dc.creatorde-la-Fuente-Valentín, Luis (1)
dc.creatorBurgos, Daniel (1)
dc.creatorGonzález-Crespo, Rubén (1)
dc.date.accessioned2020-03-31T09:15:09Z
dc.date.accessioned2023-03-07T19:26:22Z
dc.date.available2020-03-31T09:15:09Z
dc.date.available2023-03-07T19:26:22Z
dc.date.created2020-03-31T09:15:09Z
dc.identifier9781479940387
dc.identifier2161-3761
dc.identifierhttps://reunir.unir.net/handle/123456789/9927
dc.identifierhttps://doi.org/10.1109/ICALT.2014.107
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5904277
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.
dc.languageeng
dc.publisher2014 14TH IEEE International conference on advanced learning technologies (ICALT)
dc.relationhttps://dl.acm.org/doi/abs/10.1109/ICALT.2014.107
dc.rightsrestrictedAccess
dc.subjectgrade estimation
dc.subjectvisual analytics
dc.subjectsimilarity
dc.subjectawareness tool
dc.subjectWOS(2)
dc.subjectScopus(2)
dc.titleA4Learning: a case study to improve the user performance Alumni Alike Activity Analytics to self-assess personal progress
dc.typeconferenceObject


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