Keyword: «mathematics lesson»

The article is devoted to the problem of the transformation of the role of generative neural networks in mathematics lessons: from a tool of hidden cheating to a didactic partner. Based on an empirical study (76 students in grades 6-10, Glazov, MBOU "Secondary School №. 3"), it is shown that the vast majority of schoolchildren already use neural networks to complete tasks. However, they do not blindly copy the answers, but check or redo them. A clear age trend has been revealed: among sixth graders, the proportion of "cheating" students exceeds the proportion of those who study with the help of AI, while by the 10th grade the situation is reversed. A methodological system of four strategies has been proposed and tested: "Critical reviewer", "Noisy task", "AI tutor" and "Methodical duo". It has been experimentally proven that the implementation of this system makes it possible to significantly increase the proportion of students who constructively use the neural network, compared with the control group. The methodological transition from prohibitive tactics to a partnership strategy is substantiated. The results can be directly used by math teachers at school.

The article presents the modern mathematics lesson as a space of communication, choice, and collaborative problem-solving. It summarizes the methodological foundations of the approach and the main interactive practices used to develop subject and universal learning outcomes. Special attention is paid to the changing role of the teacher and to formative assessment as a tool for supporting students’ progress. The article shows that communication, choice, and cooperation strengthen students’ independence, critical thinking, and responsibility for learning. The conclusion emphasizes the developmental potential of interactive mathematics lessons.