Planning Educational Infrastructure in Kazakhstan under Demographic Growth with Digital Decision-Support Tools
https://doi.org/10.51176/1997-9967-2025-3-85-105
Abstract
Accelerated and uneven demographic growth in Kazakhstan is shaping spatially differentiated demand dynamics for places in early childhood education institutions and first-grade classes, necessitating anticipatory planning. The aim of the study is to analyze the impact of demographic growth on preschool and primary education infrastructure, to forecast the demand for places using the cohort-age method, and to develop targeted recommendations to prevent infrastructure shortages. The study applies an agecohort (cohort-component) projection integrated with Geographic Information Systems (GIS) and business intelligence (BI) visualization to assess regional needs without relying on school “capacity” calculations. In 2029, the number of preschool-age children is expected to increase primarily in the southern and western regions, indicating the need to expand the network of early childhood education providers. By 2030, the highest first-grade intake is projected in Almaty region (approximately 5.8 thousand), Kyzylorda region (approximately 5.4 thousand), and Shymkent city (approximately 5.9 thousand). Regression analysis confirmed the significant impact of fertility (β=0.48; p<0.01) and migration (β=0.31; p<0.05) on the infrastructural load. These estimates provide a foundation for prioritizing and phasing in additional seats, planning workforce needs, targeting the allocation of resources and subsidies, and aligning construction plans with anticipated demographic dynamics, measures that will promote more equitable access to education and strengthen the resilience of regional systems.
Keywords
About the Authors
Gaukhar B. AidarkhanovaKazakhstan
Gaukhar B. Aidarkhanova – PhD, Senior Lector,
71, al-Farabi Ave., Almaty.
Gaukhar B. Aubakirova
Kazakhstan
Gaukhar B. Aubakirova – Senior Lector,
71, al-Farabi Ave., Almaty.
Gulnara N. Nyussupova
Russian Federation
Gulnara N. Nyussupova – Doc. Sc (Geogr.), Professor,
71, al-Farabi Ave., Almaty.
Chingiz B. Zhumagulov
Russian Federation
Chingiz B. Zhumagulov – PhD student,
71, al-Farabi Ave., Almaty.
Abzal M. Zhakypbek
Russian Federation
Abzal M. Zhakypbek – Senior Lector,
71, al-Farabi Ave., Almaty.
References
1. Abdullah, S., Hussain, N. H. M., Haron, N., Jalil, S. A., & Osoman, M. A. (2023). GIS-based interactive technology in demographic record management and mapping towards sustainable community. International Journal of Sustainable Construction Engineering and Technology, 14(3), 366–375. https://doi.org/10.30880/ijscet.2023.14.03.031
2. Abuov, A. (2010). Ethnic differentiation of fertility in Kazakhstan [Master’s thesis, Charles University].
3. Alfredini, P., Martins, L. F., & Neves, R. C. (2024). Statistical assessment of extreme storm events on the Brazilian continental shelf from 1940 to 2022. Journal of Coastal Research, 113(Sp1), 175-179. http://dx.doi.org/10.2112/JCR-SI113-035.1
4. Amanda, A. R. (2025). Application of machine learning for determining bus stop locations in Surabaya City based on the 15-minute city approach [Master’s thesis, ITS Surabaya].
