Work

Using Gaze Transition Entropy to Detect Classroom Discourse in a Virtual Reality Classroom

Year: 2024

Type: conference-paper

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.

Source: ACM Symposium on Eye Tracking Research and Applications (ETRA)

DOI: 10.1145/3649902.3653335

Authors: Philipp Stark, Alexander J. Jung, Jens-Uwe Hahn, Enkelejda Kasneci, Richard Göllner

Institutions: University of Tübingen, Stuttgart Media University, Technical University of Munich, University of Regensburg

Language: English

Topic: Gaze Tracking and Assistive Technology

Subfield: Human-Computer Interaction

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

OpenAlex ID: W4399200099

FWCI: 1.95

Cites: 42

Cited by: 8

Related to: 10