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dc.contributor.authorEkici, Murat
dc.contributor.authorCoskun, H. Irem
dc.contributor.authorYurdugul, Halil
dc.date.accessioned2020-01-17T08:38:35Z
dc.date.available2020-01-17T08:38:35Z
dc.date.issued2014
dc.identifier.issn1877-0428
dc.identifier.urihttps://doi.org/10.1016/j.sbspro.2014.05.050
dc.identifier.urihttp://hdl.handle.net/11655/21790
dc.description.abstractIn this research, researchers aim to contribute to current literature on self-regulation by investigating the relationship between learning approaches and online self-regulation behaviour. In this study we use learning approaches as a predictor of online self-regulation skills. Sub factors of online self-regulation skills; environmental structuring, goal setting, time management, help seeking, task strategies, self-evaluation are dependent variables and sub factors of the learning approaches; deep approach, surface approach are independent variables. Research data collected from 303 college student who attended online distance courses of Usak University. Regression analysis showed that learning approaches are significant predictors of online self-regulation skills. (C) 2014 The Authors. Published by Elsevier Ltd. Open access under CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).tr_TR
dc.language.isoentr_TR
dc.publisherElsevier Science Bvtr_TR
dc.relation.isversionof10.1016/j.sbspro.2014.05.050tr_TR
dc.rightsinfo:eu-repo/semantics/openAccesstr_TR
dc.subjectEducation & Educational Researchtr_TR
dc.subject.lcshEğitimtr_TR
dc.titleInvestigation of the Relationship Between Learning Approaches and Online Self-Regulation Behaviourtr_TR
dc.typeinfo:eu-repo/semantics/conferenceObjecttr_TR
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.relation.journal4Th World Conference On Learning Teaching And Educational Leadership (Wclta-2013)tr_TR
dc.contributor.departmentBilgisayar ve Öğretim Teknolojileritr_TR
dc.identifier.volume141tr_TR
dc.identifier.startpage285tr_TR
dc.identifier.endpage289tr_TR
dc.description.indexWoStr_TR
dc.fundingYoktr_TR


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