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Open AccessArticle

A Scalable Architecture for the Dynamic Deployment of Multimodal Learning Analytics Applications in Smart Classrooms

1
Telecommunication Software & Systems Group, Waterford Institute of Technology, X91 P20H Waterford, Ireland
2
Faculty of Computer Science, University of Murcia, 30100 Murcia, Spain
3
School of Digital Technologies, Tallinn University, 10120 Tallinn, Estonia
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(10), 2923; https://doi.org/10.3390/s20102923
Received: 22 April 2020 / Revised: 19 May 2020 / Accepted: 19 May 2020 / Published: 21 May 2020
(This article belongs to the Special Issue Teaching and Learning Advances on Sensors for IoT)
The smart classrooms of the future will use different software, devices and wearables as an integral part of the learning process. These educational applications generate a large amount of data from different sources. The area of Multimodal Learning Analytics (MMLA) explores the affordances of processing these heterogeneous data to understand and improve both learning and the context where it occurs. However, a review of different MMLA studies highlighted that ad-hoc and rigid architectures cannot be scaled up to real contexts. In this work, we propose a novel MMLA architecture that builds on software-defined networks and network function virtualization principles. We exemplify how this architecture can solve some of the detected challenges to deploy, dismantle and reconfigure the MMLA applications in a scalable way. Additionally, through some experiments, we demonstrate the feasibility and performance of our architecture when different classroom devices are reconfigured with diverse learning tools. These findings and the proposed architecture can be useful for other researchers in the area of MMLA and educational technologies envisioning the future of smart classrooms. Future work should aim to deploy this architecture in real educational scenarios with MMLA applications. View Full-Text
Keywords: smart classrooms; educational technology; multimodal learning analytics; internet of things; multisensorial networks smart classrooms; educational technology; multimodal learning analytics; internet of things; multisensorial networks
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Huertas Celdrán, A.; Ruipérez-Valiente, J.A.; García Clemente, F.J.; Rodríguez-Triana, M.J.; Shankar, S.K.; Martínez Pérez, G. A Scalable Architecture for the Dynamic Deployment of Multimodal Learning Analytics Applications in Smart Classrooms. Sensors 2020, 20, 2923.

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