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dc.contributor.authorMacHado, CJR
dc.contributor.authorMacIel, AMA
dc.contributor.authorRodrigues, RL
dc.contributor.authorMenezes, R
dc.date.accessioned2019-07-01T14:58:02Z
dc.date.issued2019-01-01
dc.description.abstractDiscussion forums in learning management systems (LMS) have been shown to promote student interaction and contribute to the collaborative practice in the teaching-learning process. By evaluating the postings, teachers can identify students with learning difficulties. However, due to the large volume of posts that are generated on a daily basis in these environments, manual analysis becomes impractical. This article proposes a mechanism to support teaching through the thematic relevance analysis of the posts made by students in discussion forums. For this, text mining and metrics from network science were used to process and extract characteristics of the texts. Then, the processed texts were classified through supervised learning algorithms. The results show that the use of these techniques may generate potentially useful indicators for teachers to help them improve their pedagogical practices.en_GB
dc.identifier.citationVol. 17, pp. 37 - 51en_GB
dc.identifier.doi10.4018/IJDET.2019070103
dc.identifier.urihttp://hdl.handle.net/10871/37782
dc.language.isoenen_GB
dc.publisherIGI Globalen_GB
dc.rightsCopyright © 2019 IGI Global. All rights reserved.en_GB
dc.subjectLearning Management Systemsen_GB
dc.subjectDistance Learningen_GB
dc.titleAn approach for thematic relevance analysis applied to textual contributions in discussion forumsen_GB
dc.typeArticleen_GB
dc.date.available2019-07-01T14:58:02Z
dc.identifier.issn1539-3100
dc.descriptionThis is the final version. Available from IGI Global via the DOI in this record.en_GB
dc.identifier.journalInternational Journal of Distance Education Technologiesen_GB
dc.rights.urihttp://www.rioxx.net/licenses/all-rights-reserveden_GB
dcterms.dateAccepted2019-01-01
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2019-01-01
rioxxterms.typeJournal Article/Reviewen_GB
refterms.technicalExceptionexternalServiceProvider
refterms.dateFCD2019-07-01T14:47:21Z
refterms.versionFCDAM
refterms.dateFOA2019-07-01T14:58:05Z
refterms.panelBen_GB


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