement improved significantly following the intervention, demonstrating that the developed learning media effectively strengthened basic arithmetic skills. These findings indicate that the educational value of generative AI extends beyond content generation by supporting the design of interactive, visually engaging, and learner-centered mathematics instruction. Integrating ChatGPT and Canva AI therefore represents a promising instructional approach for enhancing foundational numeracy learning in elementary education.

References

Avdiu, E. (2019). Game-Based Learning Practices in Austrian Elementary Schools. Educational Process: International Journal, 8(3), 196–206. https://doi.org/10.22521/edupij.2019.83.4

Bhutoria, A. (2022). Personalized Education and Artificial Intelligence in the United States, China, and India: A Systematic Review Using a Human-In-The-Loop Model. Computers and Education: Artificial Intelligence, 3, 100068. https://doi.org/10.1016/j.caeai.2022.100068

Canonigo, A. M. (2024). Levering AI to Enhance Students’ Conceptual Understanding and Confidence in Mathematics. Journal of Computer Assisted Learning, 40(6), 3215–3229. https://doi.org/10.1111/jcal.13065

Carter, G., Wilson, C. B., & Mitchell, G. (2021). The Effectiveness of a Digital Game to Improve Public Perception of Dementia: A Pretest-Posttest Evaluation. PLoS ONE, 16(10), e0257337. https://doi.org/10.1371/journal.pone.0257337

Chang, S. J., Lee, K. E., Yang, E., & Ryu, H. (2022). Evaluating a Theory-Based Intervention for Improving eHealth Literacy in Older Adults: A Single Group, Pretest–Posttest Design. BMC Geriatrics, 22(1). https://doi.org/10.1186/s12877-022-03545-y

Choi, G. W., Kim, S. H., Lee, D., & Moon, J. (2024). Utilizing Generative AI for Instructional Design: Exploring Strengths, Weaknesses, Opportunities, and Threats. TechTrends, 68(4), 832–844. https://doi.org/10.1007/s11528-024-00967-w

Deng, L., Wu, S., Chen, Y., & Peng, Z. (2020). Digital Game-Based Learning in a Shanghai Primary-School Mathematics Class: A Case Study. Journal of Computer Assisted Learning, 36(5), 709–717. https://doi.org/10.1111/jcal.12438

Ding, A. C. E., & Yu, C. H. (2024). Serious Game-Based Learning and Learning by Making Games: Types of Game-Based Pedagogies and Student Gaming Hours Impact Students’ Science Learning Outcomes. Computers and Education, 218, 105075. https://doi.org/10.1016/j.compedu.2024.105075

Go, B., Lim, C., & Shin, B. (2024). Development of a Math-AI Convergence Instructional Model Using a Generative AI Chatbot. Journal of Educational Technology, 39(3), 1–40. https://doi.org/10.17232/kset.40.1.1

Horváth, L., Kokoszka, P., & Wang, S. (2020). Testing Normality of Data on a Multivariate Grid. Journal of Multivariate Analysis, 179, 104640. https://doi.org/10.1016/j.jmva.2020.104640

Howard, S. R., & Pimentel, S. D. (2021). The Uniform General Signed Rank Test and Its Design Sensitivity. Biometrika, 108(2), 381–396. https://doi.org/10.1093/biomet/asaa072

Ingkavara, T., Panjaburee, P., Srisawasdi, N., & Sajjapanroj, S. (2022). The Use of a Personalized Learning Approach to Implementing Self-Regulated Online Learning. Computers and Education: Artificial Intelligence, 3, 100086. https://doi.org/10.1016/j.caeai.2022.100086

Little, T. D., Chang, R., Gorrall, B. K., Waggenspack, L., Fukuda, E., Allen, P. J., & Noam, G. G. (2020). The Retrospective Pretest–Posttest Design Redux: On Its Validity as an Alternative to Traditional Pretest–Posttest Measurement. International Journal of Behavioral Development, 44(2), 175–183. https://doi.org/10.1177/0165025419877973

Luo, T., Muljana, P. S., Ren, X., & Young, D. (2025). Exploring Instructional Designers’ Utilization and Perspectives on Generative AI Tools: A Mixed Methods Study. Educational Technology Research and Development, 73(2), 741–766. https://doi.org/10.1007/s11423-024-10437-y

