The Multimodal Tutor - short pitch presentation at JTELSS 2018 in Durrës, Albania
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Multimodal data from video recordings, sensor data, and human annotations can be collected and processed to generate feedback for learning. This data is analyzed to develop a multimodal tutor that provides digital support for learning across physical spaces. The paper explores how to use multimodal data to create a tutor that gives feedback.
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The Multimodal Tutor - short pitch presentation at JTELSS 2018 in Durrës, Albania
- 1. How to use multimodal data to generate feedback in learning? RQ multimodal data collection Human judge Video recordings Sensor data human annotation Digital support for learning across physical spaces what’s NEW? Multimodal Tutordata processing & analysis ddm@ou.nl @dimstudi0
Editor's Notes
- My phd project is the Multimodal Tutor The problem I want to solve is how to use multimodal data to generate feedback in learning The originality is a new digital support for learning across physical spaces The Multimodal Tutor can be seen as a cycle (that we also call Multimodal pipeline) Green box Collecting data from multiple modalities using multiple sensors and data sources Red box using human judges to interpret and annotate multimodal data recordings Yellow box using the machine learning and data processing to combine multimodal data to human interpretations Blue box is how to enhance feedback
- The Multimodal Tutor now looks like the wall of the PinkFloyd Complex cycle made by multiple steps Few datasets Architecture