TRANSFORMING MISCONCEPTIONS INTO KNOWLEDGE: THE USE OF ARTIFICIAL INTELLIGENCE IN TEACHING ELECTROMAGNETIC RADIATION

Autori

  • Konstantinos T. Kotsis Lab of Physics Education and Teaching, Department of Primary Education, University of Ioannina, Greece

DOI:

https://doi.org/10.46827/ejoe.v10i3.6081

Ključne reči:

artificial intelligence, electromagnetic radiation, customized learning, physics education, scientific misconceptions

Apstrakt

Electromagnetic radiation (EMR) is a fundamental concept in physics and engineering education, yet it continues to be widely misconstrued due to enduring misconceptions. Conventional teaching methods frequently neglect the abstract characteristics and interdisciplinary significance of EMR, resulting in disjointed knowledge among students. This paper analyzes the incorporation of artificial intelligence (AI) as a transformative instrument to improve the instruction and comprehension of Electronic Medical Records (EMR). The paper posits that AI can enhance personalized learning, promote conceptual comprehension, and rectify misconceptions through adaptive feedback and diverse instructional resources, based on modern educational theories and empirical research. AI-driven simulations, intelligent tutoring systems, and natural language processing interfaces facilitate learners' visualization and interaction with electromagnetic phenomena, thereby connecting abstract theory to practical application. Furthermore, AI enhances formative assessment by providing real-time diagnostics of student cognition, enabling adaptive instructional strategies. The paper emphasizes particular misconceptions, such as conflating all electromagnetic radiation with ionizing radiation or misinterpreting the principle of wave-particle duality, and illustrates how AI tools can facilitate conceptual transformation. Inclusive education is prioritized, with AI improving accessibility for learners with varied needs via customizable content and interface design. The paper highlights AI's capacity to transform physics education by promoting inquiry-based, student-centered learning environments. The results support the intentional incorporation of AI technologies into science curricula to enhance scientific literacy, critical thinking, and engagement with intricate subjects such as EMR in a progressively technological society.

Biografija autora

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    Prof. Kotsis T. Konstantinos studied Physics at the Aristotle University of Thessaloniki, Greece. In 1985, he was an assistant researcher at Brooklyn University of New York. From September 1987 to September 2000, he served as an Assistant Professor specializing in Solid State Physics and X-ray Diffraction at the University of Ioannina Physics Department. Since 2000, he has served as a Faculty Member at the Department of Primary Education at the University of Ioannina. He has been a Full Professor since 2012, specializing in the Didactics of Physics at the Department of Primary Education of the University of Ioannina in Greece. He is the Head of the Department of Primary Education Physics Lab. His research interests are Didactics of Physics, Science Education, Physics Teaching and Learning, Teacher Training, and Education Research and AI in Education.

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Preuzimanja

Objavljeno

2025-06-20

Broj časopisa

God. 10 Br. 3 (2025)

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