Individual Differences in Programming, Testing, and Debugging Strategies in a Statistical End-User Programming Environment," Undergraduate Thesis (2002)
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BibTeX
@MISC{Ko02individualdifferences,
author = {Andrew J. Ko},
title = {Individual Differences in Programming, Testing, and Debugging Strategies in a Statistical End-User Programming Environment," Undergraduate Thesis},
year = {2002}
}
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Abstract
This study intended to investigate two areas of end-user programming: the influence of individual differences on success and whether or not groups of programming, testing, and debugging style would naturally cluster together and provide predictive value. Eighty-six participants, from backgrounds of computer science, psychology, engineering and humanities completed at battery of psychological tests and attempted to complete a timed programming task and testing and debugging task in Stata, a statistical programming environment intended for use by individuals with no programming experience. General intelligence and programming experience were good predictors of programming success. Three types of programming strategies were found: (1) the programmers group used their background knowledge to solve the programming task with little effort; (2) the lost/unmotivated group tended to exhibit repetitive and shallow problem solving; (3) the lost/motivated group tended to search for more information and exhibit more guess and check behavior. There were three types of testing and debugging strategies, but no good predictors of success: (1) the curious/distracted group ignored the task and became distracted; (2) the hesitant/focused group sought little information and
