DEBE feedback for large lecture classroom analytics

Abstract

Learning Analytics (LA) research has demonstrated the potential of LA in detecting and monitoring cognitive-affective parameters and improving student success. But most of it has been applied to online and computerized learning environments whereas physical classrooms have largely remained outside the scope of such research. This paper attempts to bridge that gap by proposing a student feedback model in which they report on the difficult/easy and engaging/boring aspects of their lecture. We outline the pedagogical affordances of an aggregated time-series of such data and discuss it within the context of LA research.