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Learning Analytics and Collaborative Groups of Learners in Distance Education: A Systematic Mapping Study.

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Title: Learning Analytics and Collaborative Groups of Learners in Distance Education: A Systematic Mapping Study.
Authors: da SILVA, Lidia M.1 lidiasilva@edu.unisinos.br, DIAS, Lucas P. S.1 lucaspfsd@gmail.com, BARBOSA, Jorge L. V.1 jbarbosa@unisinos.br, RIGO, Sandro J.1 rigo@unisinos.br, dos ANJOS, Julio C. S.2 jcsanjos@inf.ufrgs.br, GEYER, Claudio F. R.2 geyer@inf.ufrgs.br, LEITHARDT, Valderi R. Q.3 valderi@ipportalegre.pt
Source: Informatics in Education. Mar2022, Vol. 21 Issue 1, p113-146. 34p.
Subject Terms: *Distance education, *Courseware, *Educational technology, *Distance education students, *Learning management system, Data mining
Abstract: Advances in information and communication technologies have contributed to the increasing use of virtual learning environments as support tools in teaching and learning processes. Virtual platforms generate a large volume of educational data, and the analysis of this data allows useful information discoveries to improve learning and assist institutions in reducing disqualifications and dropouts in distance education courses. This article presents the results of a systematic mapping study aiming to identify how educational data mining, learning analytics, and collaborative groups have been applied in distance education environments. Articles were searched from 2010 to June 2020, initially resulting in 55,832 works. The selection of 51 articles for complete reading in order to answer the research questions considered a group of inclusion and exclusion criteria. Main results indicated that 53% of articles (27/51) offered intelligent services in the field of distance education, 47% (24/51) applied methods and analysis techniques in distance education environments, 21% (11/51) applied methods and analysis techniques focused on virtual learning environments logs and 5% (3/51) presented intelligent collaborative services for identification and creation of groups. This article also identified research interest clusters with highlights for the terms recommendation systems, data analysis, e-learning, educational data mining, e-learning platform and learning management system. [ABSTRACT FROM AUTHOR]
Copyright of Informatics in Education is the property of Informatics in Education and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Learning Analytics and Collaborative Groups of Learners in Distance Education: A Systematic Mapping Study.
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  Data: <searchLink fieldCode="AR" term="%22da+SILVA%2C+Lidia+M%2E%22">da SILVA, Lidia M.</searchLink><relatesTo>1</relatesTo><i> lidiasilva@edu.unisinos.br</i><br /><searchLink fieldCode="AR" term="%22DIAS%2C+Lucas+P%2E+S%2E%22">DIAS, Lucas P. S.</searchLink><relatesTo>1</relatesTo><i> lucaspfsd@gmail.com</i><br /><searchLink fieldCode="AR" term="%22BARBOSA%2C+Jorge+L%2E+V%2E%22">BARBOSA, Jorge L. V.</searchLink><relatesTo>1</relatesTo><i> jbarbosa@unisinos.br</i><br /><searchLink fieldCode="AR" term="%22RIGO%2C+Sandro+J%2E%22">RIGO, Sandro J.</searchLink><relatesTo>1</relatesTo><i> rigo@unisinos.br</i><br /><searchLink fieldCode="AR" term="%22dos+ANJOS%2C+Julio+C%2E+S%2E%22">dos ANJOS, Julio C. S.</searchLink><relatesTo>2</relatesTo><i> jcsanjos@inf.ufrgs.br</i><br /><searchLink fieldCode="AR" term="%22GEYER%2C+Claudio+F%2E+R%2E%22">GEYER, Claudio F. R.</searchLink><relatesTo>2</relatesTo><i> geyer@inf.ufrgs.br</i><br /><searchLink fieldCode="AR" term="%22LEITHARDT%2C+Valderi+R%2E+Q%2E%22">LEITHARDT, Valderi R. Q.</searchLink><relatesTo>3</relatesTo><i> valderi@ipportalegre.pt</i>
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  Data: <searchLink fieldCode="JN" term="%22Informatics+in+Education%22">Informatics in Education</searchLink>. Mar2022, Vol. 21 Issue 1, p113-146. 34p.
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  Data: *<searchLink fieldCode="DE" term="%22Distance+education%22">Distance education</searchLink><br />*<searchLink fieldCode="DE" term="%22Courseware%22">Courseware</searchLink><br />*<searchLink fieldCode="DE" term="%22Educational+technology%22">Educational technology</searchLink><br />*<searchLink fieldCode="DE" term="%22Distance+education+students%22">Distance education students</searchLink><br />*<searchLink fieldCode="DE" term="%22Learning+management+system%22">Learning management system</searchLink><br /><searchLink fieldCode="DE" term="%22Data+mining%22">Data mining</searchLink>
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  Data: Advances in information and communication technologies have contributed to the increasing use of virtual learning environments as support tools in teaching and learning processes. Virtual platforms generate a large volume of educational data, and the analysis of this data allows useful information discoveries to improve learning and assist institutions in reducing disqualifications and dropouts in distance education courses. This article presents the results of a systematic mapping study aiming to identify how educational data mining, learning analytics, and collaborative groups have been applied in distance education environments. Articles were searched from 2010 to June 2020, initially resulting in 55,832 works. The selection of 51 articles for complete reading in order to answer the research questions considered a group of inclusion and exclusion criteria. Main results indicated that 53% of articles (27/51) offered intelligent services in the field of distance education, 47% (24/51) applied methods and analysis techniques in distance education environments, 21% (11/51) applied methods and analysis techniques focused on virtual learning environments logs and 5% (3/51) presented intelligent collaborative services for identification and creation of groups. This article also identified research interest clusters with highlights for the terms recommendation systems, data analysis, e-learning, educational data mining, e-learning platform and learning management system. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Informatics in Education is the property of Informatics in Education and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Mar2022
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