This contribution describes one the challenges explored in the Fourth LAK Hackathon. This challenge aims at shifting the focus from learning situations which can be easily traced through user-computer interactions data and concentrate more on user-world interactions events, typical of co-located and practice-based learning experiences. This mission, pursued by the multimodal learning analytics (MMLA) community, seeks to bridge the gap between digital and physical learning spaces. The “multimodal” approach consists in combining learners’ motoric actions with physiological responses and data about the learning contexts. These data can be collected through multiple wearable sensors and Internet of Things (IoT) devices. This Hackathon table will confront with three main challenges arising from the analysis and valorisation of multimodal datasets: 1) the data collection and storing, 2) the data annotation, 3) the data processing and exploitation. Some research questions which will be considered in this Hackathon challenge are the following: how to process the raw sensor data streams and extract relevant features? which data mining and machine learning techniques can be applied? how can we compare two action recordings? How to combine sensor data with Experience API (xAPI)? what are meaningful visualisations for these data?
|Title of host publication||Companion Proceedings of the 8th International Conference on Learning Analytics and Knowledge (LAK'18)|
|Subtitle of host publication||Towards User-Centred Learning Analytics|
|Editors||Abelardo Pardo, Kathryn Bartimote, Grace Lynch, Simon Buckingham Shum, Rebecca Ferguson, Agathe Merceron, Xavier Ochoa|
|Place of Publication||Sydney, Australia|
|Number of pages||4|
|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). Multimodal Challenge: Analytics Beyond User-computer Interaction Data. In A. Pardo, K. Bartimote, G. Lynch, S. Buckingham Shum, R. Ferguson, A. Merceron, & X. Ochoa (Eds.), Companion Proceedings of the 8th International Conference on Learning Analytics and Knowledge (LAK'18): Towards User-Centred Learning Analytics (pp. 364-367). SoLAR.