Solving economic and social problems requires the use of new technologies for big data analyses. The development of network and online commerce services, such as social research and electoral polls, requires methods and tools for working with large amounts of information. For large retail chains, fine-tuning the logistics costs and product stocks within units or tenths of a percent can provide substantial savings. The wide use of big data technology points out a question of learning methods and technologies of big data analysis. Teaching courses using mathematical modeling techniques and data analysis for students of economic specialties require the development of mathematical thinking skills. The key solution for learning students with imaginative thinking by the mathematical methods is the creation of stable links between the task and its corresponding functionality in the software. Each student has an individual set of skills and its own unique experience, which suggests the formation of new paths individualization of learning principles. Information technologies helps to overcome cognitive difficulties among students. Modern Information technologies and software were used for learning students to work with Big Data. Creative thinking students can solve the tasks in Matlab and Simulink graphical programming system from MathWorks. The article analyzes the abstract and creative thinking together with computational thinking and project learning. Creative thinking can be effectively used to educate programming skills in object-oriented programming languages such as C ++ and C #. The understanding of creative thinking for economic specialties students is possible through the study of visual algorithmic schemes. The development of computational thinking is very important for our students, especially for the negative tendency to replace examinations with computer tests. Developing sustainable skills allows students to solve practical tasks in research and industry. Introducing Matlab's MathWorks infrastructure into universities is one of the possible ways for students to develop computational thinking skills, as well as supporting "project learning" and CDIO initiatives (Conceive - Design - Implement - Operate). For big data analyses it is possible to use machine learning algorithms, neural networks, flexible logic and artificial intelligence. The Matlab software package for these purposes provide toolboxes: "Neural Network Toolbox", "Fuzzy Logic Toolbox" and "Statistics and Machine Learning Toolbox". The level of complexity of tasks puts high demands on the students' learning system. It is necessary for students to introduce the teaching of the basic course Matlab to develop their skills in formulating and solving mathematical problems, as well as to train their technology collaboration in the network design. In the future, when studying compulsory disciplines and special courses, each lecturer will be able to offer students examples of solutions in the Matlab environment and with its help organize extracurricular work in network projects. At the next stage, it is possible to implement an interdisciplinary project that brings together students from different faculties, both bachelors and masters.

Baranova N. , Sorokin L.
Ключевые слова
educational technologies; cognitive barriers; mathematical thinking; computational thinking; project learning; Matlab; Simulink; mathematical modeling
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