Abstract
The article is devoted to the development of didactic bases for designing the learning process in professional educational institutions. From this standpoint, the authors propose the use of the prognostic approach, the didactic forecasting. The future state of the pedagogical process is determined on the basis of socioeconomic, scientific, technical, cultural, technological forecasting. A characteristic feature of the didactic design of the learning process in a professional educational institution is the presence of two components of the learning process: theoretical and industrial training, which necessitates the design of theoretical and production training. Designing theoretical training is associated with the development of modular programs of general educational, general technical and special subjects, pedagogical technologies that ensure the implementation of innovative approaches to the development of educational and cognitive activities. The design of production training is associated with the design of the production process, the material and technical and socio-technical environment. The design of the material and technical environment is associated with the equipment of study rooms, training workshops, with the definition of quantitative and qualitative characteristics of the raw materials, with technical and technological capabilities for manufacturing products. The design of the social and industrial sphere is associated with production, economic relations, and professional communication. Also, the article discusses the features of designing the learning process in a professional school related to establishing links between theoretical and production training, pedagogical and production tasks, between professional knowledge and production activities.
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Bystrova, N.V., Konyaeva, E.A., Tsarapkina, J.M., Morozova, I.M., Krivonogova, A.S. (2018). Didactic Foundations of Designing the Process of Training in Professional Educational Institutions. In: Popkova, E. (eds) The Impact of Information on Modern Humans. HOSMC 2017. Advances in Intelligent Systems and Computing, vol 622. Springer, Cham. https://doi.org/10.1007/978-3-319-75383-6_18
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