RT info:eu-repo/semantics/conferenceObject
T1 A Data Value Chain to Model the Processing of Multimodal Evidence in Authentic Learning Scenarios
A1 Kant Shankar, Shashi
A1 Ruiz Calleja, Adolfo
A1 Serrano Iglesias, Sergio
A1 Ortega Arranz, Alejandro
A1 Topali, Paraskevi
A1 Martínez Monés, Alejandra
K1 Multimodal Learning Analytics
K1 Análisis de aprendizaje multimodal
K1 Data Value Chain
K1 Cadena de valor de datos
K1 Multimodal learning scenarios
K1 Escenarios de aprendizaje multimodal
AB Multimodal Learning Analytics (MMLA) uncovers the possibility to get a more holistic picture of a learning situation than traditional Learning Analytics, by triangulating learning evidence collected from multiple modalities. However, current MMLA solutions are complex and typically tailored to specific learning situations. In order to overcome this problem we are working towards an infrastructure that supports MMLA and can be adapted to different learning situations. As a first step in this direction, this paper analyzes four MMLA scenarios, abstracts their data processing activities and extracts a Data Value Chain to model the processing of multimodal evidence of learning. This helps us to reflect on the requirements needed for an infrastructure to support MMLA.
PB CEUR Workshop Proceedings
SN 1613-0073
YR 2019
FD 2019
LK http://uvadoc.uva.es/handle/10324/38674
UL http://uvadoc.uva.es/handle/10324/38674
LA eng
NO Caeiro Rodríguez, M.; Hernández García, A.; Muñoz Merino, P.J. Proceedings of the Learning Analytics Summer Institute (LASI Spain 2019), Vigo, Spain: CEUR, p. 71-83
NO Producción Científica
DS UVaDOC
RD 30-abr-2024