Application of Machine Learning Models for Predicting Students' Performance in Mathematics: A K-Fold Approach-Reference-Cited by-同舟云学术

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Application of Machine Learning Models for Predicting Students' Performance in Mathematics: A K-Fold Approach

Published:2024-04-02 Issue: Volume:2 Page:1-9
ISSN:
Container-title:2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG)
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Author:

Ale Felix¹,Ikpaya Ikpaya D.²,Danyan Ilesanmi³,Opateye Goodness O.⁴,Onwodi Gregory⁴,Agboola Olufemi O.¹

Affiliation:

1. National Space Research & Development Agency,Department of Engineering & Space Systems,Abuja,Nigeria

2. National Space Research & Development Agency,Ground Station & Mission Control,Abuja,Nigeria

3. Achievers University,Department of Mechanical & Mechatronics Engineering,Owo,Nigeria

4. National Open University of Nigeria,Department of Computer Science,Abuja,Nigeria

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10629651/10629654/10630249.pdf?arnumber=10630249

Reference52 articles.

1. Influence of extrinsic and intrinsic motivation on pupils academic performance in mathematics;Adamma,2018

2. Applying machine learning approach to predict students’ performance in higher educational institutions

3. Predicting Students' Academic Performance Using Multiple Linear Regression and Principal Component Analysis

4. MOOC dropout prediction using machine learning techniques: Review and research challenges

5. Examination of causes and Effects of Anxiety on Secondary School Students’ Poor Academic Performance in Mathematics

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