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AI-Driven Assessment of Students: Current Uses and Research Trends
dc.contributor.authorSánchez Prieto, José Carlos 
dc.contributor.authorGamazo García, Adriana 
dc.contributor.authorCruz-Benito, Juan
dc.contributor.authorTherón Sánchez, Roberto 
dc.contributor.authorGarcía Peñalvo, Francisco J. 
dc.date.accessioned2022-01-13T12:34:07Z
dc.date.available2022-01-13T12:34:07Z
dc.date.issued2020
dc.identifier.citationSánchez-Prieto, J. C., Gamazo, A., Cruz-Benito, J., Therón, R., & García-Peñalvo, F. J. (2020). AI-Driven Assessment of Students: Current Uses and Research Trends. In P. Zaphiris & A. Ioannou (Eds.), Learning and Collaboration Technologies. Design, Experiences. 7th International Conference, LCT 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings, Part I (pp. 292-302). Springer Nature. https://doi.org/10.1007/978-3-030-50513-4_22. ISSN 0302-9743. ISSN 1611-3349 (electronic). ISBN 978-3-030-50512-7. ISBN 978-3-030-50513-4 (eBook).es_ES
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/10366/148287
dc.description.abstractDuring the last decade, the use of AIs is being incorporated into the educational field whether to support the analysis of human behavior in teachinglearning contexts, as didactic resource combined with other technologies or as a tool for the assessment of the students. This proposal presents a Systematic Literature Review and mapping study on the use of AIs for the assessment of students that aims to provide a general overview of the state of the art and identify the current areas of research by answering 6 research questions related with the evolution of the field, and the geographic and thematic distribution of the studies. As a result of the selection process this study identified 20 papers focused on the research topic in the repositories SCOPUS and Web of Science from an initial amount of 129. The analysis of the papers allowed the identification of three main thematic categories: assessment of student behaviors, assessment of student sentiments and assessment of student achievement as well as several gaps in the literature and future research lines addressed in the discussion.es_ES
dc.format.mimetypeapplication/pdf
dc.language.isoenges_ES
dc.rightsAtribución-NoComercial-CompartirIgual 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectArtificial intelligencees_ES
dc.subjectEducationes_ES
dc.subjectAssessmentes_ES
dc.subjectAlgorithmic evaluationes_ES
dc.titleAI-Driven Assessment of Students: Current Uses and Research Trendses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publishversionhttps://doi.org/10.1007/978-3-030-50513-4_22es_ES
dc.subject.unesco5312.04 Educaciónes_ES
dc.subject.unesco1203.17 Informáticaes_ES
dc.identifier.doi10.1007/978-3-030-50513-4_22
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.essn1611-3349
dc.journal.titleLearning and Collaboration Technologies. Design, Experiences. 7th International Conference, LCT 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19–24, 2020, Proceedings, Part I (pp. 292-302). Springer Nature.es_ES
dc.volume.number12205es_ES
dc.page.initial292es_ES
dc.page.final302es_ES
dc.type.hasVersioninfo:eu-repo/semantics/acceptedVersiones_ES


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