Student engagement as predictor of xMOOC completion: An analysis from five courses on energy sustainability

dc.contributor.authorGuajardo-Leal, Brenda E.
dc.contributor.authorValenzuela González, Jaime Ricardo
dc.contributor.authorScott, John
dc.date.accessioned2018-11-28T16:22:56Z
dc.date.available2018-11-28T16:22:56Z
dc.date.issued2019
dc.description.abstractMOOC are characterized as being courses to which a large number of students enroll, but only a small fraction completes them. An understanding of students' engagement construct is essential to minimize dropout rates. This research is of a quantitative design and exploratory in nature, and investigates the interaction between contextual factors (demographic characteristics), student engagement types (academic, behavioral, cognitive and affective), and learning outcomes, with the objective of identifying the factors that are associated with completion of massive and open online courses. Two logistic models were adjusted in two samples, general and secondary, with the binary dependent variable defined as completes the course yes/no. The results in the general sample (15% completion rate) showed that the probabilities of a participant completing the course are positively and significantly related to participation in the forum and the participant educational level, and negatively related to gender (female) and age. The results in the secondary sample (87% completion rate) showed that the probabilities of a participant completing the course are positively and significantly related to participation in the forum, gender (female), and the motivation and satisfaction indexes, and negatively related to age, having previous experience in other MOOCs, and self-efficacy and task strategies indexes. The results lead to ideas on how these variables can be used to support students to persist in these learning environments.
dc.description.notesAbstract MOOC are characterized as being courses to which a large number of students enroll, but only a small fraction completes them. An understanding of students' engagement construct is essential to minimize dropout rates. This research is of a quantitative design and exploratory in nature, and investigates the interaction between contextual factors (demographic characteristics), student engagement types (academic, behavioral, cognitive and affective), and learning outcomes, with the objective of identifying the factors that are associated with completion of massive and open online courses. Two logistic models were adjusted in two samples, general and secondary, with the binary dependent variable defined as completes the course yes/no. The results in the general sample (15% completion rate) showed that the probabilities of a participant completing the course are positively and significantly related to participation in the forum and the participant educational level, and negatively related to gender (female) and age. The results in the secondary sample (87% completion rate) showed that the probabilities of a participant completing the course are positively and significantly related to participation in the forum, gender (female), and the motivation and satisfaction indexes, and negatively related to age, having previous experience in other MOOCs, and self-efficacy and task strategies indexes. The results lead to ideas on how these variables can be used to support students to persist in these learning environments.en_US
dc.identifier.doihttp://dx.doi.org/10.24059/olj.v23i2.1523en_US
dc.identifier.journalOnline Learning Journalen_US
dc.identifier.urihttp://hdl.handle.net/11285/632315
dc.language.isoengen_US
dc.relationEsta investigación (tesis/ proyecto de campo) es un producto del proyecto 266632 “Laboratorio Binacional para la Gestión Inteligente de la Sustentabilidad Energética y la Formación Tecnológica” financiado a través de Fondo CONACYT SENER de Sustentabilidad Energética (S0019201401).en_US
dc.relation.isPartOf266632-CONACYT-SENER-S0019201401
dc.relation.ispartof266632-CONACYT-SENER-S0019201401
dc.subject.keywordengagement, learning analytics, xMOOC, self-regulated learning, completionen_US
dc.subject.lembEstados Unidos de América / United Statesen_US
dc.titleStudent engagement as predictor of xMOOC completion: An analysis from five courses on energy sustainabilityen_US
dc.typeArtículo
html.description.abstract<html> <head> <title></title> </head> <body> <p>MOOC are characterized as being courses to which a large number of students enroll, but only a small fraction completes them. An understanding of students' engagement construct is essential to minimize dropout rates. This research is of a quantitative design and exploratory in nature, and investigates the interaction between contextual factors (demographic characteristics), student engagement types (academic, behavioral, cognitive and affective), and learning outcomes, with the objective of identifying the factors that are associated with completion of massive and open online courses. Two logistic models were adjusted in two samples, general and secondary, with the binary dependent variable defined as completes the course yes/no. The results in the general sample (15% completion rate) showed that the probabilities of a participant completing the course are positively and significantly related to participation in the forum and the participant educational level, and negatively related to gender (female) and age. The results in the secondary sample (87% completion rate) showed that the probabilities of a participant completing the course are positively and significantly related to participation in the forum, gender (female), and the motivation and satisfaction indexes, and negatively related to age, having previous experience in other MOOCs, and self-efficacy and task strategies indexes. The results lead to ideas on how these variables can be used to support students to persist in these learning environments.</p> </body> </html>en_US
refterms.dateFOA2018-11-28T16:22:57Z

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