The big five: Addressing recurrent multimodal learning data challenges

Daniele Di Mitri, Jan Schneider, Marcus Specht, Hendrik Drachsler

Research output: Contribution to journalConference articleScientificpeer-review

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
JournalCEUR Workshop Proceedings
Volume2163
Publication statusPublished - 2018
Externally publishedYes
Event2nd Multimodal Learning Analytics Across (Physical and Digital) Spaces, CrossMMLA 2018 - Sydney, Australia
Duration: 6 Mar 20186 Mar 2018

Keywords

  • CrossMMLA
  • Multimodal learning analytics
  • Sensor-based learning
  • Wearables

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