Monitoring of Matching of Vocational Education with the Needs of the Labour Market

 
PIIS086904990011378-7-1
DOI10.7868/S0869049918030012
Publication type Article
Status Published
Authors
Occupation: Head (academic supervisor)
Affiliation: Research association of the Plekhanov Russian University of Economics
Address: Stremyanny lane, 36, Moscow, 117997, Russia
Occupation: Department head
Affiliation:
Research association of the Plekhanov Russian University of Economics
Joint Institute for Nuclear Research
Address: Joliot-Curie, 6, 141980, Dubna, Moscow region, Russia
Occupation: Head
Affiliation:
Research association of the Plekhanov Russian University of Economics
Joint Institute for Nuclear Research
Address: Joliot-Curie, 6, 141980, Dubna, Moscow region, Russia
Occupation: Senior software engineer
Affiliation:
Research association of the Plekhanov Russian University of Economics
Joint Institute for Nuclear Research
Address: Joliot-Curie, 6, 141980, Dubna, Moscow region, Russia
Occupation: Software engineer
Affiliation:
Research association of the Plekhanov Russian University of Economics
Joint Institute for Nuclear Research
Address: Joliot-Curie, 6, 141980, Dubna, Moscow region, Russia
Journal nameObshchestvennye nauki i sovremennost
EditionIssue 3
Pages5-16
Abstract

Last years, the prospects for digitalization of economic processes were actively discussed. It is quite a complex problem having no solution with traditional methods. Prospects of their qualitative development are illustrated by the example of the use of Big Data analytics and intellectual analysis of texts for the assessment of the needs of regional labour markets in the labour force. The problem is solved using the developed by the authors the automated information system of monitoring of matching the staffing needs of employers with the training level. The information gathering is based on open sources. The system presented provides additional opportunities to identify qualitative and quantitative relationships between education and the labour market. The system is targeted at a wide range of users: authorities and management of regions and municipalities; the management of universities, companies, recruitment agencies; graduates and prospective students.

KeywordsUnemployment, Big Data, model, regional economics, labour market
Received10.06.2018
Publication date10.06.2018
Number of characters1040
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1. Avraamova E.M. (2009) Napravleniya vertikal’noy mobil’nosti molodykh spetsialistov [Directions of vertical mobility of young specialists]. Obshchestvennyie nauki i sovremennost’, no. 6, pp. 108–116.

2. Cheremisina E.N., Belaga V.V., Samojlenko Ju.I. (2014) Informacionno-obrazovatel’naja sreda dlja obuchenija informacionnym tehnologijam na baze Instituta sistemnogo analiza i upravlenija Universiteta “Dubna” [Information and education environment for studying the information technologies based on the Institute of system analysis and management, “Dubna” University]. Otkrytoe obrazovanie, no. 2, pp. 59–65.

3. Dolado J. (2015) No Country for Young People? Youth Labour Market Problems in Europe. London: EC1V 3PZ UK.

4. Efrati A. (2012) Google Gives Search a Refresh. The Wall Street Journal. Retrieved July 13.

5. European Commission (2016) From University to Employment: Higher Education Provision and Labour Market Needs in the Western Balkans. Synthesis Report (https://ec.europa.eu/education/sites/education/files/2016-higher-education-labour-market-balkans_en.pdf).

6. Gushhin A.N. (2013) Obespechenie uchebnogo processa, postroennogo na standartah FGOS-3, sredstvami informacionnyh tehnologij [Ensuring the educational process, built on the standards of GEF-3, using information technology]. Obrazovatel’nye tehnologii [Education Technologies], no. 4, pp. 84–89.

7. Kutuzov A., Kuzmenko E. (2017) WebVectors: A Toolkit for Building Web Interfaces for Vector Semantic Models. Ignatov D. et al. (eds) Analysis of Images, Social Networks and Texts. AIST 2016. Communications in Computer and Information Science, vol. 661. Springer, Cham.

8. Martínez Garcia E., España-Bonet C., Màrquez L. (2015) Document-Level Machine Translation with Word Vector Models. Proceedings of the 18th Annual Conference of the European Association for Machine Translation (EAMT), pp. 59–66.

9. Mikolov T., Chen K., Corrado G., Dean J. (2013) Efficient Estimation of Word Representations in Vector Space, arXiv:1301.3781v3 [cs.CL].

10. Olejnikova O.N., Muravjeva A.A. (2016) Prognozy potrebnosti v umenijah i professional’noe obrazovanie i obuchenie – opyt ES [Forecasting skill needs and vocational education and training – EU experience]. Centr izuchenija problem professional’nogo obrazovanija [Center for Vocational Education Studies] (http://www.cvets.ru/Modules/SNA-EC.pdf).

11. Oren B. (2015) Bayesian Neural Word Embedding, arXiv:1603.06571.

12. Petrunina O.E. (2005) Proektirovanie informacionno-analiticheskoj sistemy upravlenija regional’nym rynkom truda [Designing an information and analytical system for managing the regional labour market]. Sovremennye naukoemkie tehnologii, no. 5, pp. 75–78.

13. Pogorelov E. (2013) Problema vostrebovannosti vypusknika vuza na sovremennom rynke truda [The problem of the high school graduate demand in the modern labour market]. Materialy V Mezhdunarodnoj studencheskoj jelektronnoj nauchnoj konferencii Studencheskij nauchnyj forum [Materials of Vth International student online conference Student Science Forum] (http://www.scienceforum.ru/2013/163/2366).

14. Quoc V. Le, Mikolov T. (2014) Distributed Representations of Sentences and Documents, arXiv:1405.4053.

15. Review of Vocational Education – The Wolf Report (2011) (https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/180504/DFE-00031-2011.pdf).

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