AI-Powered Learning: Revolutionizing Education and Automated Code Evaluation

The paper presents a case study on using artificial intelligence (AI) for preliminary grading of student programming assignments. By integrating our previously introduced learning programming interface Verificator with the Gemini 2.5 large language model via Google AI Studio, C++ student submissions were evaluated automatically and compared with teacher-assigned grades. The results showed moderate to high correlation, although the AI was stricter. The study demonstrates that AI tools can improve grading speed and consistency while highlighting the need for human oversight due to limitations in interpreting non-standard solutions. It also emphasizes ethical considerations such as transparency, bias, and data privacy in educational AI use. A hybrid grading model combining AI efficiency and human judgment is recommended.