STEM APPROACH TO TEACHING PROBABILITY THEORY AND MATHEMATICAL STATISTICS TO FUTURE TEACHERS
DOI:
https://doi.org/10.31110/fmo2025.v40i1-06Keywords:
probability theory, mathematical statistics, STEM, future teachers of mathematics and computer science, specialty 014 Secondary education, applied orientation of trainingAbstract
Formulation of the problem. Implementing STEM-oriented approaches to education is an urgent problem. Methods of teaching mathematics and teacher training need to be improved. The article aims to reveal the peculiarities of implementing STEM approaches in teaching probability theory and mathematical statistics.
Materials and methods. The article analyzes the scientific and methodological literature on the problem of implementing STEM education and stochastic education, synthesizes the leading ideas, and formulates its own conclusions.
Results. The article highlights the use of STEM approaches in teaching probability theory and mathematical statistics to future teachers of mathematics and computer science (specialty 014 Secondary Education). Attention is paid to analyzing modern methods combining science, technology, engineering, and mathematics, particularly in teaching mathematics. Particular attention is paid to training math teachers to use the Gran1 and GeoGebra dynamic mathematics systems, Google spreadsheets, Wolfram Demonstrations Project, and a probability calculator in teaching stochastics. Software tools are used to create simulations, generate samples according to certain probability distribution laws, process samples, and determine numerical and graphical characteristics. The use of Wolfram Demonstrations Project visualizations helps students better understand several topics in probability theory: the laws of probability distribution of random variables, the law of large numbers, correlation, and regression. One of the STEM approaches is the use of the Monte Carlo method, in particular for approximate calculations of the areas of shapes and volumes of bodies. Emphasis is placed on the applied orientation of learning. It is important to use practice-oriented tasks. To implement STEM approaches in teaching stochastics, it is advisable to develop program fragments and demonstrate the results of their implementation, for example, for statistical testing of statistical hypotheses. It is advisable to perform tasks in mini-groups as learning projects.
Conclusions. The use of STEM approaches in teaching probability theory and mathematical statistics will help improve future teachers' training levels, improve their practical skills, and integrate theoretical knowledge.
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