Bridging the Abstract and the Tangible: A Meta-Analysis of AI Literacy Pedagogies, Tools, and Developmental Outcomes in Elementary School Settings
DOI:
https://doi.org/10.17509/mimbar-sd.v13i3.118Keywords:
AI Literacy, Tangible AI, Elementary Education, AI-PCK, Embodied CognitionAbstract
The integration of artificial intelligence (AI) into modern life has fundamentally changed human-technology interaction, demanding a paradigm shift in education. Developing AI literacy must begin early to prepare children for a future where AI competency is as essential as reading, writing, and arithmetic. Despite this urgency, instilling AI literacy in young children remains a significant challenge, largely due to the limited availability of developmentally appropriate tools and curricula tailored to elementary students’ cognitive and socio-emotional capacities. This study examines the effectiveness of learning interventions that integrate AI literacy and tangible AI in elementary education. The researchers selected meta-analysis studies published between 2010 and 2025 from indexing databases including Scopus, Web of Science, EBSCO/Proquest, SINTA, and Google Scholar. The collected articles focused on how AI literacy is taught at the elementary level. The filtered data included learning design, assessment methods, and learning outcomes. A total of 13 independent studies were included in the meta-analysis, which analyzed average effect sizes. Results, processed using JASP software, indicate that effective implementation of teaching aids—whether software-based or tangible AI—significantly improves students’ understanding of AI concepts and their ability to apply AI to real-world challenges. The findings also underscore the importance of embedding AI literacy within subject-matter instruction rather than teaching it in isolation, which risks losing context and relevance.
References
Anderson, J. R. (2020). Cognitive Psychology and its Implications (9th ed.). Worth Publishers.
Anzures-Cabrera, J., & Higgins, J. P. (2010). Graphical Displays for Meta-Analysis: An Overview with Suggestions for Practice. Research Synthesis Methods, 1(1), 66-80. https://doi.org/10.1002/jrsm.6
Aravantinos, S., Lavidas, K., Voulgari, I., Papadakis, S., Karalis, T., & Komis, V. (2024). Educational Approaches with AI in Primary School Settings: A Systematic Review of the Literature Available in Scopus. Educational Sciences, 14(7), Article 744. https://doi.org/10.3390/educsci14070744
Arranz-García, O., García, M. d., & Alonso-Secades, V. (2025). Perceptions, Strategies, and Challenges of Teachers in the Integration of Artificial Intelligence in Primary Education: A Systematic Review. Journal of Information Technology Education: Research, 24, Article 6. https://doi.org/10.28945/5458
Bagdonaite, J., & Dagiene, V. (2025). Artificial Intelligence in Primary Education: A Systematic Literature Review 2020–2025. Informatics in Education, 24(4), 697-736. https://doi.org/10.15388/infedu.2025.24
Balangitan, D. M., Bidang, J. B., & Dano, C. B. (2025). From Access to Application: Exploring Educators’ Experiences with Technology Integration. Cognizance Journal of Multidisciplinary Studies, 5(8), 508-521. https://doi.org/10.47760/cognizance.2025.v05i08.020
Bell, T., & Lodi, M. (2019). Constructing Computational Thinking Without Using Computers. Constructivist Foundations, 14(3), 342-351. https://constructivist.info/14/3/342
Biswas, G., Schwartz, D., Leelawong, K., & Vye, N. (2005). Learning by Teaching: A New Agent Paradigm for Educational Software. Applied Artificial Intelligence, 19(3-4), 363-392. https://doi.org/10.1080/08839510590910200
Blanch, A., Escorial, S., & Colom, R. (2025). Developmental Changes in High Cognitive Ability Children: The Role of Nature and Nurture. Intelligence & Cognitive Abilities, 1(2), 1-17. https://doi.org/10.65550/001c.144062
Borenstein, M., Hedges, L. V., Higgins, J. P., & Rothstein, H. R. (2011). Introduction to Meta-Analysis. John Wiley & Sons.