5. Anselin, L. (1995). Local indicators of spatial association-LISA. Geographical Analysis, 27(2), 93–115. https://doi.org/10.1111/j.1538-4632.1995.tb00338.x
6. Anselin, L., & Griffith, D. A. (1988). Do spatial effects really matter in regression analysis? Papers in Regional Science, 65(1), 11-34. https://doi.org/10.1111/j.1435-5597.1988.tb01155.x
7. Asylbekov, M. Kh., & Galiev, A. B. (1991). Sotsial’no-demograficheskie protsessy v Kazakhstane (1917–1980) [Socio-demographic processes in Kazakhstan (1917–1980)]. Almaty: Gylym. (In Russ)
8. Aubakirova, Zh., Alekseenko, A., Stolyarova, E., Krasnobaeva, N., & Omirzak, T. (2022). Demograficheskaya bezopasnost’ Kazakhstana: Potentsial, riski i perspektivy [Demographic security of Kazakhstan: Potential, risks, and prospects]. D. Serikbayev East Kazakhstan Technical University (In Russ)
9. Balgarina, L., Jumabayev, S., & Shokamanov, Y. (2022). Prognozirovanie sotsial’no-ekonomicheskogo razvitiya regionov v Kazakhstane: Printsipy, osobennosti i nedostatki [Forecasting of socio-economic development of regions in Kazakhstan: Principles, features and disadvantages]. Economy: strategy and practice, 17(4), 76–91. https://doi.org/10.51176/1997-9967-2022-4-7691 (In Russ)
10. Batty, M., & Longley, P. A. (2003). Advanced spatial analysis: The CASA book of GIS. ESRI Press.
11. Brown, D. L., & Schafft, K. A. (2018). Rural people and communities in the 21st century: Resilience and transformation. Polity Press.
12. Bureau of National Statistics. (2024). Bureau of National Statistics of the Republic of Kazakhstan. July 05, 2025 from https://stat.gov.kz/en
13. Chanda, R. (2024). Predictive modelling of urban growth pattern: A study of Burdwan City. Urban Planning & Development Journal, 15, 203-217.
14. Engin, Z., Dijk, J., Lan, T., Longley, P., Treleaven, P., Batty, M., & Penn, A. (2020). Data-driven urban management: Mapping the landscape. Journal of Urban Management, 9, 140–150. https://doi.org/10.1016/j.jum.2019.12.001
15. Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996). From data mining to knowledge discovery in databases. AI Magazine, 17, 37. https://doi.org/10.1609/aimag.v17i3.1230
16. Frey, W. H. (2018). Diversity explosion: How new racial demographics are remaking America. Brookings Institution Press.
17. Ghanghas, A. (2025). Rise of the storms: A tale of altering extreme precipitation characteristics in a warming world [Doctoral dissertation, Purdue University].
18. Goodchild, M., Haining, R., & Wise, S. (1992). Integrating GIS and spatial data analysis: Problems and possibilities. International journal of geographical information systems, 6(5), 407–423. https://doi.org/10.1080/02693799208901923
19. Goodchild, M. F. (1992). Geographical information science. International journal of geographical information systems, 6(1), 31–45. https://doi.org/10.1080/02693799208901893
20. Goodchild, M. F., Anselin, L., Appelbaum, R. P., & Harthorn, B. H. (2000). Toward spatially integrated social science. International Regional Science Review, 23(2), 139–159. https://doi.org/10.1177/016001760002300201
21. Grossman, I., Hosseini-Chavoshi, M., & Temple, J. (2024). Demographic projections in Australia: Implications for educational and urban planning (Working Paper, 1–27). ARC Centre of Excellence in Population Ageing Research. Retrieved July 05, 2025 from https://www.cepar.edu.au/sites/default/files/WP2024%3A27.pdf
22. Taldau. (2025). Information-Analytical System. Retrieved July 05, 2025 from https://taldau.stat.gov.kz/ Isazade, V., Qasimi, A. B., Dong, P.. (2023). Integration of Moran’s I, geographically weighted regression (GWR), and ordinary least square (OLS) models in spatiotemporal modeling of COVID-19 outbreak in Qom and Mazandaran provinces, Iran. Model. Earth Syst. Environ., 9, 3923–3937. https://doi.org/10.1007/s40808-023-01729-y
23. Kireyeva, A. A., Bekturganova, M., & Alzhanova, F. (2023). Qazaqstan aimaqtaryndaǵy khalyqtyń qonys audaruynyń demografiyalyq protsesterin taldau [Analysis of demographic processes of population settlement in the regions of Kazakhstan]. Economic Series of the Bulletin of L. N. Gumilyov ENU, 3, 40–54. https://doi.org/10.32523/2789-4320-2023-3-40-54 (In Kaz)
24. Lee, R., & Mason, A. (2011). Population aging and the generational economy: A global perspective. Edward Elgar Publishing.
