The Use of Generative Neural Networks to Personalize Programming Education in Higher Education Egorova G. I., Seliverstova M. V. Formation of an Inclusive Culture of Future Teacher to Ensure Culturological Safety of Students at All Levels of Education

Abstract

Artificial intelligence technologies, in particular generative neural networks, offer a wide range of capabilities that automate some of the teacher’s functions and help solve the tasks of personalizing learning. The purpose of the study is to identify the possibilities of generative neural networks to increase the effectiveness of personalized programming education in higher education institutions. Materials and methods: analysis and generalization of pedagogical and methodological literature on the problem of research, experiment, questionnaire, statistical methods. The study clarifies the components of the bachelor’s professional competence in IT fields of study, provides the stages of using generative neural networks to teach students how to create clean code and refactor, highlights the areas of application of artificial intelligence for teaching programming at a university. The effectiveness of using generative neural networks to personalize programming training is confirmed by the experiment. The authors conclude that it is necessary to transform traditional approaches to learning programming through the use of artificial intelligence capabilities.