dc.creatorMaldonado Mahauad, Jorge Javier
dc.date2018-01-11T16:47:33Z
dc.date2018-01-11T16:47:33Z
dc.date2017-01-01
dc.dateinfo:eu-repo/date/embargoEnd/2022-01-01 0:00
dc.date.accessioned2018-03-14T20:32:27Z
dc.date.available2018-03-14T20:32:27Z
dc.identifier3601315
dc.identifierhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84994524464&doi=10.1016%2fj.compedu.2016.10.001&partnerID=40&md5=76824461fc6cc15f3615274425295af1
dc.identifierhttp://dspace.ucuenca.edu.ec/handle/123456789/29152
dc.identifier10.1016/j.compedu.2016.10.001
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1136054
dc.descriptionIndividuals with strong self-regulated learning (SRL) skills, characterized by the ability to plan, manage and control their learning process, can learn faster and outperform those with weaker SRL skills. SRL is critical in learning environments that provide low levels of support and guidance, as is commonly the case in Massive Open Online Courses (MOOCs). Learners can be trained to engage in SRL and actively supported with prompts and activities. However, effective implementation of learner support systems in MOOCs requires an understanding of which SRL strategies are most effective and how these strategies manifest in online behavior. Moreover, identifying learner characteristics that are predictive of weaker SRL skills can advance efforts to provide targeted support without obtrusive survey instruments. We investigated SRL in a sample of 4,831 learners across six MOOCs based on individual records of overall course achievement, interactions with course content, and survey responses. Results indicated that goal setting and strategic planning predicted attainment of personal course goals, while help seeking appeared to be counterproductive. Learners with stronger SRL skills were more likely to revisit previously studied course materials, especially course assessments. Several learner characteristics, including demographics and motivation, predicted learners’ SRL skills. We discuss implications for theory and the development of learning environments that provide adaptive support.
dc.languageen_US
dc.publisherELSEVIER LTD
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/3.0/ec/
dc.sourceinstname:Universidad de Cuenca
dc.sourcereponame:Repositorio Digital de la Universidad de Cuenca
dc.sourceComputers and Education
dc.subjectIndividual differences
dc.subjectLearning analytics
dc.subjectMassive open online course
dc.subjectOnline learning
dc.subjectSelf-regulated learning
dc.titleSelf-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses
dc.typeArtículos de revistas


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