Magister - Metodologia de análise de programas de educação à distância baseada em Learning Analytics

The increasing of the data registered in courses offered in the distance modality boost the use of computational methods adapted to the research and the grouping of educational data, aiming to discover learning behaviors patterns. This research area allows the development of automated monitoring, prediction and intervention tools aiming at improving the educational indexes. As a result, this work proposes a methodology for analyzing distance learning programs based on the Learning Analytics technology, using the students’ access data to the Learning Management System (LMS), identifying the most frequent sequential patterns of use and classifying them as according to the self-regulated learning categories. For a sequential mining of sequential data the SPAM and VGEN algorithms were applied to the databases of two educational institutions. In addition to the development of the methodology, as a result of processing, a high incidence of behavior not predicted in the self-regulated learning theory was identified, and to classify it was created a pattern called low participation.

Grantor

Brasil

Year dc:date.issued

2018

Author dc:creator

• Lacerda, Ivan Max Freire de

Advisor dc:contributor.advisor

• Valentim, Ricardo Alexsandro de Medeiros

• Aprendizagem autorregulada
• Ensino a distância
• Ambiente virtual de aprendizagem
• Mineração de dados educacionais
• Learning analytics

Statement dc:rights

• Acesso Aberto

Language dc:language

por

Repository record dc:identifier.uri

https://repositorio.ufrn.br/jspui/handle/123456789/25609

OAI identifier oai:identifier

oai:repositorio.ufrn.br:123456789/25609