PROBABILISTIC METHODS IN TECHNICAL EDUCATION: TEACHING THROUGH PROFESSIONALLY ORIENTED APPLIED TASKS

Alma E. Abylkassymova, Yessenkeldy Tuyakov, G.А. Rysbekova

2026

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DOI 10.48371/peds.2026.81.2.026
Data confidence 70 medium
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Abstract

In the context of technological advancement and the increasing complexity of engineering systems, there is a growing need to train specialists capable of effectively operating under conditions of uncertainty, analyzing data, and making informed decisions. In this regard, the application of probabilistic methods in the education of engineering students is of particular relevance.The aim of this study is to develop and substantiate methodological approaches to the use of probabilistic methods in professionally oriented education. The main directions of the research include the integration of probabilistic models into the educational process, the adaptation of curriculum content to the needs of engineering and IT fields, and the development of students’ skills in data analysis, forecasting, and decision-making. The key idea of the study is to bridge theoretical training with real-world industrial tasks. The scientific significance of the work lies in substantiating the role of probabilistic methods as a tool for developing professional thinking and analytical competencies. The practical significance is determined by the possibility of applying the proposed approaches in the design of educational programs.The research methodology is based on a quasi-experimental design involving control and experimental groups, pre-test and post-test assessments, and the application of statistical data analysis methods. The experimental instruction was carried out using professionally oriented tasks based on probabilistic models. The results of the study demonstrate that the use of probabilistic methods significantly improves students’ academic performance: the experimental group showed an increase in the mean score by 16 points with statistically significant differences (p < 0.001), whereas the control group showed only limited improvement. These findings confirm the effectiveness of the proposed approach. The value of the study lies in the development of a methodological model for integrating probabilistic methods into professionally oriented education. The practical significance of the results is reflected in their applicability to the modernization of educational programs and the training of specialists capable of effectively operating under conditions of uncertainty and technological complexity.