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PROJECT TOPIC: DETERMINE STUDENT’S ACADEMICS PERFORMANCE USING ARTIFICIAL NEURAL NETWORK ALGORITHM
Department: Computer Science
FORMART: MS WORD
PAGES: 90 pages, abstract, chapter 1-5 , APENDIX A source code and APENDIX B output, well reserached and supervised
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1.1 BACKGROUND TO THE STUDY
Predicting student academic performance has long been an important research work. Among the issues of education system, questions concerning admissions into academic institutions (secondary and tertiary level) remain important (Ting, 2008). The main objective of the admission system is to determine the candidates who would likely perform well after being accepted into the school. The quality of admitted students has a great influence on the level of academic performance, research and training within the institution. The failure to perform an accurate admission decision may result in an unsuitable student being admitted to the program. Hence, admission officers want to know more about the academic potential of each student. Accurate predictions help admission officers to distinguish between suitable and unsuitable candidates for an academic program, and identify candidates who would likely do well in the school (Ayan and Garcia, 2013). The results obtained from the prediction of academic performance may be used for classifying students, which enables educational managers to offer them additional support, such as customized assistance and tutoring resources.