Date of Award

2021

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Educational Leadership

First Advisor

Bernice R. Garnett

Abstract

In 2019, the United Nations Children’s Fund (UNICEF) estimated the global number of children under the age of 5 without birth registrations at 166 million, with the largest share being present in Sub-Saharan Africa. As the author witnessed firsthand while working in Cameroon, the lack of birth registration documentation (i.e. birth certificates) precluded students from progressing from primary to secondary education. Struck by this example of social exclusion, the purpose of this study was to examine the extent to which birth registration acted as a barrier to educational access in primary and secondary education systems elsewhere across Sub-Saharan Africa. An interdisciplinary conceptual framework revealed a gap in academic literature with only a few studies having explored the relationship between birth registration and access to education in a regional context. This study filled such gap by advancing an innovative explanatory spatial mixed methods research design to analyze secondary data from UNICEF and the United Nations Educational, Scientific, and Cultural Organization (UNESCO). This unique design consisted of an initial quantitative multiple regression analysis followed by a spatial autocorrelation analysis, using geographic information systems (GIS), to explain the geography of the initial results.

Results from this pragmatic research approach, outlined in a journal-article dissertation format, were intended to be made useful for researchers and policymakers alike. Noteworthy for the former audience, the quantitative strand found that while birth registration was not a significant predictor of access to education at any level of schooling, there were significant effects of gross domestic product (GDP) per capita and rurality on educational access (Article #1). For the latter readers, choropleth maps of birth registration revealed some areas of neighboring countries with similar levels of low registration despite the absence of statistical clustering. However, access to education demonstrated statistically significant cluster patterns (p<0.05) at the primary and lower-secondary levels, offering organizations like UNICEF and UNESCO noteworthy findings that could better inform policy interventions (Article #2). Finally, the author integrated both data strands using a multivariate cluster analysis in the ArcGIS platform, providing a compelling argument for the use of spatial mixed methods in educational policy research (Article #3).

Language

en

Number of Pages

208 p.

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