Multimodal Data Fusion to Track Students’ Distress during Educational Gameplay

• Published in: Journal of Learning Analytics Vol. 9; no. 3; pp. 75 - 87
• Main Authors: Moon, Jewoong, Ke, Fengfeng, Sokolikj, Zlatko, Dahlstrom-Hakki, Ibrahim
• Format: Journal Article
• Language: English
• Published: 16.12.2022

Using multimodal data fusion techniques, we built and tested prediction models to track middle-school student distress states during educational gameplay. We collected and analyzed 1,145 data instances, sampled from a total of 31 middle-school students’ audio- and video-recorded gameplay sessions. W...