Deep Learning for Discussion-Based Cross-Domain Performance Prediction of MOOC Learners Grouped by Language on FutureLearn

dc.contributor.author	Duru, Ismail
dc.contributor.author	Sunar, Ayse Saliha
dc.contributor.author	White, Su
dc.contributor.author	Diri, Banu
dc.date.accessioned	16/12/21 12:06
dc.date.available	16/12/21 12:06
dc.date.issued	2021
dc.identifier.issn	2193-567X
dc.identifier.uri	http://dspace.beu.edu.tr:8080/xmlui/handle/20.500.12643/9876
dc.identifier.uri	https://doi.org/10.1007/s13369-020-05117-x
dc.description.abstract	Analysing learners' behaviours in MOOCs has been used to identify predictive features associated with positive outcomes in engagement and learning success. Early methods predominantly analysed numerical features of behaviours such as the page views, video
dc.description.sponsorship	TUBITAKTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [1059B141601346, 1059B281304197]; University of Southampton [23593]
dc.language.iso	English
dc.publisher	Sprınger Heıdelberg
dc.rights	Green Published, Bronze
dc.source	Arabıan Journal For Scıence And Engıneerıng
dc.title	Deep Learning for Discussion-Based Cross-Domain Performance Prediction of MOOC Learners Grouped by Language on FutureLearn
dc.type	Article
dc.identifier.issue	4
dc.identifier.startpage	3613
dc.identifier.endpage	3629
dc.identifier.doi	10.1007/s13369-020-05117-x
dc.identifier.wos	WOS:000605539200001
dc.identifier.volume	46

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