dc.contributor.author | Muñoz-Merino, Pedro J. | |
dc.contributor.author | Ruipérez-Valiente, José A. | |
dc.contributor.author | Alario-Hoyos, Carlos | |
dc.contributor.author | Pérez-Sanagustín, Mar | |
dc.contributor.author | Delgado Kloos, Carlos | |
dc.date.accessioned | 2021-07-13T10:21:17Z | |
dc.date.available | 2021-07-13T10:21:17Z | |
dc.date.issued | 2015-06 | |
dc.identifier.issn | 0747-5632 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12761/1483 | |
dc.description.abstract | Present MOOC and SPOC platforms do not provide teachers with precise metrics that represent the effectiveness of students with educational resources and activities. This work proposes and illustrates the application of the Precise Effectiveness Strategy (PES). PES is a generic methodology for defining precise metrics that enable calculation of the effectiveness of students when interacting with educational resources and activities in MOOCs and SPOCs, taking into account the particular aspects of the learning context. PES has been applied in a case study, calculating the effectiveness of students when watching video lectures and solving parametric exercises in four SPOCs deployed in the Khan Academy platform. Different visualizations within and between courses are presented combining the metrics defined following PES. We show how these visualizations can help teachers make quick and informed decisions in our case study, enabling the whole comparison of a large number of students at a glance, and a quick comparison of the four SPOCs divided by videos and exercises. Also, the metrics can help teachers know the relationship of effectiveness with different behavioral patterns. Results from using PES in the case study revealed that the effectiveness metrics proposed had a moderate negative correlation with some behavioral patterns like recommendation listener or video avoider. | |
dc.language.iso | eng | |
dc.publisher | Elsevier | |
dc.title | Precise Effectiveness Strategy for analyzing the effectiveness of students with educational resources and activities in MOOCs | en |
dc.type | journal article | |
dc.journal.title | Computers in Human Behavior (Special issue: Learning Analytics, Educational Data Mining and data-driven Educational Decision Making) | |
dc.type.hasVersion | VoR | |
dc.rights.accessRights | open access | |
dc.volume.number | 47 | |
dc.identifier.url | http://dx.doi.org/10.1016/j.chb.2014.10.003 | |
dc.identifier.doi | doi:10.1016/j.chb.2014.10.003 | |
dc.page.final | 118 | |
dc.page.initial | 108 | |
dc.subject.keyword | Learning analytics | |
dc.subject.keyword | MOOCs | |
dc.subject.keyword | SPOCs | |
dc.subject.keyword | Precise Effective Strategy | |
dc.subject.keyword | metrics | |
dc.description.status | pub | |
dc.eprint.id | http://eprints.networks.imdea.org/id/eprint/978 | |