Using neural networks to test knowledge during the training process

The article discusses the use of neural networks in education. The main idea is that the neural network model can accurately evaluate students' knowledge. The authors focus on computer-based tests as the primary way to monitor learning progress. The goal of this research is to teach neural networks to analyze data, assess knowledge levers and provide personalized learning recommendations. The emphasis is on using computer testing to track process and evaluate how well the neural network system works. Results show that neural networks can effectively measure students knowledge, especially computer -based assessments. Neural networks are useful tools for organizing complex learning systems and demonstrate potential for improving knowledge structuring and organization. The novelty of this article is in using Al for accurate analysis skill assessment. The analysis of this article is to test the hypothesis about the possibility of effectively assessing student learning using a neural network model. The use of neural networks in the learning process shows the possibility of improving the learning system. Future studies plan to enhance learning pace, select appropriate materials, and optimize the learning process by analyzing educational data.