Does “Selective Mapping” Impede Depth and Breadth? A Method for Performing Meta-Analysis on Curriculum and Assessment Maps

ABSTRACT Whereas curriculum maps depict all alignments between a program’s learning outcomes and courses, assessment maps may examine a subset of courses during a given program review cycle, to measure attainment of those outcomes. The purpose of this study was to understand if such “selective mapping” negatively impacts depth and breadth of analysis. Data were collected from 129 maps at a private university in Southern California to answer the research question. A process was created to quantify assessment and curriculum maps for the purpose of meta-analysis. The quantifiable measures that were developed include triangulation breadth (TB), outcomes coverage load (OCL), alignment saturation (AS), and outcome level depth (LD). The findings show that despite selectivity in assessment mapping, the degrees of triangulation, program coverage, and outcome level depth remain robust. The meta-analysis of curriculum and assessment maps also revealed norms and outliers, which can be used to establish “best practices” for mapping.