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

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.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0105/a.php" alt="Hit counter" /></p>

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Publication Details

Journal
European Journal of Open Education and E-learning Studies
Published
2025-06-20
DOI
https://doi.org/10.46827/ejoe.v10i3.6081
Primary Topic
Engineering Education and Curriculum Development
Type
article
Field-Weighted Citation Impact
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article

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

Konstantinos Τ. Kotsis
European Journal of Open Education and E-learning Studies
Engineering Education and Curriculum Development
article

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

Konstantinos Τ. Kotsis
article en

Abstract

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.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0105/a.php" alt="Hit counter" /></p>

European Journal of Open Education and E-learning StudiesVol. 10(3)
Openalex Percentile: Top 76%
Engineering Education and Curriculum Development
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