Predicting Students Success in Blended Learning—Evaluating Different Interactions Inside Learning Management Systems

Algorithms and programming are some of the most challenging topics faced by students during undergraduate programs. Dropout and failure rates in courses involving such topics are usually high, which has raised attention towards the development of strategies to attenuate this situation. Machine learn...

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Veröffentlicht in:	Applied sciences Jg. 9; H. 24; S. 5523
Hauptverfasser:	Buschetto Macarini, Luiz Antonio, Cechinel, Cristian, Batista Machado, Matheus Francisco, Faria Culmant Ramos, Vinicius, Munoz, Roberto
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.12.2019
Schlagworte:	Algorithms At risk students Colleges & universities Computer programming Computer science Core curriculum Data mining Datasets Distance learning Learning management systems Success Teaching
ISSN:	2076-3417, 2076-3417
Online-Zugang:	Volltext
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