Teacher's Perception in the Classroom
\"Omer S\"umer, Patricia Goldberg, Kathleen St\"urmer, Tina Seidel,, Peter Gerjets, Ulrich Trautwein, Enkelejda Kasneci

TL;DR
This paper introduces a novel method combining mobile eye tracking and computer vision to analyze teachers' attentional focus on students during classroom instruction, providing new insights into teaching effectiveness.
Contribution
It presents the first integration of computer vision with mobile eye tracking to model teachers' attention in educational settings, improving analysis efficiency.
Findings
Successfully applied face detection and clustering to identify students in eye-tracking videos.
Calculated teachers' attention distribution across students during teaching sessions.
First to connect computer vision with eye tracking for educational research.
Abstract
The ability for a teacher to engage all students in active learning processes in classroom constitutes a crucial prerequisite for enhancing students achievement. Teachers' attentional processes provide important insights into teachers' ability to focus their attention on relevant information in the complexity of classroom interaction and distribute their attention across students in order to recognize the relevant needs for learning. In this context, mobile eye tracking is an innovative approach within teaching effectiveness research to capture teachers' attentional processes while teaching. However, analyzing mobile eye-tracking data by hand is time consuming and still limited. In this paper, we introduce a new approach to enhance the impact of mobile eye tracking by connecting it with computer vision. In mobile eye tracking videos from an educational study using a standardized small…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsGaze Tracking and Assistive Technology · Visual Attention and Saliency Detection · Face recognition and analysis
