Abstract
<jats:p>The purpose of the study is to identify and characterize potential changes in the assessment activity of language and literature teachers due to the availability of neural networks. The theoretical part of the study is related to the methodology of teaching the methodological cycle of disciplines to students of philology at a pedagogical university. At the empirical level, a local survey of participants in the project group for the use of artificial intelligence technologies was conducted, organized by the authors on the site of the Methodological Consulting network community. The evaluative activity of language and literature teachers is presented as a dynamic component of the subject methodology, due to the local normative regulation of the intra-school educational quality assessment system. The novelty of the research lies in the substantiation of four formats of the assessment activity of language and literature teachers that reduce the devaluation of reading work in the context of the availability of neural networks: an accumulative achievement model, consideration of user behavior within the framework of thematic control, pedagogical support for the work of students in artificial intelligence services, and in-program standardization of reading work as an object of pedagogical assessment. In the course of the research, the following results were obtained: the concept of evaluation activity as a component of the methodological system was clarified, its connection with modern requirements for the results of literary education was revealed, and the idea of complex transformations caused by the transparency of the digital educational environment of the school was argued.</jats:p>