Statistical analysis of teachers' digital competence levels

Purpose of the study. The study of the qualitative parameters of the human resources potential of the economy is necessary to describe the conditions in which digitalization processes develop, to identify the problems of training specialists. The professional education system is considered in the article as an institution that provides human resources to the digital economy of the region. Innovative processes increase the requirements not only for the system of training specialists, but also for the skills of the lecturer, individual level of mastering information and communication technologies. The purpose of this study is to diagnose the levels of digital competencies of lecturers of professional educational institutions and to identify, on the basis of statistical analysis, the impact on the level of digital competencies of a lecturer of various parameters, such as the lecturer’s age; the disciplines he/her teaches; the data of continuing education in the field of information and communication technologies.

Materials and methods. This paper provides an overview of approaches to solving the problems of staffing education in the context of informatization. Taking into account the proposed model of digital competencies of lecturers, the testing complex was approved. Methods of statistical data analysis were applied: descriptive statistics, correlation coefficients were calculated, a range diagram and scatter diagrams of lecturers' testing results were constructed. For the information processing, the qualitative indicators were converted into quantitative ones and the statistical analysis software packages were used: Microsoft Excel and STATISTICA 10.0.

Results. As a result of the lecturers’ testing of professional educational institutions and statistical analysis, data were obtained on the level of human resources in terms of the formation of knowledge and skills in the field of information and computer technologies. The relationship between the level of digital competence and various factors has been identified. The factors that were analyzed in the course of the study: age, subjects taught, the period of limitation of the advanced training in the field of information and communication technologies.

Conclusion. The introduction of the proposed model of competencies and diagnostic methods will allow diagnosing lecturers' skills in working in a digital environment and will ensure the adoption of informed managerial decisions in the development of the human resources of the vocational education system both at the level of the educational organization and at the level of public administration bodies. This model can be used to obtain information about the formation of digital competencies of different groups: employees of organizations and enterprises, state and municipal employees.

1. Panyukova S.V., Gostin A.M., Avilkina S.V. Human Capital Management in the Information Society. Ekonomika, statistika i informatika. Vestnik UMO = Economics, Statistics and Informatics. Bulletin of UMO. 2014; 1: 184-186. (In Russ.)

2. Yershova T.V., Ziva S.V. Key competencies in the digital economy [Internet]. Natsional'nyy tsentr tsifrovoy ekonomiki MGU im. M.V.Lomonosova, Lomonosovskiye chteniya v MGU = National Center for Digital Economy, Moscow State University. MV Lomonosov, Lomonosov readings at Moscow State University. 2018. [Internet]. Available from: https://digital.msu.ru/wp-content/uploads/20180419%D0%95%D1%80%D1%88%D0%BE%D0%B2%D0%B0_%D0%97%D0%B8%D0%B2%D0%B0.pdf. (cited 16.06.2020). (In Russ.)

3. Davydov S. G., Logunova O. S. Project "Index of digital literacy": methodological experiments. Sotsiologiya: metodologiya, metody, matematicheskoye modelirovaniye = Sociology: methodology, methods, mathematical modeling. 2015; 41: 120-141. (In Russ.)

4. New Vision for Education. Unlocking the Potential of Technology. World Economic Forum report. 2015. [Internet]. Available from: http://widgets.weforum.org/nve-2015/. (cited 17.07.2020).

5. Digital Literacy, Libraries, and Public Policy. Report of the Office for Information Technology Policy's. [Internet]. 2013. Available from: https://districtdispatch.org/wpcontent/uploads/2013/01/2012_OITP_digilitreport_1_22_13.pdf. (cited 06.07.2020).

6. Shut down or restart? The way forward for computing in UK schools. [Internet]. 2012. Available from: https://royalsociety.org/topicspolicy/projects/computing-in-schools/report/. (cited 06.07.2020).

7. World Telecommunication/ICT Development Report 2010: Monitoring the WSIS Targets. [Internet]. 2010. Available from: http://www.itu.int/ITU-D/ict/publications/wtdr_10/material/WTDR2010_e_v1.pdf. (cited 07.07.2020).

8. Education and training glossary (Online repository (Accessed in January 2016)) European Union commission (Eurostat) [Internet]. 2016. Available from: https://ec.europa.eu/eurostat/statistics-explained/index.php/Statistics_Explained. (cited 07.07.2020).

9. Programma «Tsifrovaya ekonomika Rossiyskoy Federatsii». Utverzhdena Rasporyazheniyem Pravitel'stva Rossiyskoy Federatsii № 1632-r ot 28 iyulya 2017g. = Program "Digital Economy of the Russian Federation". Approved by the Order of the Government of the Russian Federation No. 1632-r dated July 28, 2017. [Internet]. Available from: http://static.government.ru/media/files/9gFM4FHj4PsB79I5v7yLVuPgu4bvR7M0.pdf (cited 07.07.2020). (In Russ.)

10. Struktura IKT-kompetentnosti uchiteley. Rekomendatsii YUNESKO = Structure of ICT competence of teachers. UNESCO recommendations. [Internet]. Available from: https://unesdoc.unesco.org/ark:/48223/pf0000213475_rus. (cited 05.07.2020). (In Russ.)

11. Yershov A. P. Informatization: from computer literacy of students to the information culture of society [Internet] // Kommunist = Communist. 1988; 2: 82–92. Available from: http://ershov.iis.nsk.su/ru/node/772058 (cited 05.07.2020). (In Russ.)

