Home → Releases → № 2 (72) →

QUESTION – ANSWER PLATFORM BASED ON ARTIFICIAL INTELLIGENCE TECHNOLOGIES AS A TOOL FOR TEACHING PROGRAMMING

Artificial Intelligence in Education , UDC: 004.9 DOI: 10.24412/2072-9014-2025-272-7-19

Authors

  • Grineva Elizaveta S.
  • Shunina Lubov Andreevna Candidate of Pedagogical Sciences, Associate Professor
  • Proleev George N.
  • Dzhebilov Alexander V.

Annotation

The article describes approaches to the development of an intelligent Question – Answer platform based on artificial intelligence technologies and designed to search for educational and reference information when teaching programming. The relevance is due to the need to solve the problem associated with the limited availability of qualified assistance in the process of learning programming, especially in the context of independent work and distance education. The implementation using the development of algorithms for classifying questions, building a knowledge base and using neural networks to generate answers is described. The integration of modern NLP models with an adaptive recommendation system is proposed to take into account the context of requests and to improve the quality of the answers received.
Tags:
teaching programming; artificial intelligence; NLP model; informatization of education

How to link insert

Grineva, E. S., Shunina, L. A., Proleev, G. N. & Dzhebilov, A. V. (2025). QUESTION – ANSWER PLATFORM BASED ON ARTIFICIAL INTELLIGENCE TECHNOLOGIES AS A TOOL FOR TEACHING PROGRAMMING Bulletin of the Moscow City Pedagogical University. Series "Pedagogy and Psychology", № 2 (72), 7. https://doi.org/10.24412/2072-9014-2025-272-7-19
References
1. 1. Abdyukhanov R. H. Modern {digital} didactics / R. H. Abdyukhanov, V. I. Abramov, S. I. Ashmanov [et al.]. Moscow: A-Prior LLC, 2023. 140 p.
2. 2. Abramycheva N. L. Selected issues of digital transformation of education / N. L. Abramycheva, A. Y. Adaikina, O. V. Andryushkova [et al.]. Moscow: INFRA-M, 2024. 188 p.
3. 3. Soboleva E. V. Applying Gamification in Learning the Basics of Algorithmization and Programming to Improve the Quality of Students’ Educational Results / E. V. Soboleva, T. N. Suvorova, A. V. Grinshkun, M. I. Bocharov // European Journal of Contemporary Education, 2021. Vol. 10. №. 4. P. 987–1002.
4. 4. Burkov A. Machine learning engineering / A. Burkov. Moscow: DMK Press, 2022. 306 p.
5. 5. Azevich A. I. Providing personal development trajectories for students in the context of informatization of education: a teaching aid / A. I. Azevich, V. V. Grinshkun, O. Yu. Zaslavskaya [et al.]. Moscow: MCU, 2021. 112 p.
6. 6. Eliseev A. V. On the possibilities of using generative neural networks in the preparation of educational materials on the discipline «Modern information technologies» / A. V. Eliseev, N. S. Korneva // Shamov readings: сollection of ar ticles of the XVI International Scientific and Practical Conference. In 2 vol. (Moscow, January 25 – February 03, 2024). Moscow: Scientific School of Educational Systems Management, 2024. P. 531–533.
7. 7. Goncharova L. G. Digitalization of the processes of modernization of the higher education system as a factor of personnel training for the digital economy / L. G. Goncharova, A. E. Zubanova, S. V. Novikov, A. E. Trubin // Information systems and techno logies. 2021. № 1 (123). P. 34–42.
8. 8. Anisimov A. Yu. Problems and prospects of introducing information techno logies into the process of personnel training for the digital economy / A. Yu. Anisi mov, A. E. Trubin, A. N. Aleksakhin [et al.]. Moscow: Rusains, 2023. 170 p.
9. 9. Terekhov S. V. Artificial intelligence technologies as a tool for transfor ming the education system in the digital economy / S. V. Terekhov, L. A. Terekhova, N. A. Ozerova // Economics of education. 2023. № 3 (136). P. 79–92.
10. 10. Frolikov A. V. Prospects and risks of using artificial intelligence techno logy in corporate governance / A. V. Frolikov, A. E. Trubin, A. N. Aleksakhin, A. M. Nechaev // Bulletin of the Plekhanov Russian University of Economics. 2025. Vol. 22. №. 1 (139). P. 198–208.
11. 11. Aleksakhin A. N. Applied aspects of artificial intelligence and neural network technologies / A. N. Aleksakhin, M. A. Alymenko, A. Yu. Anisimov [et al.]. Moscow: Rusains, 2024. 176 p.
12. 12. Puchkova E. S. Review of AI tools and their capabilities in the development of digital educational content by students of pedagogical universities for working with schoolchildren / E. S. Puchkova // Pedagogical innovation and continuing education in the 21st Century: proceedings of the II International Scientific and Practical Conference (Kirov, May 20, 2024). Kirov: Vyatka State Agrotechnological University, 2024. P. 636–640.
13. 13. Shunina L. A. Approaches to the development of a question-answer system based on artificial intelligence to enhance students’ cognitive activity / L. A. Shunina, E. S. Grine va // Continuum. Mathematics. Computer science. Education. 2024. № 4 (36). Р. 96–104.
14. 14. Lane H. Natural language Processing in action / H. Lane, H. Hapke, C. Howard. St. Peters burg: Peter, 2020. 576 p.
15. 15. Ganegedara T. Natural Language processing using TensorFlow / T. Ganegedara. M.: DMK Press, 2020. 382 p.
16. 16. Bolshakova E. I. Automatic text processing in natural language and computational linguistics / E. I. Bolshakova, E. S. Klyshinsky. М.: HSE, 2017. 269 p.
17. 17. Muller A. Introduction to Machine learning using Python / A. Muller, S. Guido. М.: DMK Press, 2017. 418 p.
18. 18. McMahan B. Introduction to PyTorch: deep learning in NLP / B. McMahan, D. Rao. М.: DMK Press, 2020. 288 p.
19. 19. Flach P. Machine learning is the science and art of building algorithms that extract knowledge from data / P. Flach. M.: DMK Press, 2015. 400 p.
20. 20. Burkov A. Machine learning without unnecessary words / A. Burkov. M.: DMK Press, 2020. 192 p.
21. 21. Aleksakhin A. N. Functional programming Theoretical and practical foundations for different languages: Textbook / A. N. Aleksakhin, A. E. Trubin, A. Yu. Ansimov [et al.]. M.: Yurayt, 2025. 135 p.2. Abramycheva N. L. Selected issues of digital transformation of education / N. L. Abramycheva, A. Y. Adaikina, O. V. Andryushkova [et al.]. Moscow: INFRA-M, 2024. 188 p.
Download file .pdf 866.21 kb