11th International Scientific Conference Technics, Informatics and Education – TIE 2026, (pp. 65-70)
AUTOR(I) / AUTHOR(S): Nikola Vojtek 
, Vladan Pantović
DOI: https://doi.org/10.46793/TIE26.065V
SAŽETAK /ABSTRACT:
Artificial intelligence (AI) is becoming a foundational competency for future education and employment, yet introductory AI education frequently emphasizes programming and software tools that may discourage younger learners. This paper proposes the Tangible Artificial Intelligence Learning (TAIL) Framework, a pedagogical approach that combines interactive learning cards to develop AI literacy before students begin technical implementation. The framework integrates Agilist Brain Challenge Zone Learning Cards, which cultivate critical thinking, systems thinking and collaborative reasoning, with Agilist AI Playing Cards. Proposed TAIL framework is focused on AI concepts, responsible AI, ethics, governance, prompting and human–AI collaboration through scenario-based learning. The proposed methodology follows experiential and constructivist learning principles, enabling students to actively discuss, negotiate and justify decisions instead of passively memorizing definitions. Because the framework requires no prior programming knowledge or expensive digital infrastructure, it is particularly suitable for secondary education and introductory undergraduate courses. The paper presents the educational motivation, pedagogical foundations, classroom implementation model, expected learning outcomes and future research directions. The framework demonstrates how tangible educational assets can complement digital AI tools while improving engagement, knowledge retention and responsible AI understanding.
KLJUČNE REČI / KEYWORDS:
Artificial Intelligence Education; AI Literacy; Tangible Learning; Interactive Learning Cards; Systems Thinking
PROJEKAT / ACKNOWLEDGEMENT:
LITERATURA / REFERENCES:
- Vojtek, N. & Pantovic, V. (2026). Next-Generation Project Management: Artificial Intelligence and Agility. University of Educons, Belgrade, Serbia.
- Long, D., & Magerko, B. (2020). What Is AI Literacy? Competencies and Design Considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI ’20), 1–16. https://doi.org/10.1145/3313831.3376727
- UNESCO. (2024). AI Competency Framework for Students. Paris: UNESCO.
- Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign.
- Kolb, D. A. (1984). Experiential Learning: Experience as the Source of Learning and Development. Englewood Cliffs, NJ: Prentice Hall.
- Bloom, B. S. (Ed.). (1956). Taxonomy of Educational Objectives: Handbook I: Cognitive Domain. New York: David McKay.
- Gee, J. P. (2003). What Video Games Have to Teach Us About Learning and Literacy. New York: Palgrave Macmillan.
- Prensky, M. (2001). Digital Game-Based Learning. New York: McGraw-Hill.
- AI4K12 Initiative. (2020). AI4K12: Five Big Ideas in Artificial Intelligence. https://ai4k12.org
- OECD. (2021). OECD Digital Education Outlook 2021: Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots. Paris: OECD Publishing.
- Ishii, H., & Ullmer, B. (1997). Tangible Bits: Towards Seamless Interfaces between People, Bits and Atoms. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’97), 234–241.
- ISO/IEC 42001:2023. Information Technology — Artificial Intelligence — Management System (AIMS) — Requirements. Geneva: International Organization for Standardization.
- NIST. (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). National Institute of Standards and Technology. https://doi.org/10.6028/NIST.AI.100-1