Portal de Periódicos da CAPES

A Machine Learning Approach for Prediction of Students’ Admissibility for Post-Secondary Education using Artificial Neural Network

2022; Volume: 184; Issue: 27 Linguagem: Inglês

10.5120/ijca2022922340

0975-8887

Anietie Ekong, Abasiama Silas, Saviour Inyang,

Online Learning and Analytics

Student admission's process is a method of selecting qualified candidates for admission.Challenges such as facility constraints and insufficient ability to meet the continuously rising needs of post-secondary education.There is still an absorption capacity problem in some parts of the world as the growing number of students applying for admission for postsecondary education far surpasses the rate of expansion and this makes the selection process to be a daunting tasks.In this study, Artificial Neural network (ANN) was adopted for the determination of admissibility of candidates for postsecondary education based on (O'level Results, CGPA (Cumulative Grade Point Average), Departmental Rank (DPR) etc. Results indicated effective prediction based the performance analysis using the Confusion Matrix and AUC -ROC and gave a 99% accuracy on the dataset.