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A Soft Computing Model for Predicting Students’ Academic Performance in Tertiary Institutions
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 176 - Number 23 |
| Year of Publication: 2020 |
| Authors: Olutayo Boyinbode, Oluwaseun Ayankunle, Olumide Obe |
10.5120/ijca2020920267
|
Olutayo Boyinbode, Oluwaseun Ayankunle, Olumide Obe . A Soft Computing Model for Predicting Students’ Academic Performance in Tertiary Institutions. International Journal of Computer Applications. 176, 23 ( May 2020), 49-54. DOI=10.5120/ijca2020920267
Abstract
Educational Institutions are striving to foster the prediction of student performance into their educational sector for better students' support, this is achieved by discovering students with lower performance and making additional efforts to improve their performance. Assessing and predicting students’ performance enhance academic performance and is a catalyst to delivering high quality education. Soft computing is a promising technique used in solving prediction problems to enhance academic performance in educational sectors. This paper implemented a soft computing model (Adaptive Neuro Fuzzy Model using Levenberg–Marquardt algorithm) for predicting Students’ Academic Performance in Tertiary Institutions. The system was implemented using MATLAB 2017a. The developed model has an accuracy of 99.33%, which is the highest, when compared with some previous works.
References
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