Data Interoperability in Learning Analytics - Review of Literature

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dc.contributor.affiliationRocha, J.C., Universidade Federal de Pelotas, Centro de Desenvolvimento Tecnolgico, Pelotas, Brazil
dc.contributor.affiliationRamos, V., Universidade Federal de Santa Catarina, Depto. de Engenharia do Conhecimento, Florianópolis, Brazil
dc.contributor.affiliationCechinel, C., Universidade Federal de Santa Catarina, Coord. Tec. da Informação e Comunicação (CIT), Ararangua, Brazil
dc.contributor.affiliationHernandez-Leal, E.J., Universidad de Medellín, Facultad de Ingenierías, Medellin, Colombia
dc.contributor.affiliationMunoz, R., Universidad de Valparaíso, Escuela de Ingeniería Informática, Valparaiso, Chile
dc.contributor.affiliationPrimo, T.T., Universidade Federal de Pelotas, Centro de Engenharias, Pelotas, Brazil
dc.contributor.authorRocha J.C
dc.contributor.authorRamos V
dc.contributor.authorCechinel C
dc.contributor.authorHernandez-Leal E.J
dc.contributor.authorMunoz R
dc.contributor.authorPrimo T.T.
dc.contributor.conferencename50th Latin American Computing Conference, CLEI 2024spa
dc.date.accessioned2025-04-28T22:09:21Z
dc.date.available2025-04-28T22:09:21Z
dc.date.issued2024
dc.descriptionLearning analytics (LA) and educational data mining (EDM) are two complementary approaches to modeling and understanding teaching-learning processes and, in general, data from academic environments. LA is applied to data from various sources, which can vary in format, granularity, and structure. Integrating these data is key to addressing the challenge of scalability in LA, a fundamental aspect. To this end, interoperability, understood as the ability of different systems, devices, or applications to connect, interact, and work together effectively, is crucial and generates the need for specifications for the case of academic information systems and Learning Management Systems. According to this context, the objective of this work was to address through a literature review the following main question: What are the main challenges for modeling architecture to support the interoperability of educational data to apply Learning Analytics? To develop the review, the team used Parsifal, an online tool designed to conduct systematic literature reviews in the context of software engineering. The initial search was done in six databases, deciding to include twenty papers in the final report. The results showed that there are still many open spaces for research and development in terms of the design and use of educational data specifications for the subsequent application of LA, to make the transition from models built on data coming from a single source to the construction of models that report results from the integration of several sources using specifications like Caliper Analytics or Experience API. © 2024 IEEE.
dc.identifier.doi10.1109/CLEI64178.2024.10700464
dc.identifier.instnameinstname:Universidad de Medellínspa
dc.identifier.isbn9798331540975
dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellínspa
dc.identifier.repourlrepourl:https://repository.udem.edu.co/
dc.identifier.urihttp://hdl.handle.net/11407/8825
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.spa
dc.publisher.facultyFacultad de Ingenieríasspa
dc.publisher.programIngeniería de Sistemasspa
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85207842224&doi=10.1109%2fCLEI64178.2024.10700464&partnerID=40&md5=0e6d3a5de83916af8b9daa7b50f71603
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.sourceProceedings - 2024 50th Latin American Computing Conference, CLEI 2024
dc.sourceProc. - Lat. American Comput. Conf., CLEI
dc.sourceScopus
dc.subjectData Interchange
dc.subjectData Source
dc.subjectEducational Data Mining
dc.subjectInteroperability
dc.subjectLearning Analytics
dc.subjectAdversarial machine learning
dc.subjectAcademic environment
dc.subjectData interchange
dc.subjectData interoperability
dc.subjectData-source
dc.subjectEducational data mining
dc.subjectInformation system management
dc.subjectLearning analytic
dc.subjectLearning management system
dc.subjectOR applications
dc.subjectTeaching-learning process
dc.subjectContrastive Learning
dc.subjectData Interchange
dc.subjectData Source
dc.subjectEducational Data Mining
dc.subjectInteroperability
dc.subjectLearning Analytics
dc.titleData Interoperability in Learning Analytics - Review of Literature
dc.typeConference Paper
dc.type.localDocumento de conferenciaspa
dc.type.versioninfo:eu-repo/semantics/publishedVersion

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