Title
Edge-Based and Privacy-Preserving Multi-Modal Monitoring of Student Engagement in Online Learning Environments
Abstract
With engagement being an early predictor for a student's learning achievements, it is paramount that teachers can observe the behavior of their audience to keep them engaged, for example, with interactive lectures. In order to address this concern, we present an edge-based multimodal engagement analysis solution for teachers to maintain an engagement overview of their entire audience, including those in distance learning settings. We designed and evaluated an edge-based browser solution for the analysis of different behavior modalities with cross-user aggregation through secure multiparty computation.
Year
DOI
Venue
2019
10.1109/EDGE.2019.00017
2019 IEEE International Conference on Edge Computing (EDGE)
Keywords
Field
DocType
multi-modal engagement monitoring,edge computing,browser,privacy,online learning
Modalities,Edge computing,Online learning,Secure multi-party computation,Computer science,Distance education,Human–computer interaction,Student engagement,Modal
Conference
ISBN
Citations 
PageRank 
978-1-7281-2709-5
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Davy Preuveneers170565.56
Wouter Joosen22898287.70