Home Releases № 2 (72)

ADAPTIVE LEARNING USING NEURAL NETWORKS: EXPERIENCE AND PROSPECTS

Artificial Intelligence in Education , UDC: 378 DOI: 10.24412/2072-9014-2025-272-32-45

Authors

  • Sadykova Albina R. Doctor of Pedagogical Sciences, Associate Professor
  • Trukhmanov Dmitry V.

Annotation

The article discusses the possibilities of using neural networks for adaptive learning programming. The main problems that teachers face when teaching programming in schools are analyzed, this approach using neural networks to analyze the number of students, presented as an example of the implementation of an adaptive learning system.

How to link insert

Sadykova, A. R. & Trukhmanov, D. V. (2025). ADAPTIVE LEARNING USING NEURAL NETWORKS: EXPERIENCE AND PROSPECTS Bulletin of the Moscow City Pedagogical University. Series "Pedagogy and Psychology", № 2 (72), 32. https://doi.org/10.24412/2072-9014-2025-272-32-45
References
1. 1. Arkabaev N. Learning Python at school: problems and effective methods / N. Arkabaev, A. Kuduev, A. Sulaimanov // Journal of Osh State University. Pedagogy. Psychology. 2023. № 1 (2). P. 24–29. URL: https://cyberleninka.ru/article/n/obuchenie-yazyka-py-thon-v-shkole-problemy-i-effektivnye-metody (accessed: 12.15.2024).
2. 2. Balatsky E. V. The use of neural networks to predict inflation: new opportunities / E. V. Balatsky, M. A. Yurevich // Bulletin of UrFU. Economics and Management series. 2018. Vol. 17. No. 5. P. 823–838.
3. 3. Gerbekov H. A. Object-oriented programming in the school computer science course / H. A. Gerbekov, O. P. Bashkaeva // RUDN Journal of Informatization in Education. 2017. Vol. 14. No. 2. P. 156–160.
4. 4. Glukhov A. P. Digital literacy of teachers: conceptualization and monitoring / A. P. Glukhov, O. S. Kamneva, I. G. Solomina // Pedagogical Review. 2022. Issue 5 (45). P. 39–47. URL: https://cyberleninka.ru/article/n/tsifrovaya-gramotnost-pedagogov-kontsep-tualizatsiya-i-monitoring (accessed: 12.15.2024).
5. 5. Bosova L. L. Computer Science. 11th grade. The basic level. Independent and control work / L. L. Bosova, A. Yu. Bosova, N. A. Aquilyanov. Moscow: Prosveshchenie, 2024. 96 p.
6. 6. Kozlov O. A. Necessary competencies of a school graduate in the field of information technology in the context of an acute shortage of IT specialists / O. A. Koz lov, I. V. Barysheva // Bulletin of Cherepovets State University. 2024. No. 3 (120). P. 213–230.
7. 7. Sadykova A. R. Artificial intelligence as a component of the innovative content of general education: an analysis of world experience and domestic prospects / A. R. Sadykova, I. V. Levchenko // RUDN Journal of Informatization in Education. 2020. Vol. 17. No. 3. P. 201–209.
8. 8. Tarasova V. S. Methodological features of teaching object-oriented programming in a school computer science course / V. S. Tarasova, A. R. Nafikova // Bulletin of the Bashkir State Pedagogical University named after M. Akmulla. 2022. No. 1-4 (62). P. 112–113.
9. 9. Ostanina A. YandexGPT: what the neural network from Yandex can do and how to use it. December 24, 2024 // Skillfactory media. URL: https://blog.skillfactory.ru/yandexgpt-chto-umeet-neyroset-ot-yandeksa-i-kak-ey-polzovatsya / (accessed: 12.15.2024).
10. 10. Lapchin A. The expert reported on the shortage of computer science teachers in Russian schools. 26.01.2023 // Parliamentary newspaper: [website]. URL: https://www.pnp.ru/economics/v-rossiyskikh-shkolakh-nablyudaetsya-deficit-uchiteley-informatiki.html (accessed: 12.15.2024).
Download file .pdf 620.75 kb