ESRI Selected for Analysis in Kenya - 24/04/2007


The Ministry of Education (MOE) in Kenya has contracted Oakar Services Ltd. (OSL), ESRI's distributor in eastern Africa, to develop a GIS database of the educational facilities in the country.

Comments Thomas Ndegwa, technical director at OSL, "In a developing country such as ours where there is a large demand for donor aid, we are very fortunate that our government has taken the bold step to approve this project. It is a tribute to the forward thinking of the Kenyan government and its recognition of the critical importance of the education of our youth as well as its clear understanding of the value of spatial analysis in the decision-making process."

The project, started in December 2006, is valued at US$1 million, and is being funded with a grant from the United States Agency for International Development (USAID).

Despite improved performance in education, the government was concerned about a number of issues including overcrowded classrooms and the availability of educational resources. Other concerns included the lack of a clear view of the location and distribution of educational facilities in the country, as well as their condition, and the number, availability, and distribution of classroom instructors.

To improve access and equity in the provision of quality education throughout the country, the government began implementing the Kenya Education Sector Support Programme (KESSP) in 2005. A key part of KESSP was the development of a clear picture of the country's existing educational resources. It was determined that the implementation of a GIS could provide the necessary geographic view and analytic capabilities required to continue the improvement of education in the country.

The project involves recording the names of the schools, their locations (latitudes and longitudes), and their primary physical features. This information will be integrated with attribute data including school enrollment, number of teachers, and the school's educational resources, which will be collected in the field. When the location data is merged with attribute data and other demographic information, it will assist policy makers in obtaining answers to questions such as, Where are new schools needed now and in the future? Where are educational facilities limited or duplicated? Where are new teachers needed? Where is in-service training needed? Where is the nearest location where students can obtain elementary or secondary education? Where is significant population growth or decline expected?

Last updated: 21/10/2020