Influence of parents' on enrollment socioeconomic and retention status of children in ecde centers in Lambwe division, Mbita district
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Date
2014-07-24
Authors
Oluoch, Okumu Kennedy
Journal Title
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Abstract
According to UNESCO (2008) pre-primary learners who have been enrolled in pre
primary schools tend to perform better in school than those who have not. Preschool is
important because it helps to build a strong foundation for lifelong learning and to ensure
equitable access to later learning opportunities. Statistics show low preschool enrollment
in Kenya and particularly in Lambwe division where only 1928 children (50.14%) of the
children aged 3-6 years are attending pre-school. It is because of this that the study will
be undertaken to find out the possible causes of low enrollment and retention of early
childhood education learners in Lambwe division Mbita District, Kenya. Specific
Objectives of the study are to: determine the influence of parental economic status on
enrollment and retention of children in ECDE centres, find out the extent to which
parent's level of education influence enrollment and retention of children in ECDE
centres, establish how parents occupation influence enrollment and retention of children
in ECDE centres and describe the influence of parents income on enrolment and retention
of chi Idren in ECDE centres in Lambwe division, Mbita district, Kenya. The study will
adopt the human ecology theory by Bronfenbrenner, (1979). His ecological systems
theory holds that development reflects the influence of several environmental systems,
and it identifies five enviromnental systems that an individual interacts with. That is the
Microsystem,
Mesosystem,
Exosystem,
Macrosystem
and Chronosystem.
The
instruments that will be used for data collection are questionnaires for 196 parents. On
the other hand interviews schedules will be used for data collection from quality
assurance officers. The study will employ correlation research design. Data presentation
will involve use of tables, frequency counts and charts. Data will be analyzed using the
Pearson Product Moment Correlation statistical tool with the aim of establishing the
relationship between the variables. This will form the basis of the detailed analysis.
Descriptive statistic will be used to summarize the data and meaningfully describe the
distribution of scores. Statistical analysis will be done using statistical package for social
sciences (SPSS) version 11.0. Results and discussion on specific objectives, summary,
conclusion and recommendation will be made.