Assessing The Capacity Of The District Education Office Using The Multinomial Logistic Regression Model

Abstract

The District Education Office plays a pivotal role in the implementation of education services in Kenya, and in effect, in the attainment of Education for All (EFA) and United Nations 2nd Millennium Development Goal. It is thus, paramount, that the office has requisite capacity to deliver the required services at this level. Responses m capacity assessment are often measured as ratings or rankings. Usual analysis of vanance and linear based analysis are not appropriate for these data. Alternative methods based on the generalized linear models should therefore be applied for analysis of this kind of data. This Project proposes an elaborate and articulate means of assessing capacities of the District Education Office. In this project, Multinomial Logistic Regression has been used to assess the factors-contributing to capacity. The response variable is the Capacity to implement KESSP. Eight (8) variables were selected as explanatory variables. These variables represent the six thematic areas used in capacity assessment namely: Organizational home, Leadership, Staffing, Funding, Materials and Work practices.

Model fitting results shows that inasmuch as there is fair Capacity to implement KESSP at the District Education Office level. Factors that are evidently contributing to capacity are on Organizational home and Capacity by Staff. The capacity by staff entails the presence of the requisite number of staff and the skills and qualifications the staff possess.