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Academic Performance Modelling with Machine Learning Based on Cognitive and Non-Cognitive Features Cover

Academic Performance Modelling with Machine Learning Based on Cognitive and Non-Cognitive Features

Applied Computer Systems
Volume 26 (2021): Issue 2 (December 2021)
By: Bridgitte Owusu-Boadu,  Isaac Kofi Nti,  Owusu Nyarko-Boateng,  Justice Aning and  Victoria Boafo  
Open Access
|Dec 2021
DOI: https://doi.org/10.2478/acss-2021-0015 | Journal eISSN: 2255-8691 | Journal ISSN: 2255-8683
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Language: English
Page range: 122 - 131
Published on: Dec 30, 2021
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
Academic performance,
AdaBoost,
artificial neural network,
decision tree,
educational data mining,
k-nearest neighbour,
logistic regression,
machine learning,
naïve Bayes,
random forest,
support vector machine
Related subjects:
Computer sciences,
Artificial intelligence,
Information technology,
Project management,
Software development

© 2021 Bridgitte Owusu-Boadu, Isaac Kofi Nti, Owusu Nyarko-Boateng, Justice Aning, Victoria Boafo, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.

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