Comparative Analysis of Generative Language Models Effectiveness in Educational Process

Abstract

The use of artificial intelligence for the creation of personalized learning materials is one of the key educational innovations that has emerged in response to the growing demand for individualized learning, capable of accommodating the diverse needs of learners. Traditional teaching methods are typically based on standardized content delivery, which proves effective for large groups but fails to account for individual learning styles, information processing speeds, and cognitive characteristics of each learner. Artificial intelligence, with its ability to analyze vast amounts of data and generate valuable insights in real time, unlocks new opportunities for the development of educational materials that can dynamically adapt to the specific needs of each learner. Methods: analysis of scientific literature, content analysis, and evaluation of text responses generated by the ChatGPT, Claude, Gemini, and Mistral 7B models. Results: The study found that all examined models can generate high-quality educational content, but there are differences in the level of academic rigor and text structuring. ChatGPT and Claude demonstrated the best results in terms of logical text construction and compliance with academic standards. The Gemini model proved to be effective in generating adaptive educational materials, whereas Mistral 7B slightly lags behind other models in terms of academic correctness. The evaluation of practical usefulness confirmed the potential of AI models in preparing lecture materials, tests, and assessment tools. Conclusions: The findings of this study confirm that modern AI models can significantly enhance the process of developing educational content, optimizing the instructor’s workload. However, challenges remain regarding information accuracy control, plagiarism risks, and the need to adapt materials to specific curricula. Future research may focus on developing combined methods for AI integration into the educational process and analyzing the impact of these technologies on learning effectiveness across various disciplines.