10.1184/R1/6623441.v1
Janet Siegmund
Janet
Siegmund
Christian Kästner
Christian
Kästner
Jörg Liebig
Jörg
Liebig
Sven Apel
Sven
Apel
Stefan Hanenberg
Stefan
Hanenberg
Measuring and Modeling Programming Experience
Carnegie Mellon University
2014
Software Research
2014-12-01 00:00:00
Journal contribution
https://kilthub.cmu.edu/articles/journal_contribution/Measuring_and_Modeling_Programming_Experience/6623441
<p>Programming experience is an important confounding parameter in controlled experiments regarding program comprehension. In literature, ways to measure or control programming experience vary. Often, researchers neglect it or do not specify how they controlled for it. We set out to find a well-defined understanding of programming experience and a way to measure it. From published comprehension experiments, we extracted questions that assess programming experience. In a controlled experiment, we compare the answers of computer-science students to these questions with their performance in solving program-comprehension tasks. We found that self estimation seems to be a reliable way to measure programming experience. Furthermore, we applied exploratory and confirmatory factor analyses to extract and evaluate a model of programming experience. With our analysis, we initiate a path toward validly and reliably measuring and describing programming experience to better understand and control its influence in program-comprehension experiments.</p>