Editorial: educational big data: extracting meaning from data for smart education

Bibliographic Details
Main Author: Chen, Nian-shing
Publication Date: 2020
Other Authors: Yin, Chengjiu, Isaias, Pedro, Psotka, Joseph
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.2/16412
Summary: Data are a valuable resource in education, with a panoply of applications across all educational levels, subjects and stakeholders. When data becomes overwhelming in terms of volume and complexity, innovative techniques are required to extract meaning and transform this data into valuable information. This special issue of the journal focuses on the value of Educational Big Data in the context of different education levels, from pre-school to higher education. The manuscripts included in this issue approach the potential of EBD for academic performance prediction, learning analytics implementation, and the identification and improvement of student behavioral patterns and performance. They are centred on students and emphasize the role that technology can play in improving their learning experience and performance.
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spelling Editorial: educational big data: extracting meaning from data for smart educationEducational big dataDataAcademic performance predictionData are a valuable resource in education, with a panoply of applications across all educational levels, subjects and stakeholders. When data becomes overwhelming in terms of volume and complexity, innovative techniques are required to extract meaning and transform this data into valuable information. This special issue of the journal focuses on the value of Educational Big Data in the context of different education levels, from pre-school to higher education. The manuscripts included in this issue approach the potential of EBD for academic performance prediction, learning analytics implementation, and the identification and improvement of student behavioral patterns and performance. They are centred on students and emphasize the role that technology can play in improving their learning experience and performance.Taylor and Francis Ltd.Repositório AbertoChen, Nian-shingYin, ChengjiuIsaias, PedroPsotka, Joseph2024-08-06T16:12:36Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.2/16412eng1049-482010.1080/10494820.2019.1635395info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-26T09:45:21Zoai:repositorioaberto.uab.pt:10400.2/16412Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T21:07:18.858413Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Editorial: educational big data: extracting meaning from data for smart education
title Editorial: educational big data: extracting meaning from data for smart education
spellingShingle Editorial: educational big data: extracting meaning from data for smart education
Chen, Nian-shing
Educational big data
Data
Academic performance prediction
title_short Editorial: educational big data: extracting meaning from data for smart education
title_full Editorial: educational big data: extracting meaning from data for smart education
title_fullStr Editorial: educational big data: extracting meaning from data for smart education
title_full_unstemmed Editorial: educational big data: extracting meaning from data for smart education
title_sort Editorial: educational big data: extracting meaning from data for smart education
author Chen, Nian-shing
author_facet Chen, Nian-shing
Yin, Chengjiu
Isaias, Pedro
Psotka, Joseph
author_role author
author2 Yin, Chengjiu
Isaias, Pedro
Psotka, Joseph
author2_role author
author
author
dc.contributor.none.fl_str_mv Repositório Aberto
dc.contributor.author.fl_str_mv Chen, Nian-shing
Yin, Chengjiu
Isaias, Pedro
Psotka, Joseph
dc.subject.por.fl_str_mv Educational big data
Data
Academic performance prediction
topic Educational big data
Data
Academic performance prediction
description Data are a valuable resource in education, with a panoply of applications across all educational levels, subjects and stakeholders. When data becomes overwhelming in terms of volume and complexity, innovative techniques are required to extract meaning and transform this data into valuable information. This special issue of the journal focuses on the value of Educational Big Data in the context of different education levels, from pre-school to higher education. The manuscripts included in this issue approach the potential of EBD for academic performance prediction, learning analytics implementation, and the identification and improvement of student behavioral patterns and performance. They are centred on students and emphasize the role that technology can play in improving their learning experience and performance.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-01-01T00:00:00Z
2024-08-06T16:12:36Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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url http://hdl.handle.net/10400.2/16412
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1049-4820
10.1080/10494820.2019.1635395
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dc.publisher.none.fl_str_mv Taylor and Francis Ltd.
publisher.none.fl_str_mv Taylor and Francis Ltd.
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