Mind Wandering Detection Plugin

Project Description:

Remote video-based learning offers vast opportunities but comes with its own set of challenges, notably mind wandering. Defined as thoughts unrelated to the task, mind wandering has a proven negative impact on learning outcomes. Our project introduces a novel approach to mitigate this issue: a web player equipped with video-based mind wandering detection, utilizing only a webcam to analyze learners' facial features for signs of inattention. At the heart of this web player is a pre-trained machine learning model capable of identifying moments when a learner's focus shifts away from the educational content. We employ this tool to investigate the effectiveness of various interventions designed to help learners refocus, such as providing additional explanations or cues to regain attention, with the ultimate aim of improving learning outcomes. This project represents a bridge between technology and cognitive science, offering a practical solution to a common problem in remote learning environments. By understanding when and how learners' mind wanders, we can create more engaging and effective educational experiences.