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Adaptable Smart Learning Environments supported by Multimodal Learning Analytics
GSIC-EMIC Research Group, Universidad de Valladolid, Spain.
Departments of Computer Science and Science Education, University of Copenhagen, Denmark.
GSIC-EMIC Research Group, Universidad de Valladolid, Spain.
Malmö universitet, Fakulteten för teknik och samhälle (TS), Institutionen för datavetenskap och medieteknik (DVMT).ORCID-id: 0000-0002-9278-8063
Vise andre og tillknytning
2021 (engelsk)Inngår i: Proceedings of the LA4SLE 2021 Workshop: Learning Analytics for Smart Learning Environmentsco-located with the 16th European Conference on Technology Enhanced Learning 2021 (ECTEL 2021) / [ed] Davinia Hernández-Leo, Elise Lavoué, Miguel L. Bote-Lorenzo, Pedro J. Muñoz-Merino, Daniel Spikol, CEUR-WS.org , 2021, s. 24-30Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Smart Learning Environments and Learning Analytics hold promise of providing personalized support to learners according to their individual needs and context. This support can be achieved by collecting and analyzing data from the different learning tools and systems that are involved in the learning experience. This paper presents a first exploration of requirements and considerations for the integration of two systems: MBOX, a Multimodal Learning Analytics system for the physical space (human behavior and learning context), and SCARLETT, an SLE for the support during across-spaces learning situations combining different learning systems. This integration will enable the SLE to have access to a new and wide range of information, notably students’ behavior and social interactions in the physical learning context (e.g. classroom). The integration of multimodal data with the data coming from the digital learning environments will result in a more holistic system, therefore producing learning analytics that trigger personalized feedback and learning resources. Such integration and support is illustrated with a learning scenario that helps to discuss how these analytics can be derived and used for the intervention by the SLE.

    

sted, utgiver, år, opplag, sider
CEUR-WS.org , 2021. s. 24-30
HSV kategori
Identifikatorer
URN: urn:nbn:se:mau:diva-48217Scopus ID: 2-s2.0-85120677206ISBN: 978-3-030-86436-1 (digital)OAI: oai:DiVA.org:mau-48217DiVA, id: diva2:1620861
Konferanse
EC-TEL 2021: Learning Analytics for Smart Learning Environments, September 21, 2021, Bolzano, Italy
Tilgjengelig fra: 2021-12-16 Laget: 2021-12-16 Sist oppdatert: 2024-12-05bibliografisk kontrollert
Inngår i avhandling
1. Towards designing a flexible multimodal learning analytics system
Åpne denne publikasjonen i ny fane eller vindu >>Towards designing a flexible multimodal learning analytics system
2022 (engelsk)Licentiatavhandling, med artikler (Annet vitenskapelig)
sted, utgiver, år, opplag, sider
Malmö: Malmö universitet, 2022. s. 43
Serie
Studies in Computer Science ; 19
HSV kategori
Identifikatorer
urn:nbn:se:mau:diva-51502 (URN)10.24834/isbn.9789178772988 (DOI)978-91-7877-297-1 (ISBN)978-91-7877-298-8 (ISBN)
Veileder
Tilgjengelig fra: 2022-05-18 Laget: 2022-05-17 Sist oppdatert: 2024-09-18bibliografisk kontrollert

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