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dc.contributor.authorAkazaki, Jacqueline Mayumipt_BR
dc.contributor.authorMachado, Letícia Sophia Rochapt_BR
dc.contributor.authorSilva, Kétia Kellen Araújo dapt_BR
dc.contributor.authorBehar, Patrícia Alejandrapt_BR
dc.date.accessioned2021-05-21T04:45:15Zpt_BR
dc.date.issued2020pt_BR
dc.identifier.issn2411-2933pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/221362pt_BR
dc.description.abstractVirtual courses are increasingly being offered in Brazil, making it imperative to develop technological resources and research to help in the teaching and learning processes in this modality. One approach is to analyze student's socio-affective profile in Virtual Learning Environments (VLE). The co-operative learning network (ROODA) VLE has two features called the Social Map (SM) and Affective Map (AM), which can both contribute to the visualization of data regarding social interaction indicators and students' moods in the environment. The SM presents the social relations formed through indicators, which are the absence; collaboration; the distance from the class; evasion; informal groups and popularity, enabling the identification of the participating subjects in the form of sociograms. The AM identifies students' moods graphically through indicators, which are excitement, discouragement, satisfaction, and dissatisfaction. Thus, this article aims to map the possible recurrent socio-affective scenarios in a VLE using Learning Analytics (LA). LA is defined as measurement, collection, analysis, and reporting of data about students and their contexts to understand as well as optimize learning and the environments in which it occurs. It can also contribute to the understanding of student's learning profile, based on social and affective aspects, thus allowing the teacher to develop pedagogical strategies consistent with the needs of each subject. The importance of integrating the possible social and affective scenarios was verified using LA, making it possible to deepen the comprehension of the subjective and qualitative questions regarding the students' interactions in the VLE. In this study, the scenarios are understood as the intersection between the Affective Map and Social Map indicators identified in a VLE. It has both a qualitative and quantitative approach. The choice is qualitatively justified because the research object involves social and affective phenomena that were subjectively expressed in texts and social interactions manifested in the ROODA VLE. It is quantitatively justified by the need to measure the mapping of socio-affective indicators through social parameters and moods applying LA. The subjects were undergraduate students who participated in distance learning courses at a Brazilian public university that used the ROODA VLE in the second semester of 2019. Data were collected from social and affective maps to identify if there was a relationship between them. As a result, based on the existing indicators of social interactions and moods, the socio-affective indicators were created using LA in order to analyze the students’ behavior in relation to the forms of interaction and communication that occur in the ROODA VLE.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.relation.ispartofInternational journal for innovation education and research. [Dhaka, Bangladesh]. Vol. 8, n. 6 (2020), p.pt_BR
dc.rightsOpen Accessen
dc.subjectSocio-affectiveen
dc.subjectTecnologia educacionalpt_BR
dc.subjectVirtual Learning Environmenten
dc.subjectLearning Analyticsen
dc.titleLearning analyticsin a virtual learning environment : the challenge of mapping socio-affective scenariospt_BR
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb001126102pt_BR
dc.type.originEstrangeiropt_BR


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