  Concerns about representation in computing within the U.S. have driven
numerous activities to broaden participation. Assessment of the impact of these
efforts and, indeed, a clear assessment of the actual "problem" being addressed
are limited by the nature of the most common data analysis which looks at the
representation of each population as a percentage of the number of students
graduating with a degree in computing. This use of a single metric cannot
adequately assess the impact of broadening participation efforts. First, this
approach fails to account for changing demographics of the undergraduate
population in terms of overall numbers and relative proportion of the Federally
designated gender, race, and ethnicity groupings. A second issue is that the
majority of literature on broadening participation in computing (BPC) reports
data on gender or on race/ethnicity, omitting data on students' intersectional
identities. This leads to an incorrect understanding of both the data and the
challenges we face as a field. In this paper we present several different
approaches to tracking the impact of BPC efforts. We make three
recommendations: 1) cohort-based analysis should be used to accurately show
student engagement in computing; 2) the field as a whole needs to adopt the
norm of always reporting intersectional data; 3) university demographic context
matters when looking at how well a CS department is doing to broaden
participation in computing, including longitudinal analysis of university
demographic shifts that impact the local demographics of computing.
