Schools will have to teach children to defend their answers rather than choose the correct options.
The development of neural networks changes not only the content of school subjects, but also the methods of testing knowledge. The teachers will have to pay more attention to how the child reasons and whether he can independently explain his work. Financial University professor Alexander Spanov believes that education should maintain basic training and develop independent thinking skills. In the context of the proliferation of neural networks, reading, understanding complex texts and being able to express their content in your own words become especially important.
One possible way for schools to adapt is to expand oral forms of knowledge testing. An oral exam, retelling, discussion or defense of a project allows you to see if the student understands the material and is able to build an argument independently. Testing in such a system does not have to disappear completely. It can remain a tool for testing individual knowledge, but should not be the only way of assessment. Choosing the correct option among several proposed answers does not always show how well the student understands the subject.
Another approach is to evaluate not only the finished text, but also the process of its preparation. If a student presents research or an abstract, the teacher may ask for an explanation of why specific sources were chosen, how the hypothesis was formed, and what arguments support the conclusion. Such protection helps separate independent work from a result completely prepared by the neural network.
A complete ban on neural networks in education will not solve the problem: students will still use the tools available outside the classroom. Instead, tasks can be structured so that the use of AI requires additional analytical work from the student.