Methodological Aspects of Pedagogical Predicting of Academic Success of Students According to their Educational Profile
Abstract
The article discusses the methodological aspects of predicting academic success among students when choosing a training profile at the third stage of general secondary education. The general patterns of pedagogical predicting are revealed: patterns of purpose, content, methods and quality of pedagogical predicting. An appropriate methodology and recommendations are proposed, the use of which will allow the systematic and consistent implementation of the patterns and principles of pedagogical predicting in the practice of pre-professional training and specialized education. The developed methodology reflects the principles and logic of implementing the process of pedagogical predicting of a student’s academic success when choosing a training profile. The goals are achieved with the help of special content, specific methods and methodological techniques that have the necessary predictive potential, among which the following can be distinguished: the “goal tree” method, predictive monitoring, extrapolation, testing, questioning, the method of forecast scenarios, optimization methods, the method of pedagogical modeling. The essence of this technique is the sequential implementation of the general stages of forecasting activity: the stage of pre-forecast orientation (preparatory), retrospective, diagnostic and prospective stages, each of which corresponds to specially selected, most effective in terms of achieving the set goals, forecasting methods and techniques, qualitative and resource accompaniment.
General Information
Keywords: patterns, principles, methodology, methodological recommendations, academic success, pre-vocational training, training profile, pedagogical predicting
Publication rubric: Digital Transformation and Online Education: Technologies, Tools & Models
Article type: theses
For citation: Sinkevich V.N. Methodological Aspects of Pedagogical Predicting of Academic Success of Students According to their Educational Profile. Digital Humanities and Technology in Education (DHTE 2023),, pp. 216–231.
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