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

Autor/inn/en	da Silva, Lidia M.; Dias, Lucas P. S.; Barbosa, Jorge L. V.; Rigo, Sandro J.; dos Anjos, Julio C. S.; Geyer, Claudio F. R.; Leithardt, Valderi R. Q.
Titel	Learning Analytics and Collaborative Groups of Learners in Distance Education: A Systematic Mapping Study
Quelle	In: Informatics in Education, 21 (2022) 1, S.113-146 (34 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1648-5831
Schlagwörter	Learning Analytics; Cooperative Learning; Distance Education; Electronic Learning; Evaluation Methods; Data Collection; Integrated Learning Systems; Student Records; Educational Benefits + Suchen Sie Ihr Suchwort? Kooperatives Lernen; Distance study; Distance learning; Fernunterricht; Data capture; Datensammlung; Schülerakte; Bildungsertrag
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. (As Provided).
Anmerkungen	Vilnius University Institute of Mathematics and Informatics, Lithuanian Academy of Sciences. Akademjos str. 4, Vilnius LT 08663 Lithuania. Tel: +37-5-21-09300; Fax: +37-5-27-29209; e-mail: info@mii.vu.lt; Web site: https://infedu.vu.lt/journal/INFEDU
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01