NON-SCHOOL FACTORS ASSOCIATED WITH SCHOOL DROPOUTS IN UGANDA
DOI:
https://doi.org/10.20319/pijss.2018.41.477493Keywords:
School Dropout, Uganda, Probit Regression, EducationAbstract
Currently numerous studies have concerned themselves with reducing school dropout rates premised on school environment. This has resulted into limited impact of interventions fronted to reduce the high school dropout rates. If schools are to register high retention rates commensurate to the high enrollment levels, there is need for studies and interventions to look beyond school related factors which don’t influence school attendance in isolation but operate alongside other factors such as the individual characteristics of the children and their parents especially the household head, household structure and composition as well as the community factors. Therefore, this study aimed at determining non-school factors associated with school dropouts in Uganda. Assessment was done using the probit regression model and secondary data from Uwezo Uganda National Learning Assessment 2014 survey. Children aged 6-16 were assessed based on their household setting and supplementary data obtained through related surveys of their households, local communities and selected local schools where majority of the children in the community were enrolled. The likelihood of a child dropping out of school increased with the child’s age and reduced with; increase in years of preschool attendance and household heads education level. Furthermore, school dropouts were more likely among the disabled children and children with no biological parents in the household. The study recommended focusing on pupil retention, parent sensitization regarding the merits of formal education and the need to promote mandatory pre-school education where children’s’ reading, writing and numeracy can be nurtured at an early age. There is need to explore further the effect of other non-school factors that could influence school dropout directly or indirectly or interactively with school related factors including peer social capital, student loan scheme programmes, government education policies to curb school absenteeism and commitment to their implementation, migration among others
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