Standard
MBOX : Designing a flexible IoT multimodal learning analytics system. / Ouhaichi, Hamza; Spikol, Daniel; Vogel, Bahtijar.
Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021. ed. / Maiga Chang; Nian-Shing Chen; Demetrios G Sampson; Ahmed Tlili. IEEE, 2021. p. 122-126 (Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021).
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Harvard
Ouhaichi, H
, Spikol, D & Vogel, B 2021,
MBOX: Designing a flexible IoT multimodal learning analytics system. in M Chang, N-S Chen, DG Sampson & A Tlili (eds),
Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021. IEEE, Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021, pp. 122-126, 21st IEEE International Conference on Advanced Learning Technologies, ICALT 2021, Virtual, Online, Malaysia,
12/07/2021.
https://doi.org/10.1109/ICALT52272.2021.00044APA
Ouhaichi, H.
, Spikol, D., & Vogel, B. (2021).
MBOX: Designing a flexible IoT multimodal learning analytics system. In M. Chang, N-S. Chen, D. G. Sampson, & A. Tlili (Eds.),
Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021 (pp. 122-126). IEEE. Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021
https://doi.org/10.1109/ICALT52272.2021.00044Vancouver
Ouhaichi H
, Spikol D, Vogel B.
MBOX: Designing a flexible IoT multimodal learning analytics system. In Chang M, Chen N-S, Sampson DG, Tlili A, editors, Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021. IEEE. 2021. p. 122-126. (Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021).
https://doi.org/10.1109/ICALT52272.2021.00044Author
Ouhaichi, Hamza ; Spikol, Daniel ; Vogel, Bahtijar. / MBOX : Designing a flexible IoT multimodal learning analytics system. Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021. editor / Maiga Chang ; Nian-Shing Chen ; Demetrios G Sampson ; Ahmed Tlili. IEEE, 2021. pp. 122-126 (Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021).
Bibtex
@inproceedings{5bc144a5c93a47c48cae482ec1b45567,
title = "MBOX: Designing a flexible IoT multimodal learning analytics system",
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 = "CSCL, Human Social Signal Processing, Interaction Design, IoT, Multimodal Learning Analytics",
author = "Hamza Ouhaichi and Daniel Spikol and Bahtijar Vogel",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 21st IEEE International Conference on Advanced Learning Technologies, ICALT 2021 ; Conference date: 12-07-2021 Through 15-07-2021",
year = "2021",
doi = "10.1109/ICALT52272.2021.00044",
language = "English",
series = "Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021",
pages = "122--126",
editor = "Maiga Chang and Nian-Shing Chen and Sampson, {Demetrios G} and Ahmed Tlili",
booktitle = "Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021",
publisher = "IEEE",
}
RIS
TY - GEN
T1 - MBOX
T2 - 21st IEEE International Conference on Advanced Learning Technologies, ICALT 2021
AU - Ouhaichi, Hamza
AU - Spikol, Daniel
AU - Vogel, Bahtijar
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - CSCL
KW - Human Social Signal Processing
KW - Interaction Design
KW - IoT
KW - Multimodal Learning Analytics
U2 - 10.1109/ICALT52272.2021.00044
DO - 10.1109/ICALT52272.2021.00044
M3 - Article in proceedings
AN - SCOPUS:85114887166
T3 - Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021
SP - 122
EP - 126
BT - Proceedings - IEEE 21st International Conference on Advanced Learning Technologies, ICALT 2021
A2 - Chang, Maiga
A2 - Chen, Nian-Shing
A2 - Sampson, Demetrios G
A2 - Tlili, Ahmed
PB - IEEE
Y2 - 12 July 2021 through 15 July 2021
ER -
