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dc.contributor.authorde-la-Fuente-Valentín, Luis
dc.contributor.authorBurgos, Daniel
dc.contributor.authorGonzález-Crespo, Rubén
dc.date2014
dc.date.accessioned2020-03-31T09:15:09Z
dc.date.available2020-03-31T09:15:09Z
dc.identifier.isbn9781479940387
dc.identifier.issn2161-3761
dc.identifier.urihttps://reunir.unir.net/handle/123456789/9927
dc.description.abstractStudents usually find difficult to estimate if their effort in learning courses finds the instructor expectations. They tend to estimate "if they are doing right" by comparing themselves with peers, but this is difficult in online learning scenarios. Grade estimation methods are usually early warning systems targeted to teachers, and few systems are targeted to the students. A4Learning (Alumni Alike Activity Analytics) combines visual feedback methods and visual analytics techniques to provide students with a method to self-estimate their grade by comparing themselves to students from previous course editions. This article details the proposed visualization and presents the validation of the tool with volunteer teachers.es_ES
dc.language.isoenges_ES
dc.publisher2014 14TH IEEE International conference on advanced learning technologies (ICALT)es_ES
dc.relation.urihttps://dl.acm.org/doi/abs/10.1109/ICALT.2014.107es_ES
dc.rightsrestrictedAccesses_ES
dc.subjectgrade estimationes_ES
dc.subjectvisual analyticses_ES
dc.subjectsimilarityes_ES
dc.subjectawareness tooles_ES
dc.subjectWOS(2)es_ES
dc.subjectScopus(2)es_ES
dc.titleA4Learning: a case study to improve the user performance Alumni Alike Activity Analytics to self-assess personal progresses_ES
dc.typeconferenceObjectes_ES
reunir.tag~ARIes_ES
dc.identifier.doihttps://doi.org/10.1109/ICALT.2014.107


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