Mobile application and data visualization for Sensei : sensing educational interaction in Montessori classrooms

Abstract

Understanding early childhood development can help teachers individualize their methods to facilitate growth in children. The Montessori educational approach emphasizes independence and allows children to guide their own learning. Given this style of learning, a crucial part of this kind of education is observation of the students, so teachers can assist individuals and help address specific developmental needs. Sensei aims to assist this observation through a dynamic range-based sensor network that detects proximity. These sensors are placed on the children's shoes, on lessons, and around the classroom. I developed the mobile application and the visualization dashboard for the Sensei system. Teachers can maintain the sensor deployment in their classroom through a mobile application. This allows teachers to start the sensors in their classroom at the beginning of each day. They can also collect data from the sensors at the end of the day and view an initial graph of the collected data, showing the time they spent with each child. With this unique data set, we also provide detailed visualizations to teachers so they can determine who children are spending their time with, what lessons they are spending time with, and what areas of their classroom are most active. With this data, teachers can, for example, determine the right time to introduce a child to a new lesson or re-arrange their classroom to facilitate learning. These visualizations are easily accessible for teachers in a web application. Sensei helps discover insights for teachers that would have otherwise been lost. This system can help provide a deeper understanding of early childhood development for teachers, educators, and researchers.