DEVELOPMENT OF A METHODOLOGY FOR TEACHING STUDENTS OBJECTORIENTED PROGRAMMING IN A VIRTUAL COLLABORATIVE ENVIRONMENT USING GENERATIVE ARTIFICIAL INTELLIGENCE TOOLS

DEVELOPMENT OF A METHODOLOGY FOR TEACHING STUDENTS OBJECTORIENTED PROGRAMMING IN A VIRTUAL COLLABORATIVE ENVIRONMENT USING GENERATIVE ARTIFICIAL INTELLIGENCE TOOLS

Authors

  • Saidova Dilfuza Ergashovna

DOI:

https://doi.org/10.5281/zenodo.20704714

Keywords:

generative artificial intelligence, virtual collaboration environment, object-oriented programming, programming education, artificial intelligence tools, teaching methodology, digital learning technologies, programming competencies

Abstract

This article discusses the development of a methodology for teaching students object-oriented programming
in a virtual collaborative environment using generative artificial intelligence tools. The integration of artificial
intelligence technologies into the educational process provides opportunities to improve the effectiveness of
programming education, develop students’ algorithmic thinking, software design skills, and independent learning
competencies. The article examines methodological aspects of organizing code generation, error detection,
problem analysis, and collaborative software project development through generative AI tools. Furthermore, the
pedagogical potential of integrating virtual collaboration environments with artificial intelligence technologies in
teaching object-oriented programming is analyzed

Author Biography

Saidova Dilfuza Ergashovna

Associate Professor, Department of Algorithms and Programming Technologies, Karshi
State University



References

1. Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P.,

Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler,

D. M., Wu, J., Winter, C., & Amodei, D. (2020). Language models are few-shot learners. Advances in Neural

Information Processing Systems, 33, 1877–1901.

2. Chen, X., Xie, H., Zou, D., & Hwang, G. J. (2020). Application and theory gaps during the rise of

artificial intelligence in education. Computers and Education: Artificial Intelligence, 1, 100002.

3. VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other

tutoring systems. Educational Psychologist, 46(4), 197–221.

4. Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35.

5. Власов, А. В., & Кузнецов, С. А. (2022). Искусственный интеллект в образовании: современные

тенденции и перспективы развития. Информационные технологии и образование, 3, 45–52.

6. Иванова, Е. О., & Осмоловская, И. М. (2020). Технологии цифрового образования: теория и

практика. Москва: Юрайт.

7. Саидова Д. Э. ИНДИВИДУАЛЬНО-ПСИХОЛОГИЧЕСКИЕ ОСОБЕННОСТИ ОБУЧЕНИЯ

СТУДЕНТОВ ПРОГРАММИРОВАНИЮ В ВИРТУАЛЬНОЙ СРЕДЕ СОВМЕСТНОЙ РАБОТЫ //Экономика и

социум. – 2023. – №. 1-2 (104). – С. 635-638.

8. Saidova D. Teaching Programming Collaboratively Through Google Colab AND Github Integration //

Green Economy and Development. – Т. 3. – №. 11. – С. 667884

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Published

2026-06-01

How to Cite

Saidova , D. (2026). DEVELOPMENT OF A METHODOLOGY FOR TEACHING STUDENTS OBJECTORIENTED PROGRAMMING IN A VIRTUAL COLLABORATIVE ENVIRONMENT USING GENERATIVE ARTIFICIAL INTELLIGENCE TOOLS. GREEN ECONOMY AND DEVELOPMENT, 4(6). https://doi.org/10.5281/zenodo.20704714
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