Technical efficiency of the state-sponsored general education

Abstract

Education is one major trajectory that the government of Sri Lanka, as a welfare state, funds with the enactment of the Free Education Act. Technical Efficiency (TE) is one main assessment applied in different organizations, especially in the education sector, to estimate the output gained compared to the input resources. This study tried to analyze the TE of state sponsored general education using the Stochastic Production Frontier model with the inefficiency effects developed by Battese and Coeli in 1995. According to this model, the TE is calculated from the given input variables. And non-input variables are used to calculate the inefficiency effect. TE is defined as the ratio between the actual output and the maximum possible output. Front 4.1 software is unique for the analysis of data with inefficiency impacts. The methodology applied was the convergence mixed methodology. Although the study population included all the grade 11 students and the grade 13 science stream students in the island, the sample included 850 male and female students chosen according to the Systematic Random Sampling method from Type 1AB fully government-owned schools spread throughout the Gampaha District of the Western Province, and the students of grade 11 and grade 13 along with their parents, relevant teachers, and the principals were picked as the primary data sources. The data collection was done using a questionnaire developed after a pilot study. The study concluded that the mean TE of state-sponsored general education was between 70% and 80% and could have room for further development. While the school resources, principals' administration, teachers' contribution, students' keenness for learning, and parents' support on their childrens' education were presented as the proven factors that influence the TE; least parents' support, weak concentration level of students during lessons, inability to cover the expected syllabi, and lack of revision coverage were highlighted as the recognized factors that influence the inefficiency.