MODERN AI METHODS FOR PROGRAMMING EDUCATION
DOI:
https://doi.org/10.35546/kntu2078-4481.2025.1.2.16Keywords:
artificial intelligence, programming education, CodeGen, CodeBERT, Flask, web development, offline mode, education automation, machine learning, code generation, code analysis, educational technology, software engineeringAbstract
The paper presents the development of an integrated software system based on artificial intelligence technologies for automating and optimizing the programming education process. Current issues of artificial intelligence usage in the educational process are investigated, including technology accessibility, generated code quality, and adaptation of the learning process to modern requirements. An innovative solution for effective collaboration between programmer and AI is proposed, based on the integration of advanced machine learning models. The developed system utilizes CodeGen and CodeBERT models for comprehensive code analysis and generation.Model CodeGen-350M-mono provides syntactically correct code generation and contextual hints, while CodeBERT performs deep analysis of program structure and semantic relationships. A unique feature of the system is its ability to operate in both online and offline modes through pre-loaded models on a local server, making it accessible for use in various educational settings.The practical implementation includes creating a Flask-based web application that provides an intuitive interface for interaction with AI models and ensures fast processing of user requests. The system demonstrates high efficiency in analyzing input code, providing contextual explanations, and forming recommendations for improving programming solutions.Important functionality includes automatic code completion and early detection of potential errors during development.The created web application ensures effective cooperation between the programmer and artificial intelligence.
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