Data-driven practices and policies can help provide transparency, clarity, and accountability to remove ambiguity around service, recognition, and evaluation.

Through the use of the Workload Tool, we will focus on collecting quantitative data concerning both the more visible, traditional teaching and service loads and those that tend to be more hidden to create greater transparency on workload inequities, especially as they apply to intersectionality. Women and underrepresented minority groups tend to be more disadvantaged in unclear, foggy environments.

These data will be used to highlight likely roadmaps of success for WSU women STEM faculty in line with what other NSF ADVANCE institutions have discovered. WSU GEARS will be mindful of shedding light on unequal service workloads, while taking into account the larger contexts of size of department, type of service work, and distribution across ranks. Our analysis will build on and be consistent with those used at successful NSF ADVANCE institutions (e.g. University of Maryland, University of Massachusetts-Amherst) that have relied on the limited teaching and service data available from faculty annual reporting.

History:

As part of the WSU 2006 NSF ADVANCE Partnerships Program ESCALATE (NSF Advance Award #: 0620013), co-Pl Yaprak developed a tool for her faculty as Chair of the Engineering Technology Division to collect information on teaching and service workloads. Yaprak’s faculty complete this fillable spreadsheet and return it to her on an annual basis, a step up from information requested on what tends to be a more “visible” service, available from typical annual reports required at most public universities. Using data extracted from these spreadsheets, she created greater transparency on workload inequities in teaching and service assignments within her department. As part of WSU GEARS, in 2020-2022, we piloted this workload tool to a larger subset of WSU STEM departments. 

In Year 1, WSU GEARS invited departments to participate in the Workload Equity Pilot Project. 11 departments participated in the project. We will share findings and raise awareness of potential areas of workload inequities within and across departments.