12. Aksyanov I.M. Metodicheskiye podkhody k sovershenstvovaniyu informatsionnoy podgotovki prepodavateley uchrezhdeniy sistemy srednego professional'nogo obrazovaniya: na primere kursa informatiki dlya sistemy povysheniya kvalifikatsii: dissertatsiya = Methodological approaches to improving the information training of teachers of institutions of the secondary vocational education system: on the example of a computer science course for the advanced training system: dissertation [Internet]. Moscow: Institute of Informatization of Education, Russian Academy of Education; 2004: 192 p. Available from: https://rusneb.ru/catalog/000199_000009_002849162/. (cited 11.07.2020). (In Russ.)

13. Aymaletdinov T.A., Baymuratova L.R., Zaytseva O.A., Imayeva G.R., Spiridonova L.V. Tsifrovaya gramotnost' rossiyskikh pedagogov. Gotovnost' k ispol'zovaniyu tsifrovykh tekhnologiy v uchebnom protsesse. Analiticheskiy tsentr NAFI = Digital literacy of Russian teachers. Readiness to use digital technologies in the educational process. Analytical Center NAFI. Moscow: NAFI Publishing House; 2019: 84 p. (In Russ.)

14. Barannikova I.V., Shaforostova Ye.N. Methodology for assessing the quality of education in higher educational institutions. Statistika i ekonomika = Statistics and Economics. 2018; 15(6): 36-45. DOI: 10.21686/2500-3925-2018-6-36-45. (In Russ.)

15. Potasheva O.V., Moroshkina M.V. Statistical assessment of regional differences in the subjects of the Russian Federation in terms of the educational potential of young generations of the population. Statistika i Ekonomika = Statistics and Economics. 2018; 15(2): 38-48. DOI: 10.21686/2500-3925-2018-2-38-48. (In Russ.)

16. Epshteyn N.D., Yegorova Ye.A., Smelov P.A. Approaches to typologization of migration flows in the Russian Federation. Ekonomika, Statistika i Informatika. Vestnik UMO = Economics, Statistics and Informatics. Bulletin of UMO. 2014; 3: 175- 180. (In Russ.)

17. Minashkin V.G., Prokhorov P.E. Statistical analysis of the use of digital technologies in organizations: a regional aspect. Statistika i Ekonomika = Statistics and Economics. 2018; 15(5): 51-62. DOI: 10.21686/2500-3925-2018-5-51-62. (In Russ.)

18. Bychkova C.G., Parshintseva L.S. Information and communication technologies as the basis for the development of the information society: Russia in the system of international statistical indicators. Statistika i ekonomika = Statistics and Economics. 2019; 16(1): 32-40 DOI: 10.21686/2500-3925-2019-1-32-40. (In Russ.)

19. Abdrakhmanova G.I., Vishnevskiy K. O., Gokhberg L. M et al. Indikatory tsifrovoy ekonomiki: 2019. Statisticheskiy sbornik = Indicators of the digital economy: 2019. Statistical collection. Moscow: NRU HSE; 2019: 248 p. (In Russ.)

20. Rogozhin S. A. Material and technical support of the educational process - a necessary condition for the quality of education. Universitetskoye upravleniye: praktika i analiz = University management: practice and analysis. 2004; 4(32): 19- 26. (In Russ.)

21. Arkhipova M.YU., Prokhorov P.E. Statistical research of information and communication activities in the Russian Federation. Drukerovskiy vestnik = Drucker Bulletin. 2014; 2: 59-71. (In Russ.)

22. Sal'nikov N.V., Burukhin S.A Reforming higher education: current state and problems [Internet]. Vyssheye obrazovaniye v Rossii = Higher education in Russia. 2008; 8: 3-13. Available from: https://cyberleninka.ru/article/n/reformirovanievysshey-shkoly-aktualnoe-sostoyanie-i-problemy (cited 20.06.2020). (In Russ.)

23. Karpova O.L., Belyayeva E.B. Updating the teacher's professional training in the use of information and communication technologies. Regional'naya ekonomika: teoriya i praktika = Regional economy: theory and practice. 2014; 2: 58-62. (In Russ.)

24. Mikhalov A.V., Chepovskiy A.M. Problems of professional and educational standards in computer science and information technology. Prikladnaya informatika = Applied Informatics. 2006; 4: 15-22. (In Russ.)

25. Gorokhova I.YU. Podgotovka prepodavateley kolledzha tekhnicheskogo profilya k ispol'zovaniyu informatsionnykh i kommunikatsionnykh tekhnologiy v obrazovatel'nom protsesse: dissertatsiya = Training college teachers of technical profile for the use of information and communication technologies in the educational process: dissertation [Internet]. Stavropol: North Caucasus State Technical University. 2006: 188 p. Available from: https://rusneb.ru/catalog/000199_000009_003291094/ (cited 06.07.2020). (In Russ.)

26. Avilkina S.V. Competence-based approach to assessing the human resources potential of the digital economy of the region. Regional'naya ekonomika: teoriya i praktika = Regional economy: theory and practice. 2020; 18; 5: 846– 69. DOI: 10.24891/re.18.5.846. (In Russ.)

27. Avilkina S.V., Bakuleva M.A., Kleynosova N.P. Mathematical model of the formation of a basic statistical sample for assessing the level of mastering digital competencies of teachers. Statistika i Ekonomika = Statistics and Economics. 2018; 15(6): 26-35. DOI: 10.21686/2500-3925-2018-6-26-35. (In Russ.)