Improving access to education with climate analysis in Benin

Education for all is an integral part of the 2030 Agenda for Sustainable Development. It calls on countries to "ensure inclusive and equitable quality education and promote life-long learning opportunities for all" ( SDG 4 ) and includes a set of associated targets.

Education for Sustainable Development (ESD) is especially anchored in  target 4.7 , which highlights the importance of all learners acquiring the knowledge and skills needed to promote sustainable development and global citizenship for more equal and peaceful societies.

The COVID-19 pandemic has exacerbated the global learning crisis, with severe disruptions in education systems worldwide and countries falling short of achieving SDG 4. School closures have left worrisome consequences for children’s learning and well-being, particularly for girls and the disadvantaged, such as children with disabilities, rural dwellers and ethnic minorities, and those in Sub-Saharan region. An estimated 147 million children missed more than half of their in-person instruction over the past two years ( UNESCO ).

Governments need to implement ambitious programmes to ensure that all children return to school, recover their learning losses, and have their psychosocial needs met.

An important number of analyses have emerged on the effects of school time on learning. The crucial role of time devoted to teaching and learning, whether this is defined as instructional time,  learning time, time spent in school, or time spent in the classroom is widely recognized  (  IIEP-UNESCO, 2021  ;   GEM Report-UNESCO, 2014  ;   OECD, 2012  ;   UNESCO, 2012  ;   UNICEF, 2020  ;    World Bank, 2014  ).  The empirical studies on COVID-19 school closures conclude that school time is a key factor influencing learning loss ( Moscoviz and Evans, 2022 )

Time in school and its conversion into learning depends on many factors, including teacher presence, teacher preparation, classroom management, discipline, and others. One factor that has been understudied is the school calendar. Most countries set the school calendar uniformly throughout their national territory, neglecting local factors that may interfere with actual school attendance and therefore with time devoted to learning, especially in areas highly exposed to seasonal climatic risks (e.g., heavy rainfall and high temperatures), or economically dependent on cyclical activities (e.g., agriculture).

School calendars which have been often inherited from colonial times, rather than locally developed, are likely to be even less adapted to local realities ( World Bank, 2005 ). Current research ( Allen, 2022 ) on farming calendars also show that countries with a greater number of overlapping days in school and agricultural calendars have lower primary education completion rates.

Other research on sub-Saharan African countries shows that there is a negative correlation between rainfall and standardized test scores ( Bekkouche et al., 2019 ). Students from schools exposed to more rainy days achieve lower scores at the end of the school year.

Therefore, the  International Institute for Educational Planning  (IIEP of UNESCO) is currently leading experimental research to identify which shifts in the local school calendars could trigger greater gains in learning for students.

Evidence indicates that climate change is increasing the frequency and intensity of some extreme weather events and association between cyclical agriculture and school absenteeism.

In this regard, considering local factors is key to ensuring that quality instruction time leads to more inclusive learning (Unterhalter  2007 ,  2014 ) and authoritative data on administrative units would be critical for local level research or analysis.

The sub-national data for administrative level 1 & 2 for Benin is available for download with the latest update on 30 September 2021, through the Benin page. The  SALB programme  aims to make available a global repository of authoritative information and geospatial data about the administrative units structure of countries down to the second subnational level, and through time, in close collaboration with National Geospatial Information Authorities of each Member States of the United Nations, notably Institut Géographique National du Bénin.

The population estimates are calculated creating a 1 km grid clipped using the nationally owned administrative units made available through the SALB programme.

The methodology described in  Gagnon & Vargas Mesa (2021)  was used, together with spatialized 5-year population estimates from  WorldPop (2021) , to obtain the population by single years of age in 2020. This information was then adjusted using the  UN Population Division estimates  for 2023, with the totals for pre-primary, primary, lower secondary, and upper secondary, respectively.

To analyse impact of climate factors, specifically rainfall and temperature, temporal data are visualized to identify trends in administrative unit 2 levels, the “Communes”. The below map demonstrates disaggregated monthly mean precipitation at subnational 2 level from 2010 to 2020.

In general, during this decade, December, January, and February recorded higher temperatures and low rainfall, and June, July, and August recorded high rainfall and low temperatures.

Low rainfall months were observed in November, December, January, and February, while June, July, and August showed high rainfalls. Geographically administrative units near coastlines tended to have higher rainfall compared to those inland.

With respect to temperature, low temperature months were observed in June, July, August, and September, and high temperature months were in December, January, February, and March.

The monthly change patterns of precipitation and temperature can be easily comparable over ten years in the below data visualization :

The rainiest and hottest weeks of the 10 year period are demonstrated by administrative 2 level in the below 3D web map.

Using the administrative units'data, the spatial and temporal variation of rainfall and temperature for 10 years in Benin are illustrated, providing an opportunity to understand better and identify characteristics and patterns of the climate data.

This will be further used and expanded to all African countries to analyse the correlation between climate conditions and academic performance and providing evidence to document the benefits of local school calendars to optimize actual school time, improve inclusive access to education, and to encourage foundational learning.

In this context, the disaggregation of data to lower administrative levels would be critical.  The SALB programme, which advocates for a standardized approach and methodologies is beneficial not only to governments but also researchers, and international organizations.