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Learning analytics in higher education: assessing learning outcomes

dc.contributor.authorAlves, Paulo
dc.contributor.authorMorais, Carlos
dc.contributor.authorMiranda, Luísa
dc.date.accessioned2020-07-31T10:27:13Z
dc.date.available2020-07-31T10:27:13Z
dc.date.issued2017
dc.description.abstractStudents’ retention and dropout from degree courses before their completion continue to represent issues which challenge researchers, teachers and higher education institutions to seek solutions. Higher education institutions have been attempting different strategies to promote their students’ success, among which we highlight the implementation and use of virtual learning environments (VLEs). Through the use of learning analytics in the analysis of data regarding the frequency of access to a VLE as well as the learning outcomes of a sample of 2,636 undergraduates, we aimed to identify indicators which contribute to the possible prediction of student retention and dropout situations. The methodology followed is essentially quantitative and the desk review was the main data collection tool. The data was treated by using the statistic software SPSS for the organisation and descriptive statistic presentation, as well as inferential statistics through appropriate statistic tests. The outcomes of this study resulted in contributions which enable the prediction of undergraduates’ retention or dropout since we were able to prove that the lower the frequency of access to the institution’s virtual learning environment, the lower the attendance to on-site lessons and the lower the number of course units in which students obtain a passing mark. Absenteeism and the lack of course units passed represent indicators of school dropout and retention. This research work reveals to be of great importance since, through a framework associated with learning analytics, it provides indicators supported by a large amount of recent and validated data, which enables us to rethink the connection between undergraduates’ access to a virtual learning environment and its influence on educational attainment.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAlves, Paulo; Morais, Carlos; Miranda, Luísa (2017). Learning analytics in higher education: assessing learning outcomes. In 16th European Conference on e-Learning - ECEL 2017. Porto. p.25-32pt_PT
dc.identifier.issn2049-0992
dc.identifier.urihttp://hdl.handle.net/10198/22587
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherAcademic Conferences and Publishing International Limitedpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectLearning analyticspt_PT
dc.subjectVirtual learning environmentpt_PT
dc.subjectLearning outcomespt_PT
dc.subjectHigher educationpt_PT
dc.subjectEducationpt_PT
dc.titleLearning analytics in higher education: assessing learning outcomespt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlacePortopt_PT
oaire.citation.endPage32pt_PT
oaire.citation.startPage25pt_PT
oaire.citation.title16th European Conference on e-Learning - ECEL 2017pt_PT
person.familyNameAlves
person.familyNameMorais
person.familyNameMiranda
person.givenNamePaulo
person.givenNameCarlos
person.givenNameLuísa
person.identifier.ciencia-idC319-FC42-5B6B
person.identifier.ciencia-idF01E-0B29-326B
person.identifier.orcid0000-0002-0100-8691
person.identifier.orcid0000-0003-0537-0652
person.identifier.orcid0000-0002-7553-6059
person.identifier.ridN-6354-2013
person.identifier.ridN-6353-2013
person.identifier.scopus-author-id55834442100
person.identifier.scopus-author-id49863980800
person.identifier.scopus-author-id49864068900
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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relation.isAuthorOfPublication.latestForDiscovery43d3b0cd-8fd9-4194-a9df-9cca66f8726b

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