The analysis of multimodal data in learning is a growing field of research, which has led to the development of different analytics solutions. However, there is no standardised approach to handle multimodal data. In this paper, we describe and outline a solution for five recurrent challenges in the analysis of multimodal data: the data collection, storing, annotation, processing and exploitation. For each of these challenges, we envision possible solutions. The prototypes for some of the proposed solutions will be discussed during the Multimodal Challenge of the fourth Learning Analytics & Knowledge Hackathon, a two-day hands-on workshop in which the authors will open up the prototypes for trials, validation and feedback.
|Title of host publication||Companion Proceedings of the 8th International Conference on Learning Analytics and Knowledge|
|Subtitle of host publication||Towards User-Centred Learning Analytics|
|Place of Publication||Syndey, Australia|
|Number of pages||5|
|Publication status||Published - Mar 2018|
|Event||The 8th International Learning Analytics & Knowledge Conference - SMC Conference & Function Centre, Sydney, Australia|
Duration: 5 Mar 2018 → 9 Mar 2018
|Conference||The 8th International Learning Analytics & Knowledge Conference|
|Period||5/03/18 → 9/03/18|
- multimodal learning analytics
- sensor-based learning
Di Mitri, D., Schneider, J., Specht, M., & Drachsler, H. (2018). The Big Five: Addressing Recurrent Multimodal Learning Data Challenges. In Companion Proceedings of the 8th International Conference on Learning Analytics and Knowledge: Towards User-Centred Learning Analytics (pp. 420-424). SoLAR.