Abstract
The article describes an intelligent predictive system that allows evaluating the student's capabilities in various areas of analytical activity. When designing the prognostic apparatus of this system, a hybrid intelligent approach is taken, combining the advantages of existing methods. Its components are the neural network model and a group method of data handling. In addition, the most popular professions in the labor market are identified; professional skill maps are developed on the basis of the requirements. The training sample of the system is supplemented with images generated through the Monte Carlo method. Applying data on student success in selected key disciplines, as well as other available information, the system offers a numerical equivalent of potential for these professions. In addition to the recommendations, a student has the opportunity to timely and consciously adjust the educational focus of his educational process; this has a positive effect on the graduates' competitiveness in a higher educational establishment.
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