Brennan, K., & Resnick, M. (2012). New frameworks for studying and assessing the development of computational thinking. Proceedings of the 2012 Annual Meeting of the American Educational Research Association (AERA). American Educational Research Association. http://scratched.gse.harvard.edu/ct/files/AERA2012.pdf
Chakraburty, S., Glazewski, K. D., Hmelo-Silver, C. E., Valdivia, D. S., Ottenbreit-Leftwich, A., Mott, B., & Lester, J. (2025). Measuring upper-elementary students' understanding of AI concept - a Rasch Model Analysis. Information and Learning Sciences, 126(7-8), 445-471. https://doi.org/10.1108/ILS-10-2023-0164
Cooper, H., Hedges, L. V., & Valentine, J. C. (Eds.). (2019). The Handbook of Research Synthesis and Meta-Analysis (3rd ed.). Russell Sage Foundation. https://doi.org/10.7758/9781610448864
Duran, D. (2017). Learning-by-teaching. Evidence and Implications as a Pedagogical Mechanism. Innovations in Education and Teaching International, 54(5), 476-484. https://doi.org/10.1080/14703297.2016.1156011
Fernández-Batanero, J. M., Montenegro-Rueda, M., Fernández-Cerero, J., & López-Meneses, E. (2024). Extended Reality as an Educational Resource in the Primary School Classroom: An Interview of Drawbacks and Opportunities. Computers, 13(2), Article 50. https://doi.org/10.3390/computers13020050
Fiorella, L. (2023). Learning by Teaching. In C. E. Overson, C. M. Hakala, L. L. Kordonowy, & V. A. Benassi (Eds.), In Their Own Words: What Scholars and Teachers Want You to Know About Why and How to Apply the Science of Learning in Your Academic Setting (pp. 158-170). Society for the Teaching of Psychology.
Fombona, J., Sáez, J.-M., & Sánchez, S. (2025). Artificial Intelligence and Robotics in Education: Advances, Challenges, and Future Perspectives. Social Sciences & Humanities Open, 11, Article 101533. https://doi.org/10.1016/j.ssaho.2025.101533
Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active Learning Increases Student Performance in Science, Engineering, and Mathematics. Proceedings of the National Academy of Science , 111 (23), pp. 8410-8415. https://doi.org/10.1073/pnas.1319030111
Gupta, A., Lee, S., Mott, B., Chakraburty, S., Glazewski, K., Ottenbreit-Leftwich, A., Scribner, A., Hmelo-Silver, C. E., & Lester, J. (2024). Supporting Upper Elementary Students in Learning AI Concepts with Story-Driven Game-Based Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 38 (21), pp. 23092-23100. https://doi.org/10.1609/aaai.v38i21.30354
Jeon, M., Jantaraweragul, K., Ottenbreit-Leftwich, A., Hmelo-Silver, C., Glazewski, K., Mott, B., Lester, J., & Ringstaff, C. (2024). An Inquiry-Based Artificial Intelligence Curriculum for Upper Elementary Students: A Design Case of Primaryai. International Journal of Design for Learning, 15(3), 94-108. https://doi.org/10.14434/ijdl.v15i3.36757
Kim, K., & Kwon, K. (2024). Tangible Computing Tools in AI Education: Approach to Improve Elementary Students' Knowledge, Perception, and Behavioral Intention Towards AI. Education and Information Technologies, 29(13), 16125-16156. https://doi.org/10.1007/s10639-024-12497-2
Kirsh, D. (2010). Thinking with External Representations. AI & Society, 25, 441-454. https://doi.org/10.1007/s00146-010-0272-8
Koray, A., & Uzunçelebi, B. H. (2023). The Effect of Educational Robotics Applications in Science Education on Students' Academic Achievement and Problem-Solving Skills. Journal of Education in Science, Environment and Health (JESEH), 9(4), 317-329. https://doi.org/10.55549/jeseh.1381251
Landis, J. R., & Koch, G. G. (1977). The Measurement of Observer Agreement for Categorical Data. Biometrics, 33(1), 159-174. https://doi.org/10.2307/2529310
Levesque, H. J. (2012). Thinking as Computation - A First Course. MIT Press.
Levin, I., Semenov, A. L., & Gorsky, M. (2025). Smart Learning in the 21st Century: Advancing Constructionism Across Three Digital Epochs. Education Sciences, 15(1), Article 45. https://doi.org/10.3390/educsci15010045
Lodi, M., & Martini, S. (2021). Computational thinking, between Papert and Wing. Science & Education, 30, 883-908. https://doi.org/10.1007/s11191-021-00202-5
Macrine, S. L., & Fugate, J. M. (2020). Embodied Cognition. Oxford Research Encyclopedia of Education. https://doi.org/10.1093/acrefore/9780190264093.013.885
Marshall, P. (2007). Do Tangible Interfaces Enhance Learning? TEI '07: Proceedings of the 1st International Conference on Tangible and Embedded Interaction (pp. 163-170). ACM. https://doi.org/10.1145/1226969.1227004
Memari, M., & Ruggles, K. (2025). Artificial Intelligence in Elementary STEM Education: A Systematic Review of Current Applications and Future Challenges. arXiv preprint. arXiv: 2511.00105. https://doi.org/10.48550/arXiv.2511.00105
Merleau-Ponty, M. (2012). Phenomenology of Perception. Routledge. https://ia800600.us.archive.org/17/items/G.BachelardThePoeticsOfSpace/Phenomenology%20of%20Perception.pdf
Papert, S. A. (2020). Mindstorms - Children, Computers and Powerful Ideas (Revised ed.). Basic Books.
