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Data science for analyzing and improving educational processes

In this full review paper, the recent emerging trends in Educational Data Science have been reviewed and explored to address the recent topics and contributions in the era of Smart Education. This includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art...

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Detalles Bibliográficos
Autores principales: Aljawarneh, Shadi, Lara, Juan A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8553589/
https://www.ncbi.nlm.nih.gov/pubmed/34729004
http://dx.doi.org/10.1007/s12528-021-09299-7
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author Aljawarneh, Shadi
Lara, Juan A.
author_facet Aljawarneh, Shadi
Lara, Juan A.
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description In this full review paper, the recent emerging trends in Educational Data Science have been reviewed and explored to address the recent topics and contributions in the era of Smart Education. This includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art, frameworks and techniques research projects in the area of Data Science applied to Education, using different approaches such as Information Fusion, Soft Computing, Machine Learning, and Internet of Things, among others. Based on this systematic review, we have put some recommendations and suggestions for researchers, practitioners and scholars to improve their research quality in this area.
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spelling pubmed-85535892021-10-29 Data science for analyzing and improving educational processes Aljawarneh, Shadi Lara, Juan A. J Comput High Educ Article In this full review paper, the recent emerging trends in Educational Data Science have been reviewed and explored to address the recent topics and contributions in the era of Smart Education. This includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art, frameworks and techniques research projects in the area of Data Science applied to Education, using different approaches such as Information Fusion, Soft Computing, Machine Learning, and Internet of Things, among others. Based on this systematic review, we have put some recommendations and suggestions for researchers, practitioners and scholars to improve their research quality in this area. Springer US 2021-10-29 2021 /pmc/articles/PMC8553589/ /pubmed/34729004 http://dx.doi.org/10.1007/s12528-021-09299-7 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Aljawarneh, Shadi
Lara, Juan A.
Data science for analyzing and improving educational processes
title Data science for analyzing and improving educational processes
title_full Data science for analyzing and improving educational processes
title_fullStr Data science for analyzing and improving educational processes
title_full_unstemmed Data science for analyzing and improving educational processes
title_short Data science for analyzing and improving educational processes
title_sort data science for analyzing and improving educational processes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8553589/
https://www.ncbi.nlm.nih.gov/pubmed/34729004
http://dx.doi.org/10.1007/s12528-021-09299-7
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