Exploring Dual Eye Tracking as a Tool to Assess Collaboration

Abstract

In working towards unraveling the mechanisms of productive collaborative learning, dual eye tracking is a potentially helpful methodology. Dual eye tracking is a method where eye-tracking data from people working on a task are analyzed jointly, for example to extract measures of joint visual attention. We explore how eye gaze relates to effective collaborative learning and how analysis of dual eye-tracking data might enhance analysis of other data streams. In this chapter, we identify three broad areas of analysis where dual eye tracking may enhance understanding of collaborative learning processes: (a) how eye gaze is associated with other communication measures, (b) how eye gaze is associated with features of the task environment, and (c) how eye gaze relates to learning outcomes. We present analyses in each of the three areas through joint visual attention, using a dataset of 28 fourth- and fifth-grade student dyads working on an intelligent tutoring system for fractions. By combining eye tracking, dialogue transcripts, tutor logs, and pre/post data, we show the potential of using dual eye tracking to better understand the collaborative learning process.