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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Evaluation of the academic performance of students’ using artificial neural network: Case study of Faculty of Engineering, Nigeria Maritime University, Okerenkoko, Delta State. |
| Authors Name: | Iwekumo Stevyn Akosubo , Bolou, D. Bolou , Kabiru Ahmed , Olateju, O. Abideen |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_181899
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| Published Paper Id: | IJNRD2207003 |
| Published In: | Volume 7 Issue 7, July-2022 |
| DOI: | |
| Abstract: | The substantial development in electronic data for university students’ academic performance in either supervised or unsupervised learning has resulted in some meaningful information extracted from large volumes of data using diverse data mining techniques. Due to the increase in the rate of poor outcomes, the need to design a system that helps to reduce the menace of students’ poor academic performance or having to drop out of school was analysed. The purpose of this study was to develop a system to predict student performance with an Artificial Neutral Network approach to the predictive classification of students in the full range of academic performance (GPA) so as to determine which is more efficient in and in what case one should be preferred over the other, as well as to identify and understand the importance of the variables for each level (low, middle and high) of expected GPA. Artificial Neural networks often need a greater collection of observations to achieve enough predictive ability. The ANN is a suitable model for the prediction of students' academic performance in their final year under conditions of a very complex and great amount of data, in which a large number of variables interact in various complexes. The results attained during this study will allow the identification of the precise influence of every input set of variables on different levels of educational performance (high and low performance), on one hand, and customary processes across all students, on the opposite hand. Additionally, we identified which key factors had an important influence on overall students’ performance. Data were collected from the scholars of the school of Engineering, Nigeria Maritime University, Okerenkoko, Delta State. The study achieved an accuracy of over 92.3 percent, showing Artificial Neural Network's potential effectiveness as a predictive tool for accessing students’ academic performance. |
| Keywords: | Student performance, University Education, Data mining, Artificial Neural Network |
| Cite Article: | "Evaluation of the academic performance of students’ using artificial neural network: Case study of Faculty of Engineering, Nigeria Maritime University, Okerenkoko, Delta State.", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 7, page no.18-25, July-2022, Available :http://www.ijnrd.org/papers/IJNRD2207003.pdf |
| Downloads: | 000118759 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
| Publication Details: |
Published Paper ID:IJNRD2207003 Registration ID: 181899 Published In: Volume 7 Issue 7, July-2022 DOI (Digital Object Identifier): Page No: 18-25 Country: Okerenkoko, Delta, Nigeria Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2207003 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2207003 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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