Integration of Artificial Intelligence in K-12: Analysis of a Three-Year Pilot Study

Abstract

A three-year pilot study investigated the effectiveness of artificial intelligence (AI) as a motivational tool for teaching programming concepts within the Croatian Informatics curriculum. The study was conducted in schools through the extracurricular activity EDIT CodeSchool with the Development of Intelligent Web Applications (RIWA) module. Twelve schools in Split-Dalmatia County in the Republic of Croatia participated, resulting in 112 successfully completed student projects. The program consisted of two phases: (1) theoretical instruction with examples and exercises, and (2) project-based learning, where students developed final projects using JavaScript and the ml5.js library. The study employed project analysis and semi-structured student interviews to assess learning outcomes. Findings suggest that AI-enhanced learning can effectively support programming education without increasing instructional hours, providing insights for integrating AI concepts into existing curricula. © 2025 by the authors.

Keywords

Author Keywords

Project-Based Learning Artificial intelligence in education AI literacy extra-curricular activities programming for children

Index Keywords

Author Affiliations

Faculty of Science, University of Split, Split, Split-Dalmatia, Croatia

Funding & Acknowledgements

No funding information

References 10 References

1 Lee, Sang Joon, 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, (2024)

2 Michaeli, Tilman, What Students Can Learn About Artificial Intelligence – Recommendations for K-12 Computing Education, IFIP Advances in Information and Communication Technology, 685 AICT, pp. 196-208, (2023)

3 Su, Jiahong, Teaching artificial intelligence in K–12 classrooms: a scoping review, Interactive Learning Environments, 32, 9, pp. 5207-5226, (2024)

4 Pearce, Kate, Build-a-Bot: Teaching Conversational AI Using a Transformer-Based Intent Recognition and Question Answering Architecture, Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023, 37, pp. 16025-16032, (2023)

5 Webb, Mary E., Machine learning for human learners: opportunities, issues, tensions and threats, Educational Technology Research and Development, 69, 4, pp. 2109-2130, (2021)

6 Lin, Phoebe, Engaging teachers to co-design integrated ai curriculum for k-12 classrooms, Conference on Human Factors in Computing Systems - Proceedings, (2021)

7 Velander, Johanna, Artificial Intelligence in K-12 Education: eliciting and reflecting on Swedish teachers' understanding of AI and its implications for teaching & learning, Education and Information Technologies, 29, 4, pp. 4085-4105, (2024)

8 Lane, H. Chad, Commentary for the International Journal of Artificial Intelligence in Education Special Issue on K-12 AI Education, International Journal of Artificial Intelligence in Education, 33, 2, pp. 427-438, (2023)

9 Kaspersen, Magnus Høholt, VotestratesML: A High School Learning Tool for Exploring Machine Learning and its Societal Implications, ACM International Conference Proceeding Series, (2021)

10 Kim, Seounghun, Why and What to Teach: AI Curriculum for Elementary School, 35th AAAI Conference on Artificial Intelligence, AAAI 2021, 17B, pp. 15569-15576, (2021)

Integration of Artificial Intelligence in K-12: Analysis of a Three-Year Pilot Study

How to Cite