Expert: University Programs Must Be Adapted to Meet the Needs of Labor MarketCC0Russia14:22 27.02.2018(updated 14:36 27.02.2018) Get short URL
The information system, which is based on analysis of sets of big data that are constantly being updated, allows researchers to identify the qualitative and quantitative relations between the education sector and the labor market, said Professor Sergei Valentei, doctor of economics at Plekhanov Russian University of Economics.
Researchers from the Plekhanov Russian University of Economics have created a prototype of an automated information system for monitoring and analyzing recruitment requirements in Russian regions, and identifying the relationship between the labor market’s requirements and educational and professional standards, the university’s press service told Sputnik.
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“Using this system, we will be able to learn if university programs meet the current expectations of the labor market,” Valentei told RIA Novosti. “We will also be able to predict the changes in these expectations and automatically develop recommendations for the adjustment of training programs. The system is being developed for a wide range of users, and was designed primarily for regional governors, universities, companies, recruitment agencies and young professionals.”
Today, the Russian economy is characterized by a mismatch between the numbers and skills of university and specialized secondary school graduates and the needs of the labor market, the expert noted.
“The problems that graduates face are often related to the imbalance of supply and demand in the labor market, the poor quality of professional training, a discrepancy between the skills of recent graduates and employers’ requirements, as well as various social factors,” Valentei explained.
To make an effective prognosis of recruitment requirements, researchers require an objective assessment of the current state of the labor market, the expert said. That is why the researchers decided to develop an automated information system for labor market monitoring. This system can also be used to develop recommendations for the adjustment of educational programs.
“The professional skills described in educational standards and the requirements listed in job postings contain an average of ten words,” Valentei explained. “We developed an algorithm of mapping sentences to vector space, which allows us to calculate the “similarity” of words used, as well as the degree of semantic resemblance between the skills and listed requirements.”
The researchers use web-based sources to collect data for further analysis. Data on job openings is collected from websites like Rabota v Rossii (Jobs in Russia, information website of the Russian Federal Service for Labor and Employment), HeadHunter and SuperJob. Researchers use machine learning algorithms to map sentences to vector space, and then calculate the vectors of these sentences. This allows them to identify the semantic similarity between the labor market’s requirements and the professional skills provided to students by the Russian system of higher education, the expert said.
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The system can be developed and adapted to the specific needs of a certain region or university, Valentei added. With more statistics accumulating, researchers will also be able to predict the demand for certain specializations and skills related to their field of expertise.
The system has been added to the list of software and technological solutions used at the Situational Centre for Social and Economic Development of Russia and the Russian regions.