Teaching Pedagogical Forecasting to Future Actors-Instructors

The requirements to future specialists in professional education accentuate the qualities of their adaptability, constant self-improvement, capacity to adjust to the new demand in the profession. These qualities are especially important for students of pedagogy and art preparing for the career of actors-instructors, i.e. instructors teaching children acting in school theatres. The actors-instructors' ability to competently foresee the tendencies in their profession, to prognosticate the ways to teach their pupils seems most effective on the basis of teaching pedagogical forecasting to students. Pedagogical forecasting is viewed as the scientifically grounded activities aimed at investigating possible transformations, development trends and prospects of objects in pedagogy and education. Three aspects of pedagogical forecasting are applied in the activities of future actors-instructors: forecasting students' own leaning, forecasting and designing classes in the process of pedagogical practical training (quazi-professional activities) and teaching forecasting to pupils during practical training in schools. The present paper introduces the concept and structure of pedagogical forecasting in the activities of future actors-instructors. The levels of pedagogical forecasting in the activities of future actors-instructors are described. The criteria to measure the prognostic competency of future actors-instructors are shown. The model of pedagogical forecasting in the activities of future actors-instructors is introduced. The experimental research conducted in a higher school in the Urals in 2013-2017 illustrates the system of activities to prepare future actors-instructors to apply pedagogical forecasting in their profession. The process of future actors-instructors training to organize pedagogical forecasting is shown. The methodology to analyze the pedagogical forecasting in the activities of a future actor-instructor includes case study, educational experimentation. Data collecting and processing is based on conversational interviewing. The data collecting method is carried out to study the higher school staff opinions about the actual level of future actors-instructors' pedagogical forecasting. Statistical data processing was performed in the MS Excel 2010 environment. A comparison of the distribution of nominative variables was made using the X[superscript 2] Pearson Fitting Criterion with a sample size (n [greater than or equal to] 100). [For "NORDSCI International Conference Proceedings: Education and Language Edition (Helsinki, Finland, July 17, 2018). Book 1. Volume 1," see ED603189.]