Teaching analytics: A multi-layer analysis of teacher noticing to support teaching practice

Abstract

This paper, as part of a larger ongoing study, presents the use of a multi-layer approach to analyzing teacher noticing for the improvement of teaching practices. Situated in the field of teaching analytics, the use of multimodal sensors and analytics, especially for teacher noticing research, has provided affordances to discover deep insights for improving teaching practices. We collected data from a case study of one teacher over three lessons of science teaching in a secondary school. Multimodal sensors including an eye-tracking device, a microphone, and multiple video cameras were deployed in a classroom. The various sources of data were integrated and a multi-layer analysis was performed to uncover insights into the teaching practice. The findings show that a novice teacher in our case study was able to attend to events in her classroom, with some interpretations and sense-making of the events; some necessary actions were taken based on the teacher’s analysis but in some instances, necessary action was found to be lacking. Prior knowledge and the wealth of experiences or the lack thereof, together with visual cues in the environment, can affect the decision of novice teachers in executing certain actions in a classroom.