CrossMMLA in practice: Collecting, annotating and analyzing multimodal data across spaces
Research output: Contribution to journal › Conference article › Research › peer-review
Standard
CrossMMLA in practice : Collecting, annotating and analyzing multimodal data across spaces. / Giannakos, Michail; Spikol, Daniel; Molenaar, Inge; Mitri, Daniele Di; Sharma, Kshitij; Ochoa, Xavier; Hammad, Rawad.
In: CEUR Workshop Proceedings, Vol. 2610, 2020.Research output: Contribution to journal › Conference article › Research › peer-review
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - GEN
T1 - CrossMMLA in practice
T2 - 2020 CrossMMLA in Practice: Collecting, Annotating and Analyzing Multimodal Data Across Spaces, CrossMMLA 2020
AU - Giannakos, Michail
AU - Spikol, Daniel
AU - Molenaar, Inge
AU - Mitri, Daniele Di
AU - Sharma, Kshitij
AU - Ochoa, Xavier
AU - Hammad, Rawad
PY - 2020
Y1 - 2020
N2 - Learning is a complex process that is associated with many aspects of interaction and cognition (e.g., hard mental operations, cognitive friction etc.) and that can take across diverse contexts (online, classrooms, labs, maker spaces, etc.). The complexity of this process and its environments means that it is likely that no single data modality can paint a complete picture of the learning experience, requiring multiple data streams from different sources and times to complement each other. The need to understand and improve learning that occurs in ever increasingly open, distributed, subject-specific and ubiquitous scenarios, require the development of multimodal and multisystem learning analytics. Following the tradition of CrossMMLA workshop series, the proposed workshop aims to serve as a place to learn about the latest advances in the design, implementation and adoption of systems that take into account the different modalities of human learning and the diverse settings in which it takes place. Apart from the necessary interchange of ideas, it is also the objective of this workshop to develop critical discussion, debate and co-development of ideas for advancing the state-of-the-art in CrossMMLA.
AB - Learning is a complex process that is associated with many aspects of interaction and cognition (e.g., hard mental operations, cognitive friction etc.) and that can take across diverse contexts (online, classrooms, labs, maker spaces, etc.). The complexity of this process and its environments means that it is likely that no single data modality can paint a complete picture of the learning experience, requiring multiple data streams from different sources and times to complement each other. The need to understand and improve learning that occurs in ever increasingly open, distributed, subject-specific and ubiquitous scenarios, require the development of multimodal and multisystem learning analytics. Following the tradition of CrossMMLA workshop series, the proposed workshop aims to serve as a place to learn about the latest advances in the design, implementation and adoption of systems that take into account the different modalities of human learning and the diverse settings in which it takes place. Apart from the necessary interchange of ideas, it is also the objective of this workshop to develop critical discussion, debate and co-development of ideas for advancing the state-of-the-art in CrossMMLA.
KW - Learning spaces
KW - Multimodal learning analytics
KW - Sensor data
UR - http://www.scopus.com/inward/record.url?scp=85087460871&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:85087460871
VL - 2610
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
SN - 1613-0073
Y2 - 24 March 2020
ER -
ID: 256267920