One of the solutions to the problem, when not the best graduates enter the pedagogical profiles and after graduation are employed in the education system, is the prediction of professional orientation even at the stage of the student choosing their further professional trajectory. To solve this problem, the purpose of the study is to develop and experimentally prove the effectiveness of using a program for predicting the employment of students of a pedagogical university based on the introduction of various machine learning algorithms. Using a random selection of students, the collection and processing of their questionnaires (n=205) in 2011-2016 were carried out. Various machine learning algorithms were used to create the program: decision trees, logistic regression, and catboost. In the course of the experiment, the data of the questionnaires were loaded into the program for its training according to various algorithms, in order to ultimately obtain a finished intellectual product with the ability to predict the employment of graduates. In the final comparison, the program developed on the “decision trees” algorithm made only 2 out 19 questionnaires and 7 out 61, which was the best result – 89%. The implementation of this algorithm makes it possible to most accurately, with the least percentage of errors, identify students who will not be employed in the future according to their profile of study or not employed at all. Thus, the study developed an intelligent program that allows one to instantly process data and get an accurate forecast of employment with only a small probability of error.
Keyword(s) : employment
Educational standards and modern requirements: contradictions or opportunities
This is an empirical study of professional competencies. The article addresses two main tasks: the
demands of the labor market presented to specialists in the field of trade and marketing; and the
identification of the professional competencies formed by the standard for the preparation of FSES
HE 3+ and whether it meets the modern requirements of employers. Two hypotheses are investigated:
(i) can the competencies inherent in the educational standard develop the necessary skills required
by this profession in the modern labor market; and (ii) do the professional competencies reflect
the necessary personal qualities demanded by employers. The analysis shows that the educational
standard of the FSES HE 3+ is rather poorly adapted to the modern requirements of the labor
market. As a rule the professional competencies in it develop a specialist who is ready to engage in
his own entrepreneurial activity, while the training of such personnel is carried out at the expense
of the state budget. This implies the need to work in large organizations and to possess a wider set
of skills, including the ability for expert and analytical work, systemic thinking, etc. The increasing
innovation in high-tech industries as Russia moves towards a digital economy will increase the
demand for labor marketers who have design, engineering, visualization and skills for working with
BigData. It is these skills that should be integrated into the new FSES of HE3 ++ to train a specialist
to meet the requirements of the 21st century.