Development of a Fuzzy Logic-Based Decision Support System for Secondary School Admissions: A Case Study of Government Secondary School, Minna (Chanchaga LGA, Niger State)
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Background of the Study
The process of secondary school admissions is often complicated due to the many variables that must be considered, such as student grades, extracurricular activities, and behavioral assessments. Traditional admission methods can be time-consuming and may not provide an optimal decision-making framework. Fuzzy logic, a mathematical model that deals with reasoning that is approximate rather than fixed and exact, can be an effective decision support tool in such cases (Jang & Sun, 2024). Fuzzy logic-based systems allow for better handling of uncertain, imprecise, or vague information. This study will focus on the development of a fuzzy logic-based decision support system to streamline the secondary school admission process at Government Secondary School, Minna, located in Chanchaga LGA, Niger State. The system aims to improve the fairness and efficiency of the admission process by taking into account multiple criteria that are often difficult to quantify.
Statement of the Problem
Government Secondary School, Minna, currently uses a traditional admission process that relies heavily on fixed numerical thresholds, which may not fully reflect the holistic qualifications of applicants. This method can lead to inefficiencies, such as overlooking deserving candidates or admitting students who do not meet the school's broader educational goals. The introduction of a fuzzy logic-based decision support system could help accommodate a wider range of factors and make the admission process more comprehensive and fair.
Objectives of the Study
- To design and develop a fuzzy logic-based decision support system for secondary school admissions at Government Secondary School, Minna.
- To assess the effectiveness of the fuzzy logic system in improving the fairness and efficiency of the school’s admission process.
- To compare the performance of the fuzzy logic-based system with traditional admission decision-making methods.
Research Questions
- How can fuzzy logic-based systems be used to improve the secondary school admission process at Government Secondary School, Minna?
- What impact does the fuzzy logic-based system have on the fairness and efficiency of the admission process?
- How does the performance of the fuzzy logic-based system compare to traditional admission methods in terms of decision accuracy and speed?
Research Hypotheses
- The fuzzy logic-based system will lead to a more efficient and fair secondary school admission process compared to traditional methods.
- The fuzzy logic-based system will better handle imprecise and subjective information, leading to more accurate admission decisions.
- The fuzzy logic-based decision support system will outperform the traditional method in terms of processing time and decision quality.
Significance of the Study
This study will provide valuable insights into the application of fuzzy logic in decision-making processes, particularly in educational settings. The findings will help Government Secondary School, Minna, adopt a more transparent, efficient, and fair approach to student admissions, benefiting both the school and the applicants. Furthermore, it will contribute to the broader field of fuzzy logic applications in education.
Scope and Limitations of the Study
The study will focus on the development and implementation of a fuzzy logic-based decision support system for secondary school admissions at Government Secondary School, Minna, within Chanchaga LGA, Niger State. It will not address broader issues in educational management beyond admissions.
Definitions of Terms
Fuzzy Logic: A mathematical system that allows for reasoning with uncertain or imprecise information.
Decision Support System: A computerized system designed to help decision-makers solve complex problems by analyzing large amounts of data.
Admission Process: The method by which students are selected for entry into a secondary school based on predefined criteria.
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