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Implementing a Learning Record Warehouse for Different Interoperability Specifications in Moodle LMS

dc.contributor.authorRocha J.C.
dc.contributor.authorHernandez-Leal E.J.
dc.contributor.authorRamos V.
dc.contributor.authorMunoz R.
dc.contributor.authorCechinel C.
dc.contributor.authorPrimo T.T.
dc.contributor.authorQueiroga E.M.
dc.date.accessioned2024-12-27T20:52:03Z
dc.date.available2024-12-27T20:52:03Z
dc.date.created2024
dc.identifier.isbn979-835037661-6
dc.identifier.urihttp://hdl.handle.net/11407/8706
dc.descriptionSemantic interoperability is an important aspect in Learning Analytics systems, allowing data from various sources to be processed by a central application while preserving its original meaning. In this regard, there are two specifications that enable interoperability for Learning Analytics: Caliper Analytics and the Experience API (xAPI). This study presents the implementation of a Learning Record Warehouse (LRW) for storing Moodle logs, using the specifications Caliper Analytics and xAPI. OpenLRW was chosen as the platform to store data collected by plugins responsible for gathering Moodle logs in Caliper Analyzer and xAPI formats. Despite OpenLRW having an internal converter to convert data from xAPI to Caliper Analyzer format, some bottlenecks were identified during the experiments conducted within this study. © 2024 IEEE.
dc.language.isoeng
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85201202540&doi=10.1109%2fSIIE63180.2024.10604489&partnerID=40&md5=9d53244b0059f17eee6ec5ca57017030
dc.source26th International Symposium on Computers in Education, SIIE 2024
dc.sourceInt. Symp. Comput. Educ., SIIE
dc.sourceScopus
dc.subjectCaliper Analyzereng
dc.subjectLearning Analyticseng
dc.subjectLearning Record Ware-houseeng
dc.subjectMoodleeng
dc.subjectStandardseng
dc.subjectxAPIeng
dc.subjectData handlingeng
dc.subjectInteroperabilityeng
dc.subjectSemanticseng
dc.subjectWarehouseseng
dc.subjectAnalytics systemseng
dc.subjectCaliper analyzereng
dc.subjectLearning analyticeng
dc.subjectLearning recordeng
dc.subjectLearning record ware-houseeng
dc.subjectMoodleeng
dc.subjectPlug-inseng
dc.subjectSemantic interoperabilityeng
dc.subjectXAPIeng
dc.subjectSpecificationseng
dc.titleImplementing a Learning Record Warehouse for Different Interoperability Specifications in Moodle LMSeng
dc.typeConference paper
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.publisher.programIngeniería de Sistemas
dc.identifier.doi10.1109/SIIE63180.2024.10604489
dc.publisher.facultyFacultad de Ingenierías
dc.affiliationRocha J.C., Centro de Desenvolvimento Tecnológico, Universidade Federal de Pelotas, Pelotas, Brazil
dc.affiliationHernandez-Leal E.J., Universidad de Medellin, Facultad de Ingenierias, Medellin, Colombia
dc.affiliationRamos V., Universidade Federal de Santa Catarina, Depto. de Engenharia Do Conhecimento, Florianópolis, Brazil
dc.affiliationMunoz R., Universidad de Valparaiso, Escuela de Ingenieria Informática, Valparaiso, Chile
dc.affiliationCechinel C., Universidade Federal de Santa Catarina, Coord. Tec. da Informação e Comunicação (CIT), Araranguá, Brazil
dc.affiliationPrimo T.T., Centro de Engenharias, Universidade Federal de Pelotas, Pelotas, Brazil
dc.affiliationQueiroga E.M., Instituto Federal Sul-rio-grandense, Diretoria de Tec. da Informação, Pelotas, Brazil
dc.relation.referencesMoissa B., Gasparini I., Kemczinski A., Learning analytics: um mapeamento sistemático, Nuevas Ideas en Informática Educativa TISE, 19, pp. 283-290, (2014)
dc.relation.referencesSiemens G., Gasevic D., Haythornthwaite C., Dawson S., Shum S.B., Ferguson R., Duval E., Verbert K., Baker R., Et al., Open learning analytics: an integrated & modularized platform, (2011)
dc.relation.referencesda Matta Furniel A.C., Bernardo-Mendonca A.P., da Silva R.M., Recursos educacionais abertos: Conceitos e princípios, (2019)
dc.relation.referencesSayao L.F., Marcondes C.H., O desafio da interoperabilidade e as novas perspectivas para as bibliotecas digitais, Transinformação, 20, pp. 133-148, (2008)
dc.relation.referencesBishr Y.A., Semantic aspects of interoperable GIS, (1997)
dc.relation.referencesSheth A.P., Changing focus on interoperability in information systems: from system, syntax, structure to semantics, Interoperating geographic information systems, pp. 5-29, (1999)
