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MBOX :
MBOX : Designing a Flexible IoT Multimodal Learning Analytics System
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- Ouhaichi, Hamza (författare)
- Malmö universitet,Institutionen för datavetenskap och medieteknik (DVMT)
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- Spikol, Daniel, 1965- (författare)
- Univ Copenhagen, Dept Sci Educ, Copenhagen, Denmark.
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- Vogel, Bahtijar (författare)
- Malmö universitet,Institutionen för datavetenskap och medieteknik (DVMT)
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(creator_code:org_t)
- IEEE, 2021
- 2021
- Engelska.
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Ingår i: IEEE 21st International Conferenceon Advanced Learning TechnologiesICALT 2021. - : IEEE. - 9781665441063 ; , s. 122-126
- Relaterad länk:
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Multimodal Learning Analytics (MMLA) provides opportunities for understanding and supporting collaborative problem-solving. However, the implementation of MMLA systems is challenging due to the lack of scalable technologies and limited solutions for collecting data from group work. This paper proposes the Multimodal Box (MBOX), an IoT-based system for MMLA, allowing the collection and processing of multimodal data from collaborative learning tasks. MBOX investigates the development and design for an IoT focusing on small group work in real-world settings. Moreover, MBOX promotes adaptation to different learning environments and enables a better scaling of computational resources used within the learning context.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- Multimodal Learning Analytics
- CSCL
- IoT
- Interaction Design
- Human Social Signal Processing
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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