ВПРОВАДЖЕННЯ ПРИНЦИПІВ FAIR У ПРАКТИЧНУ ПІДГОТОВКУ МАЙБУТНІХ УЧИТЕЛІВ ІНФОРМАТИКИ ТА МАТЕМАТИКИ

This article examines the challenge of integrating the FAIR principles into the practical training of trainee teachers of computer science and mathematics in the context of the digitalisation of education and the growing volume of educational data. It justifies the need for practical training of trainee teachers in the application of the FAIR principles in their professional practice, which includes searching for, processing, documenting, storing, providing access to, and reusing data. The aim of the study is to justify and develop approaches to integrating the FAIR principles into the practical training of future computer science and mathematics teachers as a means of enhancing the effectiveness of their professional training. To achieve this aim, the study utilised an analysis of academic publications and international recommendations, as well as methods of comparison, generalisation, systematisation and pedagogical modelling. Based on an analysis of recent research and publications, a classification of online data set repositories by specialisation is presented, and their application in future teaching practice is clarified in relation to specific pedagogical tasks; five areas for the implementation of FAIR in the practical training of future teachers of computer science and mathematics are identified. A conceptual framework for integrating the FAIR principles into the practical training of future teachers of computer science and mathematics is presented, which includes the areas and forms of their implementation through practice-oriented tasks, a project-based approach and teaching practice. To implement this approach, examples of practice-oriented tasks and an integrated educational project on creating a dataset in accordance with the FAIR principles are proposed. The outcome of this project is a digital package comprising the dataset, metadata, documentation, a lesson plan, information on terms of use and a visualisation of the data analysis. Assessment criteria for such a project have been defined, taking into account data quality and metadata description, pedagogical suitability, legal and ethical requirements, and the degree of compliance with the FAIR principles. The author also proposes implementing the outlined approach during teaching practice in five stages: organisational and diagnostic, design and preparatory, practical and activity-based, analytical and evaluative, and reflective and generalising. The prospects for further research include the practical testing of the proposed approach and experimental verification of its effectiveness.