Machine Learning Algorithm to Predict Student’s Performance: A Systematic Literature Review

One of the ultimate goals of the learning process is the success of student learning. Using data and students' achievement with machine learning to predict the success of student learning will be a crucial contribution to everyone involved in determining appropriate strategies to help students...

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Autores principales:	Lidia Sandra, Ford Lumbangaol, Tokuro Matsuo
Formato:	article
Lenguaje:	EN
Publicado:	UIKTEN 2021
Materias:	machine learning algorithm systematic literature review student’s performance Education L Technology T
Acceso en línea:	https://doaj.org/article/85bfd239507740dbac3558b268964f43
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id	oai:doaj.org-article:85bfd239507740dbac3558b268964f43
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spelling	oai:doaj.org-article:85bfd239507740dbac3558b268964f432021-12-01T22:33:42ZMachine Learning Algorithm to Predict Student’s Performance: A Systematic Literature Review10.18421/TEM104-562217-83092217-8333https://doaj.org/article/85bfd239507740dbac3558b268964f432021-11-01T00:00:00Zhttps://www.temjournal.com/content/104/TEMJournalNovember2021_1919_1927.pdfhttps://doaj.org/toc/2217-8309https://doaj.org/toc/2217-8333One of the ultimate goals of the learning process is the success of student learning. Using data and students' achievement with machine learning to predict the success of student learning will be a crucial contribution to everyone involved in determining appropriate strategies to help students perform. The selected 11 research articles were chosen using the inclusion criteria from 2753 articles from the IEEE Access and Science Direct database that was dated within 2019-2021 and 285 articles that were research articles. This study found that the classification machine learning algorithm was most often used in predicting the success of students' learning. Four algorithms that were used most often to predict the success of students' learning are ANN, Naïve Bayes, Logistic Regression, SVM and Decision Tree. Meanwhile, the data used in these research articles predominantly classified students' success in learning into two or three categories which are pass/fail; or fail/pass/excellent.Lidia SandraFord LumbangaolTokuro MatsuoUIKTENarticlemachine learning algorithmsystematic literature reviewstudent’s performanceEducationLTechnologyTENTEM Journal, Vol 10, Iss 4, Pp 1919-1927 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	machine learning algorithm systematic literature review student’s performance Education L Technology T
spellingShingle	machine learning algorithm systematic literature review student’s performance Education L Technology T Lidia Sandra Ford Lumbangaol Tokuro Matsuo Machine Learning Algorithm to Predict Student’s Performance: A Systematic Literature Review
description	One of the ultimate goals of the learning process is the success of student learning. Using data and students' achievement with machine learning to predict the success of student learning will be a crucial contribution to everyone involved in determining appropriate strategies to help students perform. The selected 11 research articles were chosen using the inclusion criteria from 2753 articles from the IEEE Access and Science Direct database that was dated within 2019-2021 and 285 articles that were research articles. This study found that the classification machine learning algorithm was most often used in predicting the success of students' learning. Four algorithms that were used most often to predict the success of students' learning are ANN, Naïve Bayes, Logistic Regression, SVM and Decision Tree. Meanwhile, the data used in these research articles predominantly classified students' success in learning into two or three categories which are pass/fail; or fail/pass/excellent.
format	article
author	Lidia Sandra Ford Lumbangaol Tokuro Matsuo
author_facet	Lidia Sandra Ford Lumbangaol Tokuro Matsuo
author_sort	Lidia Sandra
title	Machine Learning Algorithm to Predict Student’s Performance: A Systematic Literature Review
title_short	Machine Learning Algorithm to Predict Student’s Performance: A Systematic Literature Review
title_full	Machine Learning Algorithm to Predict Student’s Performance: A Systematic Literature Review
title_fullStr	Machine Learning Algorithm to Predict Student’s Performance: A Systematic Literature Review
title_full_unstemmed	Machine Learning Algorithm to Predict Student’s Performance: A Systematic Literature Review
title_sort	machine learning algorithm to predict student’s performance: a systematic literature review
publisher	UIKTEN
publishDate	2021
url	https://doaj.org/article/85bfd239507740dbac3558b268964f43
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Machine Learning Algorithm to Predict Student’s Performance: A Systematic Literature Review

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