GENERATIVE MODELS (GPT) FOR TEACHING COMPUTER SCIENCE AND PROGRAMMING: METHODOLOGICAL APPROACHES AND PRACTICAL APPLICATIONS

The article analyzes the application of GPT in computer science education. It demonstrates examples of automation (materials, assignments, feedback). Key AI benefits and risks are highlighted. Recommendations are based on pedagogical oversight and developing AI literacy. Conclusion: GPT is an effective assistant when retaining the instructor's leading role.

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Publication Details

Published
2025-07-20
DOI
https://doi.org/10.37539/250626.2025.72.42.010
Primary Topic
Educational Games and Gamification
Type
article
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article

GENERATIVE MODELS (GPT) FOR TEACHING COMPUTER SCIENCE AND PROGRAMMING: METHODOLOGICAL APPROACHES AND PRACTICAL APPLICATIONS

Maria Petrovna Grishkina
Educational Games and Gamification
article

GENERATIVE MODELS (GPT) FOR TEACHING COMPUTER SCIENCE AND PROGRAMMING: METHODOLOGICAL APPROACHES AND PRACTICAL APPLICATIONS

Maria Petrovna Grishkina
article en

Abstract

The article analyzes the application of GPT in computer science education. It demonstrates examples of automation (materials, assignments, feedback). Key AI benefits and risks are highlighted. Recommendations are based on pedagogical oversight and developing AI literacy. Conclusion: GPT is an effective assistant when retaining the instructor's leading role.

Bauman Moscow State Technical University (RU)
Openalex Percentile: Top 81%
Educational Games and Gamification
DOISourceOpenAlex
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GENERATIVE MODELS (GPT) FOR TEACHING COMPUTER SCIENCE AND PROGRAMMING: METHODOLOGICAL APPROACHES AND PRACTICAL APPLICATIONS — Maria Petrovna Grishkina · (2025) | TGRS Research Map | TGRS