Learning analytics and collaborative groups of learners in distance education: a systematic mapping study

• Published in: Informatics in education Vol. 21; no. 1; pp. 113 - 146
• Main Authors: 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
• Format: Journal Article
• Language: English
• Published: Vilnius Vilniaus Universiteto Leidykla 2022; Vilnius University Press; Institute of Mathematics and Informatics; Vilnius University Institute of Mathematics and Informatics, Lithuanian Academy of Sciences; Vilnius University
• Subjects: CAI; Collaboration; Collaborative Groups; Communication studies; Computer assisted instruction; Cooperative Learning; Data analysis; Data Collection; Data mining; Distance Education; Distance learning; Distance learning / e-learning; e-learning; Education; Educational Benefits; Electronic Learning; Evaluation Methods; Integrated Learning Systems; Learning Analytics; Learning management systems; Learning Processes; Mapping; Methodology and research technology; Online instruction; Recommender systems; Student Records; Virtual environments; virtual learning environments; collaborative groups; learning analytics; elearning; virtual learning environments
• ISSN: 1648-5831; 2335-8971
• DOI: 10.15388/infedu.2022.05

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.