SCHOOL-BASED MANAGEMENT COMMITTEE RESOURCE MOBILIZATION, AVAILABILITY AND UTILIZATION ON PUBLIC PRIMARY SCHOOL PERFORMANCE IN EKITI STATE NIGERIA: ARTIFICIAL INTELLIGENCE NEURAL NETWORK APPROACH
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Keywords

School-Based Management Committee
resource mobilization
resource availability
resource utilization
school performance

How to Cite

Oresajo, N. O. (2022). SCHOOL-BASED MANAGEMENT COMMITTEE RESOURCE MOBILIZATION, AVAILABILITY AND UTILIZATION ON PUBLIC PRIMARY SCHOOL PERFORMANCE IN EKITI STATE NIGERIA: ARTIFICIAL INTELLIGENCE NEURAL NETWORK APPROACH. African Journal of Educational Management, 22(2), 35-59. Retrieved from http://journals.ui.edu.ng/index.php/ajem/article/view/716

Abstract

School performance involves with the efficiency and effectiveness in the service delivery that a school as an organisation rendered to her potential client satisfactorily. This is often created an issue concerned to the stakeholders such as government, parents and the employer of labour especially the public primary schools’ performance. For school performance to be improved upon, relevant resources must be made available at the disposal of the school community that is the teachers and pupil’s use. In the view of this, this study examined School-Based Management Committee resource mobilization, availability and utilization on public primary schools’ performance in Ekiti State: Artificial Neural Network (ANN) approach. One research question was raised and two research instruments were designed to elicit relevant information from the study participants with the titled “Observation Checklist: Resource Mobilization, Availability and Utilization” with the reliability co-efficient of 0.86 Cronbach Alpha and “School Performance Questionnaire” (SPQ) with the reliability coefficient of 0.89 Cronbach Alpha. The study adopted multi-stage sampling technique which embraces purposive sampling methods, simple random sampling methods and stratified sampling methods. Population sampled for the study include: 90 headteachers, 90 SBMC Chairmen and 1020 teachers in 12 Local Government Education Authorities (LGEAs) in Ekiti State Universal Basic Education Board. Data generated from the field for the study was analyzed using the Artificial Neural Network (ANN) which is a statistical package that is more reliable and that work like human brain at 0.05 level of significance. The results findings indicated R2 of 0.85; 0.68; 0.91; 0.84; 0.75; and 0.72 based on the key performance indicators to the study, and arising from the result findings, it is therefore recommended among others that: government at the various levels of governance should step up the awareness campaign of SBMC by sensitizing the citizenry on the significant of the organization in the school system. The SBMC members should be trained and re-trained from time to time on their responsibilities in the school administration in order to avert conflict of interest between them and the PTA executives operating in schools as partners in progress.

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