Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses

Individuals 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...

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Autor: Maldonado Mahauad, Jorge Javier
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2017
País:Ecuador
Institución:Universidad de Cuenca
Repositorio:Repositorio Universidad de Cuenca
OAI Identifier:oai:dspace.ucuenca.edu.ec:123456789/29152
Acceso en línea:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994524464&doi=10.1016%2fj.compedu.2016.10.001&partnerID=40&md5=76824461fc6cc15f3615274425295af1
http://dspace.ucuenca.edu.ec/handle/123456789/29152
Access Level:acceso abierto
Palabra clave:Individual Differences
Learning Analytics
Massive Open Online Course
Online Learning
Self-Regulated Learning
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spelling Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online CoursesMaldonado Mahauad, Jorge JavierIndividual DifferencesLearning AnalyticsMassive Open Online CourseOnline LearningSelf-Regulated LearningIndividuals 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.ELSEVIER LTD2018-01-11T16:47:33Z2018-01-11T16:47:33Z2017-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdf3601315https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994524464&doi=10.1016%2fj.compedu.2016.10.001&partnerID=40&md5=76824461fc6cc15f3615274425295af1http://dspace.ucuenca.edu.ec/handle/123456789/2915210.1016/j.compedu.2016.10.001Computers and Educationreponame:Repositorio Universidad de Cuencainstname:Universidad de Cuencainstacron:UCUENCAen_USinfo:eu-repo/semantics/openAccess2020-08-01T01:15:26Zoai:dspace.ucuenca.edu.ec:123456789/29152Institucionalhttp://dspace.ucuenca.edu.ec/Universidad públicahttps://www.ucuenca.edu.ec/http://dspace.ucuenca.edu.ec/oai.Ecuador...opendoar:41862020-08-01T01:15:26Repositorio Universidad de Cuenca - Universidad de Cuencafalse
dc.title.none.fl_str_mv Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses
title Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses
spellingShingle Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses
Maldonado Mahauad, Jorge Javier
Individual Differences
Learning Analytics
Massive Open Online Course
Online Learning
Self-Regulated Learning
title_short Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses
title_full Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses
title_fullStr Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses
title_full_unstemmed Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses
title_sort Self-regulated learning strategies predict learner behavior and goal attainment in Massive Open Online Courses
dc.creator.none.fl_str_mv Maldonado Mahauad, Jorge Javier
author Maldonado Mahauad, Jorge Javier
author_facet Maldonado Mahauad, Jorge Javier
author_role author
dc.subject.none.fl_str_mv Individual Differences
Learning Analytics
Massive Open Online Course
Online Learning
Self-Regulated Learning
topic Individual Differences
Learning Analytics
Massive Open Online Course
Online Learning
Self-Regulated Learning
description Individuals 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.
publishDate 2017
dc.date.none.fl_str_mv 2017-01-01
2018-01-11T16:47:33Z
2018-01-11T16:47:33Z
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
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format article
status_str publishedVersion
dc.identifier.none.fl_str_mv 3601315
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994524464&doi=10.1016%2fj.compedu.2016.10.001&partnerID=40&md5=76824461fc6cc15f3615274425295af1
http://dspace.ucuenca.edu.ec/handle/123456789/29152
10.1016/j.compedu.2016.10.001
identifier_str_mv 3601315
10.1016/j.compedu.2016.10.001
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http://dspace.ucuenca.edu.ec/handle/123456789/29152
dc.language.none.fl_str_mv en_US
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dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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publisher.none.fl_str_mv ELSEVIER LTD
dc.source.none.fl_str_mv Computers and Education
reponame:Repositorio Universidad de Cuenca
instname:Universidad de Cuenca
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instname_str Universidad de Cuenca
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