A study of secondary schools' costs and indicators in the Sudan
thesisposted on 29.11.2010, 10:22 by Leila T. Salih
Comprehensive educational planning has been adopted in Sudan since independence in 1956. The inadequate projection of resources for the plans' implementation has bedevilled the full achievement of their targets and led to frustration with the planning process. Relevant cost data for unit costs analysis, which gives a quantified framework within which it is possible to estimate in advance the financial and economic implications of structural changes and educational programmes and projects at the micro or macro levels and hence lead to more informed decision-making, are not available on a systematic basis at any level of aggregation. In the last decade as the adverse economic conditions have continued and financial stringency tightened, the need for reliable costs analysis based on more accurate relevant costs data has become even more urgent. This thesis is an attempt in this direction. It is based on a representative random sample of 48 academic secondary schools out of 203 public schools in northern Sudan, in the academic year 1988/89. It analyses the unit expenditure of secondary schools and its constituents, identifies the factors that influence their variations among educational institutions and between regions, and examines the utilization of resources at the school level. The per pupil costs, components and cost indicators are investigated by size, location, type and kind of school as well as the teacher profile of academic qualifications, types of training and levels of experience; per boarder costs are discussed separately. Pearson correlation has been employed to estimate the type and strength of the relationships between the unit costs and their constituents on one hand and the cost indicators on the other. The sample data are tested for economies of size and the results of the final public examination, the Sudan School Certificate, are related to the size of school and to per pupil expenditure and other cost indicators using linear and multiple regression, analysis.
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