Detecting Teacher Expertise in an Immersive VR Classroom: Leveraging Fused Sensor Data with Explainable Machine Learning Models

Hong Gao, Efe Bozkir, Philipp Stark, Patricia Goldberg, Gerrit Meixner, Enkelejda Kasneci, Richard Gollner

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

4 Zitate (Scopus)

Abstract

Currently, VR technology is increasingly being used in applications to enable immersive yet controlled research settings. One such area of research is expertise assessment, where novel technological approaches to collecting process data, specifically eye tracking, in combination with explainable models, can provide insights into assessing and training novices, as well as fostering expertise development. We present a machine learning approach to predict teacher expertise by leveraging data from an off-the-shelf VR device collected in a VirATec study. By fusing eye-tracking and controller-tracking data, teachers' recognition and handling of disruptive events in the classroom are taken into account or considered. Three classification models were compared, including SVM, Random Forest, and LightGBM, with Random Forest achieving the best ROC-AUC score of 0.768 in predicting teacher expertise. The SHAP approach to model interpretation revealed informative features (e.g., fixations on identified disruptive students) for distinguishing teacher expertise. Our study serves as a pioneering effort in assessing teacher expertise using eye tracking within an interactive virtual setting, paving the way for future research and advancements in the field.

OriginalspracheEnglisch
TitelProceedings - 2023 IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2023
Redakteure/-innenGerd Bruder, Anne-Helene Olivier, Andrew Cunningham, Evan Yifan Peng, Jens Grubert, Ian Williams
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten683-692
Seitenumfang10
ISBN (elektronisch)9798350328387
DOIs
PublikationsstatusVeröffentlicht - 2023
Veranstaltung22nd IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2023 - Sydney, Australien
Dauer: 16 Okt. 202320 Okt. 2023

Publikationsreihe

NameProceedings - 2023 IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2023

Konferenz

Konferenz22nd IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2023
Land/GebietAustralien
OrtSydney
Zeitraum16/10/2320/10/23

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