Artificial Intelligence in Physics Classrooms: Comparative Perspectives on ChatGPT and DeepSeek as Learning Supports

Konstantinos T. Kotsis

doi:10.59652/xf577b82

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Published: 2025-12-24

DOI: https://doi.org/10.59652/xf577b82

Keywords:

ChatGPT, DeepSeek, physics education, artificial intelligence, pedagogy

Konstantinos T. Kotsis

University of Ioannina

Abstract

This study presents a conceptual comparative analysis of two advanced AI-driven platforms, ChatGPT and DeepSeek, within the context of physics education. It explores how these systems can serve as complementary learning supports that enhance conceptual understanding, inquiry, and problem-solving in classroom settings. ChatGPT’s dialogic and adaptive interaction style fosters exploratory learning, metacognitive reflection, and conceptual clarification, aligning well with constructivist and inquiry-based pedagogies. In contrast, DeepSeek’s precision-oriented architecture and iterative refinement processes lend themselves to structured problem-solving and cognitive efficiency, supporting students in procedural and computational tasks. Together, these affordances illustrate how distinct AI designs can address different dimensions of physics learning. The analysis also examines emerging ethical and pedagogical challenges, including issues of academic integrity, cognitive dependency, and algorithmic bias, underscoring the importance of teacher mediation and institutional regulation. The study concludes that, when thoughtfully integrated, AI tools like ChatGPT and DeepSeek can enrich physics education by balancing conceptual exploration with procedural rigor, while emphasizing the need for ethical literacy and transparent frameworks in their classroom use.

Issue

Vol. 3 No. 4 (2025): EIKI Journal of Effective Teaching methods

Section

Concept Paper

This work is licensed under a Creative Commons Attribution 4.0 International License.

Author Biography

Konstantinos T. Kotsis, University of Ioannina

Konstantinos T. Kotsis 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 Lecturer and 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 was the Head of the Department of Primary Education and the Dean of the School of Education at the University of Ioannina. Now he is the Head of the Lab of Physics Education and Teaching at the Department of Primary Education. His research interests are Didactics of Physics, Science Education, Physics Teaching and Learning, Teacher Training, and Education Research and AI in Science Education.

How to Cite

Kotsis, K. T. (2025). Artificial Intelligence in Physics Classrooms: Comparative Perspectives on ChatGPT and DeepSeek as Learning Supports. EIKI Journal of Effective Teaching Methods, 3(4). https://doi.org/10.59652/xf577b82

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