Mostrar registro simples

dc.contributor.authorBoff, Elisapt_BR
dc.contributor.authorReategui, Eliseo Bernipt_BR
dc.date.accessioned2018-05-05T03:16:09Zpt_BR
dc.date.issued2013pt_BR
dc.identifier.issn1989-1660pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/177560pt_BR
dc.description.abstractThis paper presents a learning environment where a mining algorithm is used to learn patterns of interaction with the user and to represent these patterns in a scheme called item descriptors. The learning environment keeps theoretical information about subjects, as well as tools and exercises where the student can put into practice the knowledge gained. One of the main purposes of the project is to stimulate collaborative learning through the interaction of students with different levels of knowledge. The students' actions, as well as their interactions, are monitored by the system and used to find patterns that can guide the search for students that may play the role of a tutor. Such patterns are found with a particular learning algorithm and represented in item descriptors. The paper presents the educational environment, the representation mechanism and learning algorithm used to mine social-affective data in order to create a recommendation model of tutors.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.relation.ispartofInternational Journal of Interactive Multimedia and Artificial Intelligence. 2013. Vol. 2, n. 1 (2013), 32-38pt_BR
dc.rightsOpen Accessen
dc.subjectCollaborationen
dc.subjectTecnologia educacionalpt_BR
dc.subjectTutoriapt_BR
dc.subjectLearning Environmenten
dc.subjectRecommender Systemsen
dc.subjectSocial-Affective Dataen
dc.titleMining social and affective data for recommendation of student tutorspt_BR
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb000931317pt_BR
dc.type.originEstrangeiropt_BR


Thumbnail
   

Este item está licenciado na Creative Commons License

Mostrar registro simples