Development of a Climate-Mapped Educational Risk Index for Thailand
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Abstract
Education systems worldwide, including Thailand's, face increasing vulnerability to climate change–related disasters, particularly in rural and socioeconomically disadvantaged areas. Although global policy frameworks emphasize protecting children from environmental risks, existing indices lack spatial granularity and do not directly incorporate educational outcomes into their structure. This study aims to (1) develop a spatial index of educational risk linked to climate conditions—the Climate-Mapped Educational Risk Index (CMER)—and (2) analyze the relationships between this index and geographic, school, and student factors. The study integrated school-level O-NET scores from four core subjects across 30,112 schools during 2017–2021 with high-resolution climate data from the SEACLID/CORDEX-SEA project covering the same period relative to a baseline of 1970–2007. The CMER Index was developed using Principal Component Analysis of extreme climate variables and student achievement, with schools classified by risk levels using ROC-based criteria. Elastic Net regression was then applied to analyze relationships between CMER scores and risk factors across educational service areas, followed by the construction of a Risk–Importance Matrix (RIM) to support policy decision-making.
The results revealed that the duration of extreme precipitation events was the only dimension showing a significant structural relationship with student achievement. Schools in the Northern, Northeastern, Central, and Southern regions exhibited higher risk levels. RIM analysis indicated that educational factors amplify risk to varying degrees across different areas, underscoring the need for context-specific interventions. The CMER Index and RIM provide a data-driven framework for identifying climate-linked educational risks and targeting resource allocation to build a more equitable and climate-resilient education system.
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References
Adler, C., Wester, P., Bhatt, I., Huggel, C., Insarov, G. E., Morecroft, M. D., Muccione, V., & Prakash, A. (2022). Cross-Chapter Paper 5: Mountains. In H. O. Pörtner, D. C. Roberts, M. Tignor, E. S. Poloczanska, K. Mintenbeck, A. Alegría, M. Craig, S. Langsdorf, S. Löschke, V. Möller, A. Okem, & B. Rama (Eds.), Climate change 2022: Impacts, adaptation and vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (pp.2273-2318). Cambridge University Press. https://doi.org/10.1017/9781009325844.022
Auer-Frege, I., Befus, E., Bih, K. B., Fawwad, M., Ide, T., Kiefer, M., Kienzl, P., Klüppel, D., Korte, L., Kortendieck, M., Moloinyane, S., Peters, K., Radtke, K., Schneider, S., & Weller, D. (2024). WorldRiskReport 2024: Focus on education and vulnerability to climate risks. Bündnis Entwicklung Hilft & Institute for International Law of Peace and Armed Conflict. https://weltrisikobericht.de/worldriskreport/
Auer-Frege, I., Bliecke, V., Bradshaw, S., Dijkzeul, D., Funke, C., Kienzl, P., Küsters, K., Masuch, L., Nasreen, M., Radtke, K., Schneider, S., Thielbörger, P., Weller, D., Wiegers, O., Yaman, D. K., & Zennig, K. (2023). WorldRiskReport 2023: Focus on diversity. Bündnis Entwicklung Hilft & Institute for International Law of Peace and Armed Conflict. https://weltrisikobericht.de/worldriskreport/
Bündnis Entwicklung Hilft & Ruhr-Universität Bochum, Institut für Internationales Friedens- und Konfliktrecht (IFHV). (2024). WorldRiskReport 2024: Multiple crises. https://securesustain.org/wp-content/uploads/2024/10/WorldRiskReport_2024.pdf
Duchek, S. (2020). Organizational resilience: A capability-based conceptualization. Business Research, 13(1), 215–246. https://doi.org/10.1007/s40685-019-0085-7
Eckstein, D., Künzel, V., & Schäfer, L. (2021). Global climate risk index 2021: Who suffers most from extreme weather events? Weather-related loss events in 2019 and 2000-2019. Germanwatch. https://germanwatch.org/en/cri
Google. (2024). Google Maps Platform documentation. https://developers.google.com/maps
Gottfried, M. A. (2014). Chronic absenteeism and its effects on students’ academic and socioemotional outcomes. Journal of Education for Students Placed at Risk, 19(1–2), 53–75. https://doi.org/10.1080/10824669.2014.962696
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2021). Multivariate data analysis (9th ed.). Cengage.
