The impact of a neural network-based assessment system for engagement dynamics and simulation-based learning on the formation of professional competencies in future teachers

The purpose of the study is to evaluate the impact of a neural network-based engagement dynamics assessment system combined with simulation-based learning on the formation of professional competencies of future teachers during trial lessons at Moscow City University (MCU). Research methods: analysis and synthesis of scientific-methodological literature, pedagogical experiment, and methods of mathematical statistics. Research results and conclusions. Based on the experience of Moscow City University (MCU), the comprehensive influence of interconnected components on the conduct of trial lessons by students is examined: the "Digital Mirror" service, an expert assessment system, and simulation training using specialized simulators. Each of these components makes a unique contribution to the formation of professional competencies of the future teacher, and their integration creates a synergistic effect that significantly enhances the quality of student preparation. It is concluded that an integrated approach is necessary, combining objective data from artificial intelligence (AI), expert assessment, and simulation simulators in the process of preparing students at a pedagogical university.