Rothstein, H. R., Sutton, A. J., & Borenstein, M. (Eds.). (2005). Publication Bias in Meta‐Analysis: Prevention, Assessment and Adjustments. Wiley. https://doi.org/10.1002/0470870168
Ryan, R. M., & Deci, E. L. (2000). Self-Determination Theory and the Facilitation of Intrinsic Motivation, Social Development, and Well-Being. American Psychologist, 55(1), 68-78. https://doi.org/10.1037/0003-066X.55.1.68
Sampanis, N. (2025). Innovative Tangible Interactive Games for Enhancing Artificial Intelligence Knowledge and Literacy in Elementary Education: A Pedagogical Framework. arXiv preprint. arXiv:2506.00651. https://doi.org/10.48550/arXiv.2506.00651
Sesay, I. M., & Sesay, G. A. (2024). Redefining Student Assessments in the Age of AI-Assisted Learning Strategies for Educators. Global Scientific Journals, 12(8), 704-721. https://doi.org/10.11216/gsj.2024.08.229058
Shapiro, L., & Spaulding, S. (2021). Embodied Cognition. Stanford Encyclopedia of Philosophy. https://plato.stanford.edu/entries/embodied-cognition/
Suryadi, N., Zulfikar, R., Prasarry, Y. V., & Islam, M. F. (2025). AI product knowledge as moderator of trust and attitude in usage intention: a study of Indonesian postgraduates. Cogent Social Sciences, 11(1), Article 2526799. https://doi.org/10.1080/23311886.2025.2526799
Tayeh, S. A. (2025). Integrating Artificial Intelligence into Curriculum Design: Strategies for Enhancing Teaching Methods in Primary Education. TPM – Testing, Psychometrics, Methodology in Applied Psychology, 32, S4. https://tpmap.org/submission/index.php/tpm/article/view/1046
Tomczyk, B. (2024). The Locus of Agency in Extended Cognitive Systems. Journal for General Philosophy of Science, 55, 579–604. https://doi.org/10.1007/s10838-023-09666-1
Tyler, S. (2020). Cognitive Development in Middle Childhood. In Human Behavior and the Social Environment I. University of Arkansas Libraries. https://doi.org/10.54119/ZITK3624
Umur, E., Ureten, I., Koca, K., & Yalcin, S. (2026). Parse: Teaching How AI Learns Through Tangible Unplugged Modules. IDC '26: Proceedings of the 25th Annual ACM Interaction Design and Children Conference (pp. 1257-1260). ACM. https://doi.org/10.1145/3773077.3812137
Wilson, B. G., & Myers, K. M. (2000). Situated Cognition in Theoretical and Practical Context. In D. Jonassen, & S. Land (Eds.), Theoretical Foundations of Learning Environments (pp. 57-88). Erlbaum.
Wilson, M. (2002). Six views of embodied cognition. Psychonomic Bulletin & Review, 9, 625-636. https://doi.org/10.3758/BF03196322
Yim, I. H. (2024). A critical review of teaching and learning artificial intelligence (AI) literacy: Developing an intelligence-based AI literacy framework for primary school education. Computers and Education: Artificial Intelligence, 7, Article 100319. https://doi.org/10.1016/j.caeai.2024.100319
Yim, I. H., & Su, J. (2025). Artificial intelligence literacy education in primary schools: a review. International Journal of Technology and Design Education, 35(5), 2175-2204. https://doi.org/10.1007/s10798-025-09979-w
Zhang, X., Ding, Y., Huang, X., Li, W., Long, L., & Ding, S. (2024). Smart Classrooms: How Sensors and AI Are Shaping Educational Paradigms. Sensors, 24(17), Article 5487. https://doi.org/10.3390/s24175487
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