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dc.contributor.authorBurgos, Daniel (1)
dc.date2020
dc.date.accessioned2020-08-03T10:01:30Z
dc.date.available2020-08-03T10:01:30Z
dc.identifier.citationBurgos, D. A Predictive System Informed by Students’ Similar Behaviour. Sustainability 2020, 12, 706.es_ES
dc.identifier.issn2071-1050
dc.identifier.urihttps://reunir.unir.net/handle/123456789/10301
dc.description.abstractIt is quite complex to adapt instruction to student needs in view of online education owing to the ensuing communication disconnection in such learning environments. Decision support schemes offer assistance by automatically gathering students' data and forwarding them to the tutor in the appropriate perspective, in order to predict their behaviour and implement some action beforehand to avert or promote the final upshot. This study shows of a decision support scheme known as u-Tutor that is centred on the similarity computation between learners in the past, and how it was used in a real-case scenario. For this case study, this tool has been utilized by two real courses comprising of 392 learners alongside academic faculty, as of 2015 to 2019. The analysis offered focuses on 3 research areas: (1) perceived usefulness, (2) usability of the tool and (3) success rate of classification. From the acquired data, it can be seen that the teaching group managed to offer excellent approximations for those learners who eventually managed to pass the course, whereas u-Tutor seemed to be an early warning for learners at risk, indicating its capacity as a tutors' supportive tool.es_ES
dc.language.isoenges_ES
dc.publisherSustainabilityes_ES
dc.relation.ispartofseries;vol. 12, nº 2
dc.relation.urihttps://www.mdpi.com/2071-1050/12/2/706es_ES
dc.rightsopenAccesses_ES
dc.subjectrecommender systemses_ES
dc.subjectlearning analyticses_ES
dc.subjectstudent’s behavioures_ES
dc.subjectbackground similaritieses_ES
dc.subjectlearning management systemses_ES
dc.subjectScopuses_ES
dc.subjectJCRes_ES
dc.titleA Predictive System Informed by Students’ Similar Behavioures_ES
dc.typeArticulo Revista Indexadaes_ES
reunir.tag~ARIes_ES
dc.identifier.doihttps://doi.org/10.3390/su12020706


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