Insights in Learners' Behaviour and Early Dropout Detection based on Coursera MOOCs

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dc.catalogadorjwg
dc.contributor.authorFrank, Sarah
dc.contributor.authorGutl, Christian
dc.contributor.authorPerez-Sanagustin, Mar
dc.contributor.authorHilliger Carrasco, Isabel
dc.date.accessioned2025-03-17T13:41:50Z
dc.date.available2025-03-17T13:41:50Z
dc.date.issued2021
dc.description.abstractIncreased utilization of distance learning makes the creation of effective learning tools ever more important. However, while Massive Open Online Courses (MOOCs) are a popular online learning tool, they often suffer from high user attrition. This paper investigated this effect for 6 different MOOCs with more than 35 thousand users, using AdaBoosted decision trees to create a model which was then used for the prediction of dropouts, as well as the calculation of feature importance scores. The resulting model generally scored high accuracy scores which were plotted for each course, and feature importance scores were especially high for the features encompassing the number of user requests, the user's total active time and the average time between clicks. Furthermore, the paper explored the results of the inclusion of forum data in this setting. While the forum features did not lead to a major increase in model accuracy, there was a statistical difference between the number of forum interactions for those who completed the MOOCs and those who did not, which opens up possibilities for future research into utilization of forum interaction data, and forums in MOOCs in general.
dc.fuente.origenORCID
dc.identifier.doi10.1109/ITHET50392.2021.9759784
dc.identifier.eisbn9781728188836
dc.identifier.scopusidSCOPUS_ID:85130095492
dc.identifier.urihttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9759536
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/102652
dc.information.autorucEscuela de Ingeniería; Hilliger Carrasco Isabel; 0000-0001-5270-7655; 141681
dc.language.isoen
dc.nota.accesocontenido parcial
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof2021 19th International Conference on Information Technology Based Higher Education and Training, ITHET 2021
dc.revista2021 19th International Conference on Information Technology Based Higher Education and Training, ITHET 2021
dc.rightsacceso restringido
dc.subjectCoursera
dc.subjectDropout Detection
dc.subjectMOOC
dc.subject.ddc370
dc.subject.deweyEducaciónes_ES
dc.titleInsights in Learners' Behaviour and Early Dropout Detection based on Coursera MOOCs
dc.typecomunicación de congreso
sipa.codpersvinculados141681
sipa.trazabilidadORCID;2025-03-03
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