Generative artificial intelligence as a means of delivering personalised and adaptive feedback in education

Introduction. In today’s digital transformation era, enhancing the quality of the learning process through improved feedback mechanisms has become particularly relevant. Traditional feedback methods are unable to adapt dynamically to the unique educational needs of any learner. Generative artificial intelligence (hereinafter GAI) is an innovative tool that expands the teacher’s capabilities in automating and personalising learner feedback. The aim of this article is to develop the theoretical foundations and practical applications of GAI in the organisation of feedback to ensure a personalised, timely, and informed dialogue between the teacher and the learner. Methodology and methods. The survey involved 15 lecturers and 213 students working on teacher training programmes at the Faculty of Mathematics and Computer Studies of Pushkin Leningrad State University (St Petersburg). The participants were divided into two groups: the control group (107 students), where traditional feedback was used, and the experimental group (106 students) involving an improved GAI-based feedback system. An experiment was conducted to assess the impact of different feedback methods on student satisfaction with the feedback. Systemic, person-centred and praxiological approaches were used to analyse the effects. The experiment results were assessed on the basis of questionnaires and statistical methods (Mann Whitney and Wilcoxon tests). KEYWORDS Results. The findings of the experiment showed a statistically significant improvement in the perception of feedback by the experimental group working with GAI, compared to the control group, where traditional methods were applied (p< 0.01). The key indicators, characterising the timeliness, personalisation level and informative value of feedback, demonstrated steady growth (determination coefficients R² ≥ 0.97), which directly resulted in an increase in students’ overall satisfaction. The use of GAI significantly reduced the routine workload of teachers (by approximately 80–87% according to their estimates) and improved the speed and quality of feedback (with up to 93% of positive ratings). The students noted their increased motivation, reduced anxiety and greater confidence in the learning process. It was concluded, on the basis of the quantitative and qualitative indicators of the experiment, that the integration of GAI into the feedback system facilitated a more personalised and adaptive dialogue between the teacher and the student. Conclusion. The integration of GAI into the feedback system represents an innovative solution for optimising teaching practice and improving the quality of education. The balanced interaction of the teacher and GAI ensures a high degree of personalisation in feedback, helps to increase learners’ motivation and engagement, and stimulates the development of students’ critical thinking and interest in the learning process. The presented results can be used to develop professional development programmes for teachers in applying GAI in the educational process.