Please use this identifier to cite or link to this item: http://repositorio.grial.eu/handle/grial/1083
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dc.contributor.authorGarcía-Holgado, Alicia-
dc.contributor.authorGarcía-Peñalvo, Francisco J.-
dc.date.accessioned2017-12-22T08:18:35Z-
dc.date.available2017-12-22T08:18:35Z-
dc.date.issued2017-10-18-
dc.identifier.citationGarcía-Holgado, A., & García-Peñalvo, F. J. (2017). Preliminary validation of the metamodel for developing learning ecosystems. In J. M. Dodero, M. S. Ibarra Sáiz, & I. Ruiz Rube (Eds.), Fifth International Conference on Technological Ecosystems for Enhancing Multiculturality (TEEM’17) (Cádiz, Spain, October 18-20, 2017) (Article 91). New York, NY, USA: ACM. doi:10.1145/3144826.3145439en
dc.identifier.isbn978-1-4503-5386-1-
dc.identifier.urihttp://repositorio.grial.eu/handle/grial/1083-
dc.description.abstractLearning ecosystems are positioned as a technological solution able to provide learning environments that evolve over time to cover the changing needs of users or include new tools for knowledge management. The definition, development and deployment of this type of software solutions is complex and involves several problems identified and analyzed in previous works. In order to solve these problems, an architectural pattern based on Buschmann's Layers pattern has been defined. The accumulated experience developing learning ecosystems along with the problems analysis using Business Process Model and Notation and the architectural pattern, have provided a knowledge base to define an ecosystems metamodel. The proposed metamodel provides a framework for Model-Driven Development of learning ecosystems. The main objective of the present work is to validate the ecosystems metamodel from modeling a learning ecosystem.en
dc.language.isoenen
dc.publisherACMen
dc.subjectTechnological ecosystemsen
dc.subjectSoftware ecosystemsen
dc.subjectMDAen
dc.subjectModelingen
dc.subjectSoftware engineeringen
dc.subjectKnowledge managementen
dc.subjectOpen Sourceen
dc.subjectGestión del conocimientoes
dc.titlePreliminary validation of the metamodel for developing learning ecosystemsen
dc.typeArticleen
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