Authors: Sarah Hooshangi, Subhasish Dasgupta, Tara Behrend
Tags: 2018, attitudes, programming, self regulatory theory
Much attention has been given to the fact that women and racial minorities are underrepresented in STEM and computing professions. These gaps begin quite early in the educational pipeline, with differences in achievement and interest reported as early as elementary school. It is important to understand, however, where these gaps come from, in order to identify interventions that can reduce inequalities. This preliminary study seeks to identify the mechanisms that affect programming performance, with the goal that later studies can design and test interventions. We focus on a sample of diverse students who are transitioning from a 2-year college to a 4-year college. We first assess the effects of age and gender on programming performance. We then explore the incremental predictive power of attitudinal and cognitive variables such as goal orientation and technology selfefficacy as possible explanatory mechanisms.
Cite as:
Dasgupta S., Hooshangi S., and Behrend T. (2018). “Mechanisms That Affect Programming Performance,” in AIS SIGSAND, Syracuse, NY, United States, May 23 – 25, 2018.