dc.relation.referencesBaker R.S., Inventado P.S., Educational Data Mining and Learning Analytics, pp. 61-75, (2014)
dc.relation.references(2011)
dc.relation.referencesQueiroga E.M., Paragarino V.R., Casas A.P., Primo T.T., Munoz R., Ramos V.C., Cechinel C., Experimenting learning analytics and educational data mining in different educational contexts and levels, 2022 XVII Latin American Conference on Learning Technologies (LACLO), pp. 1-9, (2022)
dc.relation.referencesSiemens G., Learning analytics: The emergence of a discipline, American Behavioral Scientist, 57, 10, pp. 1380-1400, (2013)
dc.relation.referencesRomero C., Ventura S., Educational data mining and learning analytics: An updated survey, Wiley interdisciplinary reviews: Data mining and knowledge discovery, 10, 3, (2020)
dc.relation.referencesChatti M.A., Dyckhoff A.L., Schroeder U., Thus H., A reference model for learning analytics, International Journal of Technology Enhanced Learning, 4, 5-6, pp. 318-331, (2013)
dc.relation.referencesZohair L.M.A., Prediction of student’s performance by modelling small dataset size, International Journal of Educational Technology in Higher Education, 16, 1, (2019)
dc.relation.referencesPaik J.H., Himelfarb I., Yoo S.H., Yoo K., Ha H., The relationships among school engagement, students’ emotions, and academic performance in an elementary online learning, Proceedings of the 14th Learning Analytics and Knowledge Conference, 2024, pp. 219-230
dc.relation.referencesSiemens G., Dawson S., Lynch G., Improving the quality and productivity of the higher education sector, Policy and Strategy for Systems-Level Deployment of Learning Analytics, 31, (2013)
dc.relation.referencesTarouco L.M.R., Avila B.G., Bez M.R., Objetos de Aprendizagem: teoria e prática, (2014)
dc.relation.referencesSchiffner D., Ritter M., Horn F., Learning analytics bundle, DeLFI 2018-Die 16. E-Learning Fachtagung Informatik, (2018)
dc.relation.referencesCaliper 1.1 Metric Profiles | IMS Global Learning Consortium, (2024)
dc.relation.referencesRyunosuke M., Watnus M., Takayuki N., Et al., Development of a logging system for student activities on mahara according to xapi standard by using apache logs and openlrs, IPSJ SIG Technical Report (CLE), 2016, 2, pp. 1-4, (2016)
dc.relation.referencesGuterres J.P.D., Framework para construção de objetos de aprendizagem com learning analytics
dc.relation.referencesPurpose · xAPI LRS Conformance Requirements, (2024)
dc.relation.referencesJohnson A., xAPI-Spec, (2024)
dc.relation.referencesKevan J.M., Ryan P.R., Experience api: Flexible, decentralized and activity-centric data collection, Technology, Knowledge and Learning, 21, pp. 143-149, (2016)
dc.relation.referencesAngeloni M.P.C., Saliah-Hassane H., da Silva J.B., da Mota Alves J.B., Model to evaluate users’ engagement to augmented reality using xapi, Advances in Intelligent Systems and Computing, 1231, pp. 320-329
dc.relation.referencesGriffiths D., Hoel T., Comparing xapi and caliper, Learning Analytics Review, 7, (2016)
dc.relation.referencesKitto K., Lupton M., Bruza P., Mallett D., Banks J., Dawson S., Gasevic D., Buckingham Shum S., Pardo A., Siemens G., Learning Analytics beyond the LMS: Enabling Connected Learning via Open Source Analytics in” the wild, Office for Learning and Teaching
dc.relation.referencesSyed M., Anggara T., Lanski A., Duan X., Ambrose G.A., Chawla N.V., Integrated closed-loop learning analytics scheme in a first year experience course, Proceedings of the 9th international conference on learning analytics & knowledge, pp. 521-530, (2019)
dc.relation.referencesCechinel C., Queiroga E., Primo T., Ramos V., Munoz R., Machado M., Stein M., Rocha J., Rodrigues T., Santos H., Portelinha G., Targino R., Melgarejo V., Almeida J., Learning analytics para moodle em uma arquitetura na nuvem: uma solução escalável para predição de risco acadêmico, Anais do Workshop de Aplicações Práticas de Learning Analytics em Instituições de Ensino no Brasil (WAPLA), pp. 128-137
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.reponamereponame:Repositorio Institucional Universidad de Medellín
dc.identifier.repourlrepourl:https://repository.udem.edu.co/
dc.identifier.instnameinstname:Universidad de Medellín
dc.contributor.event26th International Symposium on Computers in Education, SIIE 2024


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