Academic performance problems: A predictive data mining-based model

Often times, universities are not able to deal with the variety of factors that may affect the academic performance of students. This kind of situation generates the need for tools that establish academic performance patterns, setting profiles as a basis to detect potential cases of underachieving s...

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Detalles Bibliográficos
Autores principales:	La Red Martínez, David Luis, Giovannini, Mirtha, Báez, María Eugenia, Torre, Juliana, Yaccuzzi, Nelson
Formato:	Artículo publishedVersion
Lenguaje:	Inglés Inglés
Publicado:	2020
Materias:	academic performance educational data mining predictive data mining higher education course assessment student assessment
Acceso en línea:	http://hdl.handle.net/20.500.12272/4437
Aporte de:	RIA - Repositorio Institucional Abierto (UTN) de Universidad Tecnológica Nacional

id	I68-R174-20.500.12272-4437
record_format	dspace
institution	Universidad Tecnológica Nacional
institution_str	I-68
repository_str	R-174
collection	RIA - Repositorio Institucional Abierto (UTN)
language	Inglés Inglés
topic	academic performance educational data mining predictive data mining higher education course assessment student assessment
spellingShingle	academic performance educational data mining predictive data mining higher education course assessment student assessment La Red Martínez, David Luis Giovannini, Mirtha Báez, María Eugenia Torre, Juliana Yaccuzzi, Nelson Academic performance problems: A predictive data mining-based model
topic_facet	academic performance educational data mining predictive data mining higher education course assessment student assessment
description	Often times, universities are not able to deal with the variety of factors that may affect the academic performance of students. This kind of situation generates the need for tools that establish academic performance patterns, setting profiles as a basis to detect potential cases of underachieving students who need support in their academic activities. This paper proposes the use of Data Warehousing and Data Mining techniques on performance, social, economic, demographic and cultural data from students who took “Algorithms and Data Structures”, which is a subject in the Information Systems Engineering curricula at UTN-FRRe (Resistencia, Chaco, Argentina) in an attempt to establish generic academic performance profiles. From the descriptive analysis obtained during the 2013 to 2015 period from the subject aforementioned, a predictive model was used. It establishes the possibility of students' academic failure, taking into account the factors earlier mentioned.
format	Artículo publishedVersion
author	La Red Martínez, David Luis Giovannini, Mirtha Báez, María Eugenia Torre, Juliana Yaccuzzi, Nelson
author_facet	La Red Martínez, David Luis Giovannini, Mirtha Báez, María Eugenia Torre, Juliana Yaccuzzi, Nelson
author_sort	La Red Martínez, David Luis
title	Academic performance problems: A predictive data mining-based model
title_short	Academic performance problems: A predictive data mining-based model
title_full	Academic performance problems: A predictive data mining-based model
title_fullStr	Academic performance problems: A predictive data mining-based model
title_full_unstemmed	Academic performance problems: A predictive data mining-based model
title_sort	academic performance problems: a predictive data mining-based model
publishDate	2020
url	http://hdl.handle.net/20.500.12272/4437
work_keys_str_mv	AT laredmartinezdavidluis academicperformanceproblemsapredictivedataminingbasedmodel AT giovanninimirtha academicperformanceproblemsapredictivedataminingbasedmodel AT baezmariaeugenia academicperformanceproblemsapredictivedataminingbasedmodel AT torrejuliana academicperformanceproblemsapredictivedataminingbasedmodel AT yaccuzzinelson academicperformanceproblemsapredictivedataminingbasedmodel
bdutipo_str	Repositorios
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Academic performance problems: A predictive data mining-based model

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