International Organization for Standardization. (2018). ISO 31000:2018 Risk management—Guidelines. Author.
Intergovernmental Panel on Climate Change. (2023). Climate change 2023: Synthesis report. Summary for policymakers. IPCC. https://doi.org/10.59327/IPCC/AR6-9789291691647.001
Jolliffe, I. T., & Cadima, J. (2016). Principal component analysis: A review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2065), Article 20150202. https://doi.org/10.1098/rsta.2015.0202
Landell, H. (2016). The risk matrix as a tool for risk analysis: How to apply existing theories in practice in order to overcome its limitations [Master’s thesis, University of Gävle]. DiVA Portal. https://www.diva-portal.org/smash/get/diva2:944825/FULLTEXT01.pdf
Liu, J., Lee, M., & Gershenson, S. (2021). The short- and long-run impacts of secondary school absences. Journal of Public Economics, 199, Article 104441. https://doi.org/10.1016/j.jpubeco.2021.104441
Martilla, J. A., & James, J. C. (1977). Importance-Performance Analysis. Journal of Marketing, 41(1), 77–79. https://doi.org/10.2307/1250495
Ngo-Duc, T., Tangang, F. T., Santisirisomboon, J., Cruz, F., Trinh-Tuan, L., Nguyen-Xuan, T., & Aldrian, E. (2016). Performance evaluation of RegCM4 in simulating extreme rainfall and temperature indices over the CORDEX-Southeast Asia region. International Journal of Climatology, 37(3), 163-182. https://doi.org/10.1002/joc.4803
Park, J., Goodman, J., Hurwitz, M., & Smith, J. (2020). Heat and learning. American Economic Journal: Economic Policy, 12(2), 306-339. https://doi.org/10.1257/pol.20180612
Rivadeneira Moreira, J. C. (2025). Risk management in education: A systematic
literature review of the last five years. Revista de Gestión Social y Ambiental, 19(1), e010977. https://doi.org/10.24857/rgsa.v19n1-127
Sutcliffe, K. M., & Vogus, T. J. (2003). Organizing for resilience. In K. S. Cameron, J. E. Dutton, & R. E. Quinn (Eds.), Positive organizational scholarship: Foundations of a new discipline (pp. 94–110). Berrett-Koehler Publishers.
Thampanishvong, K., Santisirisomboon, J., Sumano, B., Channuntapipat, C., Ngaosri, K., Witoonchart, P., Kaewbuadee, N., & Pinkaew, L. (2022). Impact assessment of climate change and environmental degradation on children in Thailand. Thailand Development Research Institute. https://www.unicef.org/thailand/media/10361/file/Climate%20Change%20Impact%20Assessment%20-%20Full%20report.pdf
Unal, I. (2017). Defining an optimal cut-point value in ROC analysis: An alternative approach. Computational and Mathematical Methods in Medicine, 2017, Article 3762651. https://doi.org/10.1155/2017/3762651
UNICEF. (2021). The climate crisis is a child-rights crisis: Introducing the Children’s Climate Risk Index. https://www.unicef.org/reports/climate-crisis-child-rights-crisis
United Nations Office for Disaster Risk Reduction. (2015). Sendai Framework for Disaster Risk Reduction 2015–2030. UNDRR.
Zivin, J. G., & Neidell, M. (2014). Temperature and the allocation of time: Implications for climate change. Journal of Labor Economics, 32(1), 1-26. https://doi.org/10.1086/671766
Srisuttiyakorn, S. (2019). Educational inequality and its factors: Multilevel analysis integrated with median-based class of generalized entropy inequality index. Journal of Research Methodology, 32(3), 342–379. (in Thai)
