E ISSN: 2583-049X
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International Journal of Advanced Multidisciplinary Research and Studies

Volume 6, Issue 1, 2026

Teaching Magnetism in Early and Primary Education through Technology-Enhanced Inquiry-Based Science Education STEM, Educational Robotics, and Artificial Intelligence as Mediational Approaches



Author(s): Konstantinos T Kotsis

DOI: https://doi.org/10.62225/2583049X.2026.6.1.5777

Abstract:

In early physics education, magnetism is one of the most conceptually challenging topics since it is invisible, non-contact, and relational. As young learners approach magnetic phenomena with solid intuitive conceptions that resist change, magnetism is a paradigmatic illustration of how complicated scientific ideas can be meaningfully introduced in early childhood and primary education. Recent educational reforms stress STEM integration, educational robotics, and AI to innovate early scientific teaching. The literature is fragmented, with little theory-driven synthesis of how these approaches might be systematically connected to assisting conceptual learning. This article reviews Greek and international research on teaching magnetism using STEM pedagogy, educational robotics, and artificial intelligence in early childhood and primary education. Based on constructivism, conceptual transformation, sociocultural, and constructionist views, the research investigates each approach's epistemic affordances and proposes an integrated pedagogical model that aligns action, representation, and discourse around conceptual aims. The review emphasizes the effectiveness of design-based inquiry, embodied engagement, and adaptive scaffolding in reconstructing naïve concepts and fostering relational and mechanical understanding. This study contributes to physics education debates regarding how technology-enhanced learning environments might enable deep conceptual engagement in the early years by making magnetism a privileged case for integrated pedagogy.


Keywords: Magnetism, Early Childhood, Primary Education, STEM Education, Educational Robotics, Artificial Intelligence in Education

Pages: 2103-2113

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