{ "dc.contributor.author": "Slimani, Abdelali" , "dc.contributor.author": "Elouaai, Fatiha" , "dc.contributor.author": "Elaachak, Lotfi" , "dc.contributor.author": "Yedri, Othman Bakkali" , "dc.contributor.author": "Bouhorma, Mohammed" , "dc.contributor.author": "Sbert, Mateu" , "dc.date.accessioned": "2019-03-21T07:53:30Z" , "dc.date.available": "2019-03-21T07:53:30Z" , "dc.date.issued": "2018" , "dc.identifier.uri": "http://hdl.handle.net/10256/16372" , "dc.description.abstract": "Learning analytics is an emerging discipline focused on the measurement, collection, analysis and reporting of learner interaction data through the E-learning contents. Serious game provides a potential source for relevant educational user data; it can propose an interactive environment for training and offer an effective learning process. This paper presents methods and approaches of educational data mining such as EM and K-Means to discuss the learning analytics through serious games, and then we provide an analysis of the player experience data collected from the educational game 'ELISA' used to teach students of biology the immunological technique for determination of ANTI-HIV antibodies. Finally, we propose critically evaluation of our results including the limitations of our study and making suggestions for future research that links learning analytics and serious gaming" , "dc.format.extent": "19 p." , "dc.format.mimetype": "application/pdf" , "dc.language.iso": "eng" , "dc.publisher": "International Association of Online Engineering (IAOE)" , "dc.relation.isformatof": "Reproducció digital del document publicat a: https://doi.org/10.3991/ijet.v13i01.7518" , "dc.relation.ispartof": "International Journal of Emerging Technologies in Learning (iJET), 2018, vol. 13, núm. 1, p. 46-64" , "dc.relation.ispartofseries": "Articles publicats (D-IMAE)" , "dc.rights": "Reconeixement 3.0 Espanya" , "dc.rights.uri": "http://creativecommons.org/licenses/by/3.0/es" , "dc.source": "Slimani, Abdelali Elouaai, Fatiha Elaachak, Lotfi Yedri, Othman Bakkali Bouhorma, Mohammed Sbert, Mateu 2018 Learning Analytics Through Serious Games: Data Mining Algorithms for Performance Measurement and Improvement Purposes International Journal of Emerging Technologies in Learning (iJET) 13 1 46 64" , "dc.subject": "Ensenyament virtual" , "dc.subject": "Web-based instruction" , "dc.subject": "Aprenentatge actiu" , "dc.subject": "Active learning" , "dc.title": "Learning Analytics Through Serious Games: Data Mining Algorithms for Performance Measurement and Improvement Purposes" , "dc.type": "info:eu-repo/semantics/article" , "dc.rights.accessRights": "info:eu-repo/semantics/openAccess" , "dc.type.version": "info:eu-repo/semantics/publishedVersion" , "dc.identifier.doi": "https://doi.org/10.3991/ijet.v13i01.7518" , "dc.identifier.idgrec": "029518" , "dc.type.peerreviewed": "peer-reviewed" , "dc.identifier.eissn": "1863-0383" }