Maamin, M., Maat, S. M., & Iksan, Z. H. (2022). The Influence of Student Engagement on Mathematical Achievement Among Secondary School Students. Mathematics, 10(1), 41. https://doi.org/10.3390/math10010041

Madunić, J., & Sovulj, M. (2024). Application of ChatGPT in Information Literacy Instructional Design. Publications, 12(2), 11. https://doi.org/10.3390/publications12020011

Maier, U., & Klotz, C. (2022). Personalized Feedback in Digital Learning Environments: Classification Framework and Literature Review. Computers and Education: Artificial Intelligence, 3, 100080. https://doi.org/10.1016/j.caeai.2022.100080

Makigusa, N., & Naito, K. (2020). Asymptotics and Practical Aspects of Testing Normality with Kernel Methods. Journal of Multivariate Analysis, 180, 104665. https://doi.org/10.1016/j.jmva.2020.104665

Martini, V., Favero, F., Corà, D., Varughese, F., Sica, A., & Gennari, A. (2020). Abstract P3-05-09: mRNA Expression Level and Prognostic Significance of Different Immune-Related Biomarkers in Early Breast Cancer. Cancer Research, 80(4), P3-05-09. https://doi.org/10.1158/1538-7445.sabcs19-p3-05-09

Nadeem, M., Oroszlanyova, M., & Farag, W. (2023). Effect of Digital Game-Based Learning on Student Engagement and Motivation. Computers, 12(9). https://doi.org/10.3390/computers12090177

Partovi, T., & Razavi, M. R. (2019). The Effect of Game-Based Learning on Academic Achievement Motivation of Elementary School Students. Learning and Motivation, 68, 101592. https://doi.org/10.1016/j.lmot.2019.101592

Ramos, L., Simões, V., & Franco, S. (2024). “Active Mathematics”—A Classroom-Based Physical Active Learning Intervention in an Elementary School: An Experimental Pilot Study. Education Sciences, 14(6), 637. https://doi.org/10.3390/educsci14060637

Relmasira, S. C., Lai, Y. C., & Donaldson, J. P. (2023). Fostering AI Literacy in Elementary Science, Technology, Engineering, Art, and Mathematics (STEAM) Education in the Age of Generative AI. Sustainability, 15(18), 13595. https://doi.org/10.3390/su151813595

Rich, K. M. (2021). Examining Agency as Teachers Use Mathematics Curriculum Resources: How Professional Contexts May Support or Inhibit Student-Centered Instruction. Teaching and Teacher Education, 98, 103249. https://doi.org/10.1016/j.tate.2020.103249

Schorcht, S., Buchholtz, N., & Baumanns, L. (2024). Prompt the Problem – Investigating the Mathematics Educational Quality of AI-Supported Problem Solving by Comparing Prompt Techniques. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1386075

Sein, M. (2022). AI-Assisted Knowledge Assessment Techniques for Adaptive Learning Environments. Computers and Education: Artificial Intelligence, 3, 100050. https://doi.org/10.1016/j.caeai.2022.100050

Squalli Houssaini, M., Aboutajeddine, A., Toughrai, I., & Ibrahimi, A. (2024). Development of a Design Course for Medical Curriculum: Using Design Thinking as an Instructional Design Method Empowered by Constructive Alignment and Generative AI. Thinking Skills and Creativity, 52, 101491. https://doi.org/10.1016/j.tsc.2024.101491

Wang, Y. (2020). Engagement in PC-Based, Smartphone-Based, and Paper-Based Materials: Learning Vocabulary Through Chinese Stories. Technology in Language Teaching & Learning, 2(1), 3–21. https://doi.org/10.29140/tltl.v2n1.319

Zhang, J., & Zhang, Z. (2024). AI in Teacher Education: Unlocking New Dimensions in Teaching Support, Inclusive Learning, and Digital Literacy. Journal of Computer Assisted Learning, 40(4), 1871–1885. https://doi.org/10.1111/jcal.12988

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Published

2026-06-30

How to Cite

Athoillah, H., & Diana, R. F. (2026). The Effectiveness of Mathematics Learning Media Developed with Artificial Intelligence (AI) Assistance in Training Basic Arithmetic Skills. Educazione: Journal of Education and Learning, 3(2), 312–322. https://doi.org/10.61987/educazione.v3i2.2430

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Articles