Using big data and neural network technologies in the creation of adaptive methodological materials for the development of teachers’ research skills

Adaptive learning including adaptive methodological literature plays an important role in improving the effectiveness of teachers’ professional skills development and formation of their research competencies. The article is devoted to the application of big data processing models and neural network technologies in the preparation of adaptive methodological literature for the formation of teachers’ research competencies during the period from 2010 to 2023. Based on the analysis of scientific publications, technical documentation, surveys of teachers and educational analytics, the key principles, methods, and tools of personalization of educational content are identified. Types of data and sources of information for customizing materials to meet the individual needs of research teachers are determined. Criteria and metrics for assessing the effectiveness of adaptive methodological literature are developed, and the prospects of its development on the basis of big data and neural network technologies are substantiated. The problems and limitations of the approaches under consideration are revealed, and recommendations for overcoming them are given. Theoretical significance of the article consists in enhancing scientific concepts of the methodology of adaptive educational content development on the basis of intellectual analysis of big data. The practical value lies in the potential for optimizing the processes of creating personalized methodological resources and developing an adaptive system of pedagogical staff professional development.