Using Gaze Transition Entropy to Detect Classroom Discourse in a Virtual Reality Classroom
(2024) 16th Annual ACM Symposium on Eye Tracking Research and Applications, ETRA 2024 In Eye Tracking Research and Applications Symposium (ETRA)- 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... (More)
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.
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- author
- Stark, Philipp LU ; Jung, Alexander J. ; Hahn, Jens Uwe ; Kasneci, Enkelejda and Göllner, Richard
- publishing date
- 2024-06-04
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Classroom Discourse, Event Detection, Eye Tracking, Gaze Entropy, Virtual Reality
- host publication
- Proceedings - ETRA 2024, ACM Symposium on Eye Tracking Research and Applications
- series title
- Eye Tracking Research and Applications Symposium (ETRA)
- editor
- Spencer, Stephen N.
- article number
- 23
- publisher
- Association for Computing Machinery (ACM)
- conference name
- 16th Annual ACM Symposium on Eye Tracking Research and Applications, ETRA 2024
- conference location
- Hybrid, Glasgow, United Kingdom
- conference dates
- 2024-06-04 - 2024-06-07
- external identifiers
-
- scopus:85196487654
- ISBN
- 9798400706073
- DOI
- 10.1145/3649902.3653335
- language
- English
- LU publication?
- no
- additional info
- Publisher Copyright: © 2024 Owner/Author.
- id
- 1d06eade-a0dc-4874-8cea-b8d5ce40c790
- date added to LUP
- 2024-10-15 08:45:08
- date last changed
- 2025-04-04 14:33:02
@inproceedings{1d06eade-a0dc-4874-8cea-b8d5ce40c790,
abstract = {{<p>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.</p>}},
author = {{Stark, Philipp and Jung, Alexander J. and Hahn, Jens Uwe and Kasneci, Enkelejda and Göllner, Richard}},
booktitle = {{Proceedings - ETRA 2024, ACM Symposium on Eye Tracking Research and Applications}},
editor = {{Spencer, Stephen N.}},
isbn = {{9798400706073}},
keywords = {{Classroom Discourse; Event Detection; Eye Tracking; Gaze Entropy; Virtual Reality}},
language = {{eng}},
month = {{06}},
publisher = {{Association for Computing Machinery (ACM)}},
series = {{Eye Tracking Research and Applications Symposium (ETRA)}},
title = {{Using Gaze Transition Entropy to Detect Classroom Discourse in a Virtual Reality Classroom}},
url = {{http://dx.doi.org/10.1145/3649902.3653335}},
doi = {{10.1145/3649902.3653335}},
year = {{2024}},
}