Abstract

The Springtime Development Foundation (SDF), being a non-profit and non-governmental organization has spent over 10 Billion Naira in sponsoring thousands of students who cannot afford the payment of school fees into higher institutions all over Nigeria. However, this quantum of money invested is not commensurable to the performance received as feedback. From past studies, it is evident that some of the challenges which may have caused this include the method of students' selection. This research then proposes to design a model that will predict and classify students’ performance in higher institution putting some factors into consideration. O’level results, Joint Admission and Matriculation Board (JAMB) exam results and Age of applicant were the factors considered in building this model. A Scikit Learn Neural Network package and a Multi-Layer Perception (MLP) classifier was chosen for the algorithm used for the implementation, while Fuzzy Logic was used as the concept From the findings, it was observed that for multifactor/variable system, the traditional binary logic may not be the best logical approach; rather the use of fuzzy logic reduces the complexity and enhances the performance. From the development of the model, it was realized that the complexity of the binary logic will be in order power of (mn ) or (mna), whereas, using the concept of fuzzy logic, the complexity has been reduced to ma T where ‘a’ is a constant in both scenario. The output was displayed from the web browser (https://www.sdfscreening.com.ng) thereby hiding all the logic behind the work to the layman user. The output of this model will serve as a determinant for awarding scholarship to the applicants. From the analysis of the model, it is evident that this model when adopted will be faster than the traditional method since the conventional way of selecting scholarship awardees has not been yielding a positive result in proportion to the students’ academic performances in the university, which has resulted to waste of money, time and resources, hence, limit other people chances.