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

Owusu-Boadu, Bridgitte; Nti, Isaac Kofi; Nyarko-Boateng, Owusu; Aning, Justice; Boafo, Victoria

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

Bridgitte Owusu-Boadu

Owusu-Boadu, Bridgitte

,

Isaac Kofi Nti

Nti, Isaac Kofi

,

Owusu Nyarko-Boateng

Nyarko-Boateng, Owusu

,

e

30 dic 2021

Applied Computer Systems

Volume 26 (2021): Numero 2 (Dicembre 2021)

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Pubblicato online: 30 dic 2021

Pagine: 122 - 131

DOI: https://doi.org/10.2478/acss-2021-0015

Parole chiave
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

© 2021 Bridgitte Owusu-Boadu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Owusu-Boadu, Bridgitte

Brivink Consult & TechnologySunyani, Ghana

Nti, Isaac Kofi

Department of Computer Science and Informatics, University of Energy and Natural ResourcesSunyani, Ghana

Nyarko-Boateng, Owusu

Department of Computer Science and Informatics, University of Energy and Natural ResourcesSunyani, Ghana

Aning, Justice

Department of Computer Science, Sunyani Technical UniversitySunyani, Ghana

Boafo, Victoria

Department of Computer Science & ICT, Mampong Technical College of EducationMampong, Ghana

Lingua:: Inglese

Frequenza di pubblicazione:: 1 volte all'anno
Argomenti della rivista:: Informatica, Intelligenza artificiale, Tecnologia informatica, Project Management, Software Development

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

Bridgitte Owusu-Boadu

Isaac Kofi Nti

Owusu Nyarko-Boateng

Justice Aning

Victoria Boafo

Pubblicato online: 30 dic 2021

Pagine: 122 - 131

DOI: https://doi.org/10.2478/acss-2021-0015

Parole chiaveAcademic performance, AdaBoost, artificial neural network, decision tree, educational data mining, k-nearest neighbour, logistic regression, machine learning, naïve Bayes, random forest, support vector machine

© 2021 Bridgitte Owusu-Boadu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Parole chiave
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