MBOX : Designing a Flexible IoT Multimodal Learning Analytics System

MBOX : Designing a Flexible IoT Multimodal Learning Analytics System

Publication Type:
paper-conference
Date Issued:
2021
Authors:
Hamza Ouhaichi , Daniel Spikol , Bahtijar Vogel
Publisher:
IEEE
Language:
eng
Page:
122-126
DOI:
10.1109/ICALT52272.2021.00044
ISBN:
978-1-6654-4106-3
Abstract:

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.

Keywords:
Multimodal Learning Analytics CSCL IoT Interaction Design Human Social Signal Processing