Student Performance Prediction Model based on Supervised Machine Learning Algorithms

Higher education institutions aim to forecast student success which is an important research subject. Forecasting student success can enable teachers to prevent students from dropping out before final examinations, identify those who need additional help and boost institution ranking and prestige. M...

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Veröffentlicht in:	IOP conference series. Materials Science and Engineering Jg. 928; H. 3; S. 32019 - 32036
Hauptverfasser:	Salah Hashim, Ali, Akeel Awadh, Wid, Khalaf Hamoud, Alaa
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Bristol IOP Publishing 01.11.2020
Schlagworte:	Algorithms Colleges & universities Data mining Datasets Decision Tree Decision trees Educational Data Mining Higher education institutions K-Nearest Neighbour Logistic Regression Machine learning Mathematical models Multi-layer Perceptron Naive Bayes Neural Network Neural networks Optimization Performance prediction Prediction models Students Supervised Machine Learning Support vector machines
ISSN:	1757-8981, 1757-899X
Online-Zugang:	Volltext
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