25. Logan, J. R., & Molotch, H. (2007). Urban fortunes: The political economy of place. University of California Press.
26. Lubienski, C., & Gulosino, C. (2009). School choice and competitive incentives: Mapping the distribution of educational opportunities across local education markets. American Journal of Education, 115(4), 601–647. https://doi.org/10.1086/599778
27. Mahdavi, S., Anthony, N. M., Sikaneta, T., & Tam, P. Y. (2025). Multiomics and artificial intelligence for personalized nutritional management of diabetes in patients undergoing peritoneal dialysis. Advances in Nutrition, 16(3), 100378. https://doi.org/10.1016/j.advnut.2025.100378
28. Meshkini, A. (2024). Spatial analysis of housing resilience against natural hazards with an emphasis on earthquakes: A case study of southern regions of Tehran metropolis. Geographical Planning of Space, 89, 118. http://dx.doi.org/10.1007/s10708-024-11101-x
29. Miller, H. J., & Han, J. (Eds.). (2009). Geographic data mining and knowledge discovery (2nd ed.). CRC Press. https://doi.org/10.1201/9781420073980
30. Milusheva, S., Marty, R., Bedoya, G., Williams, S., Resor, E., & Legovini, A. (2021). Applying machine learning and geolocation techniques to social media data (Twitter) to develop a resource for urban planning. PLOS ONE, 16, e0244317. https://doi.org/10.1371/journal.pone.0244317
31. Ministry of Education of the Republic of Kazakhstan. (2022). Order of the Minister of Education of the Republic of Kazakhstan No. 385. Retrieved July 05, 2025 from https://adilet.zan.kz/rus/docs/G25HP000031
32. National Platform for Reporting on Sustainable Development Goals. (2025). SDG National Platform (Kazakhstan). Retrieved July 05, 2025 from https://kazstat.github.io/sdg-site-kazstat/en/
33. Nyussupova, G., Aidarkhanova, G., Kadylbekov, M., Kenespayeva, L., Kelinbayeva, R., & Kozhakhmetov, B. (2021). Nationalization of indicators for sustainable development goals in the Republic of Kazakhstan through geoinformation technologies. GI_Forum, 9(1), 158–168. https://doi.org/10.1553/giscience2021_01_s158
34. OECD. (2022). Education at a glance 2022: OECD indicators. OECD Publishing.
35. Ospan, A. G., Mansurova, M., Kakimzhanov, Y., Ixanov, S. Sh., & Barakhnin, V. B. (2022). Development of a program for the integration of socio-economic indicators with spatial data to analyze the standard of living of the population of Kazakhstan. Bulletin of the NEA RK, 3(85), 67–77. https://doi.org/10.47533/2020.1606-146x.170
36. Parkes, E. A. (2013). Mode of communication of cholera by John Snow, MD: Second edition. International Journal of Epidemiology, 42, 1543–1552. https://doi.org/10.1093/ije/dyt193
37. Rahman, M. T., Jamal, A., & Al-Ahmadi, H. M. (2020). Examining hotspots of traffic collisions and their spatial relationships with land use: A GISbased geographically weighted regression approach for Dammam, Saudi Arabia. ISPRS International Journal of Geo-Information, 9(9), 540. https://doi.org/10.3390/ijgi9090540
38. Sachs, J. D., Schmidt-Traub, G., Mazzucato, M., & Messner, D. (2019). Six Transformations to achieve the Sustainable Development Goals. Nature Sustainability 2(9), 805–814. http://dx.doi.org/10.1038/s41893-019-0352-9
39. Sagwa, D., Stephen, O., & Jason, N. (2024). Projection models for selected infrastructural requirements for the implementation of competency-based curriculum in senior secondary schools in 2026, in Kenya. Journal of Education Management and Leadership, 3(1), 63-75. http://dx.doi.org/10.51317/jeml.v3i1.647
