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CHATGPT-4 IN TEACHING PHYSICS AND MATHEMATICS: OPPORTUNITIES, LIMITATIONS, AND PROSPECTS FOR IMPROVEMENT

Tribune of Young Scientists , UDC: 37 DOI: 10.24412/2072-9014-2024-470-95-115

Authors

  • Marinosyan Andreas K.

Annotation

The article discusses the possibilities of using ChatGPT-4 in teaching physics and mathematics. The strengths and weaknesses of this language model in solving educational tasks are analyzed using specific examples. The assessment of ChatGPT-4 capabilities in the field of mathematics and physics is presented according to a number of criteria, including the amount of knowledge, accuracy of information, clarity and persuasiveness of presentation, communication, ability to perform calculations, logic, multi-step problem solving, reflexivity and scientific intuition. The article notes the prospects of using large language models as an additional tool for personalizing learning and provides recommendations for effective interaction of students with ChatGPT-4.
Tags:
digital technologies; artificial intelligence; large language models; informatization of education; educational innovations

How to link insert

Marinosyan, A. K. (2024). CHATGPT-4 IN TEACHING PHYSICS AND MATHEMATICS: OPPORTUNITIES, LIMITATIONS, AND PROSPECTS FOR IMPROVEMENT Bulletin of the Moscow City Pedagogical University. Series "Pedagogy and Psychology", № 4 (70), 95. https://doi.org/10.24412/2072-9014-2024-470-95-115
References
1. 1. Kapustina L. V. ChatGPT and education: an eternal confrontation or a possible cooperation? / L. V. Kapustina, Yu. D. Ermakova, T. V. Kalyuzhnaya // Concept. 2023. № 10. P. 119–132.
2. 2. Rezaev A. V. ChatGPT and artificial intelligence in universities: what future awaits us? / A. V. Rezaev, N. D. Tregubova // Higher Education in Russia. 2023. Vol. 32, № 6. P. 19–37.
3. 3. Cooper G. Examining science education in ChatGPT: an exploratory study of generative artificial intelligence / G. Cooper // Journal of Science Education and Technology. 2023. Vol. 32, № 3. P. 444–452.
4. 4. ChatGPT in education: global reactions to AI innovations / T. Fütterer [et al.] // Scientific reports. 2023. Vol. 13, № 1. P. 15310. DOI: 10.1038/s41598–023-42227–6
5. 5. Lo C. K. What is the impact of ChatGPT on education? A rapid review of the literature / C. K. Lo // Education Sciences. 2023. Vol. 13, № 4. P. 410. DOI: 10.3390/educsci13040410
6. 6. Memarian B. ChatGPT in education: methods, potentials and limitations / B. Memarian, T. Doleck // Computers in Human Behavior: Artificial Humans. 2023. Vol. 6, № 26. P. 100152.
7. 7. Impact of the implementation of ChatGPT in education: A systematic review / M. Montenegro-Rueda [et al.] // Computers. 2023. Vol. 12, № 8. P. 153.
8. 8. Pradana M. Discussing ChatGPT in education: a literature review and bibliometric analysis / M. Pradana, H. P. Elisa, S. Syarifuddin // Cogent Education. 2023. Vol. 10, № 2. DOI: 10.3390/computers12080153
9. 9. Whalen J. ChatGPT: challenges, opportunities, and implications for teacher education / J. Whalen, C. Mouza // Contemporary Issues in Technology and Teacher Education. 2023. Vol. 23, № 1. P. 1–23.
10. 10. Wu Y. Integrating generative AI in education: how ChatGPT brings challenges for future learning and teaching / Y. Wu // Journal of Advanced Research in Education. 2023. Vol. 2, № 4. P. 6–10.
11. 11. Calonge D. S. Enough of the chit-chat: a comparative analysis of four AI chatbots for calculus and statistics [Electronic resource] / D. S. Calonge, L. Smail, F. Kamalov // Journal of Applied Learning and Teaching. 2023. Vol. 6, № 2. DOI: 10.37074/jalt.2023.6.2.22
12. 12. Educational data augmentation in physics education research using ChatGPT [Electronic resource] / F. Kieser [et al.] // Physical Review Physics Education Research. 2023. Vol. 19, № 2. DOI: 10.1103/PhysRevPhysEducRes.19.020150
13. 13. Large language models — valuable tools that require a sensitive integration into teaching and learning physics / S. Küchemann [et al.] // The Physics Teacher. 2024. Vol. 62, № 5. P. 400–402.
14. 14. Sperling A. Artificial intelligence and high school physics / A. Sperling, J. Lincoln // The Physics Teacher. 2024. Vol. 62, № 4. P. 314–315.
15. 15. Pelton T. Using generative AI in mathematics education: critical discussions and practical strategies for preservice teachers, teachers, and teacher educators / T. Pelton, L. F. Pelton // Society for Information Technology & Teacher Education International Conference. Waynesville: Association for the Advancement of Computing in Education (AACE), 2024. P. 1800–1805.
16. 16. West C. G. Advances in apparent conceptual physics reasoning in ChatGPT-4 [Electronic resource] / C. G. West // arXiv: 2303.17012 [physics.ed-ph]. URL: https://arxiv.org/abs/2303.17012
17. 17. Polverini G. How understanding large language models can inform the use of Chat-GPT in physics education [Electronic resource] / G. Polverini, B. Gregorcic // European Journal of Physics. 2024. Vol. 45, № 2. URL: https://www.fmf.uni-lj.si/en/news/event/1501/assoc-prof-dr-bor-gregorcic-u-uppsala-how-understanding-large-language-models-can-helpinform-their-use-in-physics-education/
18. 18. Feynman R. The Feynman Lectures on Physics / R. Feynman, R. Leighton, M. Sands. М.: AST, 2021. Vol. VI (8–9).
19. 19. Observation of the Phase Shift of a Neutron Due to Precession in a Magnetic Field / S. A. Werner [et al.] // Physical Review Letters. 1975. Vol. 35, № 16. P. 1053–1055.
20. 20. Steane A. M. An introduction to spinors [Electronic resource] / A. M. Steane // arXiv:1312.3824 [math-ph]. DOI: 10.48550/arXiv.1312.3824; URL: https://arxiv.org/abs/1312.3824
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