Looks can mean achieving: understanding eye gaze patterns of proficiency in code comprehension

Abstract

The research proposes four hypotheses that focus on deriving helpful insights from eye patterns, including hidden truths concerning programmer expertise, task context and difficulty. We present results from a study performed in a classroom setting with 17 students, in which we found that novice programmers visit output statements and declarations the same amount as the rest of the program they are presented other than control flow block headers. This research builds upon insightful findings from our previous work, wherein we focus on gathering statistical eye-gaze effects between categories of various populations to drive the pursuit of new research. Ongoing and future work entails using the iTrace infrastructure to capture gaze as participants scroll to read code pages extending longer than what can fit on one screen. The focus will be on building various models that relate eye gaze to comprehension via methods that realistically capture activity in a development environment.