Combining self-reported and automatic data to improve programming effort measurement

Measuring effort accurately and consistently across subjects in a programming experiment can be a surprisingly difficult task. In particular, measures based on self-reported data may differ significantly from measures based on data which is recorded automatically from a subject's computing environment. Since self-reports can be unreliable, and not all activities can be captured automatically, a complete measure of programming effort should incorporate both classes of data. In this paper, we show how self-reported and automatic effort can be combined to perform validation and to measure total programming effort.