The ability to write programs that execute efficiently on modern parallel computers has not been fully studied. In a DARPA-sponsored project, we are looking at measuring the development time for programs written for high performance computers (HPC). To attack this relatively novel measurement problem, our goal is to initially measure such development time in student programming to evaluate our own experimental protocols. Based on these results, we will generate a set of feasible experimental methods that can then be applied with more confidence to professional expert programmers. This paper describes a first pilot study addressing those goals. We ran an observational study with 15 students in a graduate level High Performance Computing class at the University of Maryland. We collected data concerning development effort, developer activities and chronology, and resulting code performance, for two programming assignments using different HPC development approaches. While we did not find strong correlations between the expected factors, the primary outputs of this study are a set of experimental lessons learned and 12 wellformed hypotheses that will guard future study.