Valentyna Gapon
https://orcid.org/0000-0001-7521-5450
Lyudmyla Chimbay
https://orcid.org/0000-0002-4647-2471
APPLICATION OF ECONOMIC AND MATHEMATICAL METHODS FOR DEVELOPING FORECASTS IN THE FIELD OF GENERAL SECONDARY EDUCATION
Full text (pdf)
Language: Ukrainian
Abstract. The military aggression of the russian federation against Ukraine and the introduction of martial law in Ukraine caused serious problems with the collection, processing and analysis of the necessary statistical and administrative information. In particular, it was necessary to predict the number of first-graders and enrollment of pupils in general secondary schools at the beginning of the 2022/2023 school year and especially school leavers, who are expected to become potential entrants to higher education, pre-tertiary vocational and vocational education institutions. When developing a model for forecasting the number of first-graders, a functional dependence was determined that adequately describes the development trends of this indicator, and consisted in obtaining the minimum average absolute deviation of the forecast value from the actual. In the course of the study, we developed trend models for forecasting the number of first-grade students for each region and determined the mathematical characteristics of the forecast model. For a more detailed study, we consider factor analysis models in order to examine the relationship between the number of first-graders and the number of children born. Based on the regression analysis, the type of function was determined; regression coefficients and theoretical values of the resulting indicator were calculated; and the statistical significance of the equation and regression coefficients was tested. In this way, we received a target forecast of the number of students for the 2022/2023-2024/2025 school years. Given the large-scale temporary displacement of the population, in particular families with children to safer regions, we consider it expedient to calculate the forecast values of the number of first-grade students using trend models for Ukraine as a whole and by region, taking into account internally displaced persons. Factor models should be used only to develop a forecast for Ukraine as a whole, since forecasting from the number of births by region is not meaningful in today’s conditions and is possible only in the post-war period. The prospect of further research in this direction is the development of economic and mathematical models for forecasting the total number of school students, the number of pedagogical staff and teachers of certain subjects in general secondary schools.
Keywords: general secondary education, number of students in first grades, school student contingent, forecasting methods and models, regression and correlation analysis, forecast evaluation.
https://doi.org/10.32987/2617-8532-2023-2-108-121
Keywords: general secondary education, number of students in first grades, school student contingent, forecasting methods and models, regression and correlation analysis, forecast evaluation.
https://doi.org/10.32987/2617-8532-2023-2-108-121
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3. Onyshchuk, L. A. (2016). The concept of forecasting the development of general secondary education. Kyiv: Pedahohichna dumka. Retrieved from https://undip.org.ua/wp-content/uploads/2021/08/kontseptsiya_prognozuvannya_rozvytku_zagalnoyi_serednoyi_osvity_2016.pdf [in Ukrainian].
4. Pusikov, D. (2017). Theoretical model for prediction of general secondary education development. Ukrainian Educational Journal, 4, 128-137. Retrieved from https://uej.undip.org.ua/index.php/journal/article/view/575 [in Ukrainian].
5. Mushka, O. (2018). Secondary education development forecasting models developed in the independent Ukraine in the contents of teacher’s pedagogical forecasting manual. Problems of the Modern Textbook, 21, 271-282. DOI: https://doi.org/10.32405/2411-1309-2018-21-271-283 [in Ukrainian].
6. Mezentseva, O. (2017). International factors of influence on the comprehensive secondary education development. Ukrainian Educational Journal, 4, 18-26. Retrieved from http://nbuv.gov.ua/UJRN/ukrpj_2017_4_5 [in Ukrainian].
7. Klimchuk, I. (2016). Research on criteria and indicators for the development of general secondary education in Ukraine. ScienceRise: Pedagogical Education, 10, 19-26. Retrieved from http://nbuv.gov.ua/UJRN/texcped_2016_10_6 [in Ukrainian].
8. Tsymbalaru, A. D. (2013). Pedagogical design of educational space in a school of the first degree: theory and practice. Kyiv: Pedahohichna dumka [in Ukrainian].
9. Bakhrushyn, V. (2011). Data analysis methods. Zaporizhzhia: KPU. Retrieved from http://kist.ntu.edu.ua/textPhD/metDataManing.pdf [in Ukrainian].
10. Klebanova, T. S., Kurzenev, V. A., Naumov, V. M., Hurianova, L. S., Cherniak, O. I., Zakharchenko, P. V., & Serhiienko, O. A. (2015). Forecasting of social and economic processes. Kharkiv: KhNEU named after S. Kuznets. Retrieved from http://repository.kpi.kharkov.ua/bitstream/KhPI-Press/37928/3/Book_2015_Klebanova_Prohnoz_sots_ekon_protsesiv.pdf [in Ukrainian].
11. Kryvda, O. V., Sydorenko, Iu. V., & Romanova, D. P. (2017). Forecasting the dynamics of economic processes by the methods of fractal geometry. Economic Bulletin of NTUU “Kyiv Polytechnical Institute”, 14. DOI: https://doi.org/10.20535/2307-5651.14.2017.108714 [in Ukrainian].
12. Sehida, K. (2016). Methodical bases of geodemographic forecasting. Problems of Continuous Geographic Education and Cartography, 24, 109-116. Retrieved from http://nbuv.gov.ua/UJRN/Pbgo_2016_24_26 [in Ukrainian].
13. Gapon, V., Barabash, O., & Chimbay, L. (2021). Analysis of the demographic situation and forecast estimation of the number of first grade students. Educational analytics of Ukraine, 2(13), 101-116. DOI: https://doi.org/10.32987/2617-8532-2021-2-101-116 [in Ukrainian].
14. Gapon, V. & Chimbay, L. (2022). Assessment of the accuracy of the developed forecast of the student population in full-time general secondary education institutions. Educational analytics of Ukraine, 2(18), 72-87. DOI: https://doi.org/10.32987/2617-8532-2022-2-72-87 [in Ukrainian].
15. Bredyuk, V. I., Vasyliv, V. B. & Dzhoshi, O. I. (2015). Prognostification of graduates’ number of middle general secondary educational establishments of levels II and III in Rivne region. Learning technologies, 14, 31-36. Rivne: NUVGP. Retrieved from https://ep3.nuwm.edu.ua/1603/ [in Ukrainian].
16. SSI «Institute of Educational Analytics». (n. d.). Consolidated report of general secondary education institutions (form No. 76-RVK). Retrieved from https://iea.gov.ua/naukovo-analitichna-diyalnist/analitika/informatsijni-byuleteni/ [in Ukrainian].
17. State Statistics Service of Ukraine. (n. d.). Population of Ukraine. Retrieved from http://db.ukrcensus.gov.ua/MULT/Dialog/statfile_c.asp [in Ukrainian].