Toward Multimodal Analytics in Ubiquitous Learning Environments

While Ubiquitous Learning Environments (ULEs) have shown several benefits for learning, they pose challenges for orchestration. Teachers need to be aware of the learning process, which is difficult to achieve when it occurs across a heterogeneous set of spaces, resources and devices. In addition, ULEs can benefit from multimodal analyses due to the heterogeneity of the data sources available (e.g., logs, geolocation, sensor information, learning artifacts). In previous works, we proposed an orchestration system with some analytics features that can gather multimodal datasets during the learning process. Based on this experience, in this paper we describe the technological support provided by the system to collect data from multiple spaces and sources as well as the structure of the generated dataset. We also reflect about the challenges of multimodal learning analytics (MMLA) in ULEs, and we pose some ideas about how the system could better support MMLA in the future to mitigate those challenges.


Editor(s):
Prieto, Luis P.
Martínez-Maldonado, Roberto
Spikol, Daniel
Hernández-Leo, Davinia
Rodriguez Triana, Maria Jesus
Ochoa, Xavier
Published in:
Joint Proceedings of the Sixth Multimodal Learning Analytics (MMLA) Workshop and the Second Cross-LAK Workshop co-located with 7th International Learning Analytics and Knowledge Conference, 1828, 60-67
Presented at:
6th Multimodal Learning Analytics Workshop, Vancouver, Canada, March 14, 2017
Year:
2017
Publisher:
CEUR
Keywords:
Laboratories:




 Record created 2017-07-02, last modified 2018-11-14

Publisher's version:
Download fulltextPDF
External link:
Download fulltextURL
Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)