Zero-augmented models for exploring the factors affecting the pass rate of 2016 grade 10 learners in Khomas region, Namibia

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Rapikama Mumbuu
Lilian Pazvakawambwa
Opeoluwa Oyedele

Abstract

The poor performance of grade 10 learners has been a big concern over the last few years and in the effort to understand this phenomenon there has been efforts to present models that explain it. This study aimed at exploring the factors which influence Khomas Region grade 10 learners' pass rate using Generalized Linear Models (GLMs). The data used for this study was obtained from the Directorate of National Examination and Assessment for the year 2016, with permission from the Permanent Secretary of the Ministry of Education (DNEA). With the presence of excess zeros in the study data, six GLMs were explored (Poisson, Negative Binomial, Hurdle Poisson, Hurdle Negative Binomial, Zero Inflated Poisson and Zero- Inflated Negative Binomial) to assess their goodness of fit on modelling the zero-inflated DNEA count data. Afterwards, the better performing GLM was used in achieving the study aim. The Zero- Inflated Negative Binomial performed better based on its lowest Akaike Information Criterion (AIC) values among the six fitted GLMs. Results from the fitted Zero- Inflated Negative Binomial model revealed that the age
of the learner, school location and the type of school (private/state) had significant differential in the pass rate of grade 10 learners, with p-values < 0.05 in the Zero- Inflated Negative Binomial model. Thus, it is recommended that for densely populated areas, emphasis should be put on building more schools in these areas so that classrooms are not overcrowded per subject. In
addition, overaged learners should also be given extra assistance such as extra classes and extra motivation.

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How to Cite
Mumbuu, R., Pazvakawambwa, L. ., & Oyedele, O. (2022). Zero-augmented models for exploring the factors affecting the pass rate of 2016 grade 10 learners in Khomas region, Namibia. Namibian Journal for Research, Science and Technology, 4(1), 13-20. https://doi.org/10.54421/njrst.v4i1.81
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