Neural network as a tool for informatics teachers to develop materials for teaching programming

The article examines issues related to the use of neural networks in education from the perspective of teaching practice. It highlights the potential of neural network capabilities in preparing informatics teachers for lessons, particularly in the development of instructional materials. Three methods are proposed for using the DeepSeek neural network to create programming-related learning materials: developing tasks at varying difficulty levels for personalized learning, designing test questions for assessment purposes, and creating error-identification exercises. The practical component is based on material from the 8th-grade informatics textbook by L. L. Bosova and A. Yu. Bosova. Examples of tasks at different difficulty levels generated using DeepSeek are presented, along with a comparative analysis against the exercises found in the aforementioned textbook. Recommendations are offered for integrating these developed materials into the educational process.