Abstract
Collecting direct and indirect measures of student learning outcomes is a staple of assessment and accreditation activities, but the problem is that the data are often most meaningful at the program-level but least meaningful at the aggregated department and unit levels. For example, faculty often review student survey responses (indirect measures) and performance assessments (direct measures) on a given outcome and derive a useful indication of how students perceive their own performance against an objective measure of their actual performance. Complexity interferes with this straightforward process of interpretation when separate programs and their measures become compiled at the department and division/college levels. This paper proposes a workable solution to the problem of aggregation, equating measures, and interpreting the results of direct and indirect assessments of student learning outcomes through time-series plotting using the open-source statistical program R and R-Studio.