40. Slabodich, K. A., Tagirova, E. R., & Shavrov, S. A. (2017). O sozdanii pravovoy osnovy infrastruktury prostranstvennykh dannykh v Belarusi i Kazakhstane [On the creation of the legal framework of the infrastructure of spatial data in Belarus and Kazakhstan]. Proceedings of BSTU. Series 5: Economics and Management, 1(5), 129–133. (In Rus)
41. Spankulova, L. S., & Chulanova, Z. K. (2022). Demographic processes in Kazakhstan: Current trends and forecasting the future development. Bulletin of Turan University, 3, 60–71. https://doi.org/10.46914/15622959-2022-1-3-60-71
42. Spankulova, L.S, Chulanova, Z. K., Nurmakhanova, M., & Kangalakova, D. (2023). Assessment of the parameters of the future demographic situation in Kazakhstan. Society and Security Insights, 4(5), 50–69. https://doi.org/10.14258/SSI(2022)4-03
43. Spoorenberg, T. (2013). Fertility changes in Central Asia since 1980. Asian Populution Studies, 9(1), 50–77. https://doi.org/10.1080/17441730.2012.752238
44. Sun, Z., & Wu, Z. (2022). A strategic perspective on big data driven socioeconomic development. In Proceedings of the 5th International Conference on Big Data Research (pp. 35–41).ACM https://doi.org/10.1145/3505745.3505751
45. Sunday, A. P., Jibo, A., & Yohanna, L. (2024). A meta-analysis of Nigeria’s population census results falsification and its implications. Wukari International Studies Journal, 8(3), 81-91
46. Talen, E. (2001). School, community, and spatial equity: An empirical investigation of access to elementary schools in West Virginia. Annals of the Association of American Geographers, 91(3), 465–486. https://doi.org/10.1111/0004-5608.00254
47. Tetiana, B., & Xin, C. (2024). Demographic processes and economic growth in China: Simulation forecasting. In New areas of scientific research: Exploring new frontiers (pp. 59–72).
48. Tobler, W. R. (1970). A computer movie simulating urban growth in the Detroit region. Supplement: Proceedings. International Geographical Union. Commission on Quantitative Methods, 46, 234–240. https://doi.org/10.2307/143141
49. Tomlinson, R. F. (1969). A geographic information system for regional planning. Journal of Geography, 78(1), 45-48. https://doi.org/10.5026/jgeography.78.45
50. Toreti, A., Tsagai, D., Maurer, T., Cremonese, E., & Rossi, L. (2024). World drought atlas. University of Milan.
51. UNESCO. (2022). Global education monitoring report 2022. UNESCO Publishing.
52. World Bank. (2022). World development report 2022: Data for better lives. The World Bank.
53. Zhantayev, Z. S., Nurakynov, S. M., Gavruk, S. V., Iskakov, B. A., Sydyk, N. K., & Merekeyev, A. A. (2020). Creation of a geoportal and its role in operational monitoring of the natural and manmade emergency character in the territory of the Republic of Kazakhstan. News NAS RK. Series of Physico-Mathematical, 3(331), 191–201. http://dx.doi.org/10.32014/2020.2518-1726.53
Review
For citations:
Aidarkhanova G.B., Aubakirova G.B., Nyussupova G.N., Zhumagulov Ch.B., Zhakypbek A.M. Planning Educational Infrastructure in Kazakhstan under Demographic Growth with Digital Decision-Support Tools. Economy: strategy and practice. 2025;20(3):85-105. (In Kazakh) https://doi.org/10.51176/1997-9967-2025-3-85-105