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 group situation, we apply a state-ofthe-art face detector, create face tracklets, and introduce a novel method to cluster faces into the number of identity. Subsequently, teachers' attentional focus is calculated per student during a teaching unit by associating eye tracking fixations and face tracklets. To the best of our knowledge, this is the first work to combine computer vision and mobile eye tracking to model teachers' attention while instructing.

本文介绍了一种利用计算机视觉来增强移动眼动跟踪的影响的新方法，通过将面部检测器和移动眼动追踪相结合，计算了教师在教学过程中对每个学生的注意力焦点，以便在课堂互动的复杂性中识别出学生的相关需求，这是将计算机视觉和移动眼动跟踪结合起来对教师提出关注时的第一次工作。(Translation: This paper presents a novel method to enhance the impact of mobile eye tracking by connecting it with computer vision, calculating teachers’ attentional focus per student during a teaching unit, in order to recognize the relevant needs for learning in the complexity of classroom interaction. This is the first work to combine computer vision and mobile eye tracking to model teachers' attention while instructing.)

教师在课堂上的感知