@inproceedings{1801d135f4fc424db6459e295a292298,
title = "Using Gaze Transition Entropy to Detect Classroom Discourse in a Virtual Reality Classroom",
abstract = "This paper explores gaze entropy as a metric for detecting classroom discourse events in a virtual reality (VR) classroom. Using data from a laboratory experiment with N = 240 secondary school students, we distinguished between events of teacher-centered classroom discourse (question, hand raising, answer) and teacher explanation by analyzing their transition and stationary gaze entropy. Employing multi-level regression models, both entropy measures effectively discriminated between the two events and distinguished different levels of classroom participation as indicated by the degree of hand-raising by virtual students. Furthermore, using both measures in a logistic regression model, the potential of gaze entropy could be demonstrated by predicting the two events with 67% accuracy. By analyzing transition and stationary entropy, the study attempts to uncover different gaze patterns associated with learning events in a virtual classroom. The results contribute to the research and development of VR scenarios that help to simulate effective learning environments.",
keywords = "Classroom Discourse, Event Detection, Eye Tracking, Gaze Entropy, Virtual Reality",
author = "Philipp Stark and Jung, {Alexander J.} and Hahn, {Jens Uwe} and Enkelejda Kasneci and Richard G{\"o}llner",
note = "Publisher Copyright: {\textcopyright} 2024 Owner/Author.; 16th Annual ACM Symposium on Eye Tracking Research and Applications, ETRA 2024 ; Conference date: 04-06-2024 Through 07-06-2024",
year = "2024",
month = jun,
day = "4",
doi = "10.1145/3649902.3653335",
language = "English",
series = "Eye Tracking Research and Applications Symposium (ETRA)",
publisher = "Association for Computing Machinery",
editor = "Spencer, {Stephen N.}",
booktitle = "Proceedings - ETRA 2024, ACM Symposium on Eye Tracking Research and Applications",
}