Stochastic component of professional education for future mathematics and computer science teachers
Автор: Grushevskiy Sergey P., Knyazeva Elena V.
Журнал: Историческая и социально-образовательная мысль @hist-edu
Рубрика: Образование и педагогические науки
Статья в выпуске: 1-1 т.8, 2016 года.
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The article introduces a context line of practice-oriented educational course that includes such disciplines as “Probability Theory and Mathematical Statistics”, “Mathematical methods in Pedagogical Sciences and Psychology”, “Mathematical methods in Social Studies and Humanities", "Probabilistic Models", for perception of basic concepts of Probability Theory and methods of stochastic modeling in professional education for future teachers of Mathematics and Computer Science. Context line of educational course is built in such a way, that understanding of basic terms of Probability Theory when taught to school pupils is sequentially supplemented with principles of creation of probabilistic models in different fields of science and use of statistical methods in psycho-pedagogical research, which should facilitate development of professional competences of future teachers of Mathematics and Computer Science. System of professional Masters’ education also focuses on development of disciplines, connected with creation of system of terminology, knowledge and skills in applying methods of Mathematical Statistics to research in Natural Sciences and Humanities; with development of intuitive and practical notion of Masters about data analyses used in research tasks; with use of contemporary computer technologies and software. Today’s specialist should master information technologies and statistical methods, applicable to his or her sphere: future teachers should be familiar with basic mathematical methods of processing empirical data to be able to estimate efficiency of educational process, with the main concepts and stages of pedagogical experiment, with idea of probabilistic model, with basic statistical methods of processing survey and verifying experimental hypotheses.
Probability theory, probabilistic models, mathematical statistics, applied statistics, educational research
Короткий адрес: https://sciup.org/14951068
IDR: 14951068 | DOI: 10.17748/2075-9908-2016-8-1/1-134-138