The Data Subcommittee of the CAPCSD Admissions Committee is pleased to announce the launch of the CSDCAS Open Data Initiative.

The participation rate of programs using CSDCAS has increased over the past years such that now a majority of both SLP and AUD programs use this service as their primary method for obtaining applications to their graduate programs. One of the requirements of using CSDCAS is the agreement to input “final disposition” data at the end of the admissions cycle, which has the potential to  provide national insight into admission trends. Because CSDCAS is used nationally, this dataset can provide us with information regarding rates of acceptances or denials, for example, or information about diversity of the applicant pool on multiple dimensions.

CAPCSD/CSDCAS recently published the first summary data report for the years 2017-2018, while simultaneously presenting these data at the 2019 CAPCSD conference. Learning about the data increased general interest in CSDCAS, in addition to conversations and discussions about trends that are now available to be examined with this dataset.

CSD admissions have worked through challenges over the years, including receiving considerably more qualified applicants than there are spots in programs. The seemingly competitive landscape of admissions in our fields has led to messaging particularly around high achievement on metrics such as GPA and GRE scores, while also encouraging students to participate in as much volunteer and leadership work as possible. These messages may or may not be indicative of the trends seen in the national data, which is now available for examination.

The goal of the initiative is to provide a mechanism for faculty (and their trainees) at CAPCSD member institutions to conduct research using the rich dataset provided by CSDCAS. In doing so, we aim to jumpstart a more rigorous understanding of the graduate admissions process in the CSD fields, which will ultimately support data-driven solutions to admissions challenges.

We have aimed to make the data set as transparent as possible while also protecting applicant and program anonymity. All applicant data is deidentified and there is no program data. To promote anonymity, some demographic information is reported in binned (e.g., age) or binary categories (e.g., economically disadvantaged) instead of more fine-grained categories. A full description of the dataset is provided in the codebook. We welcome feedback from the community regarding potential edits or additions to the nature of the open CSDCAS data set to the extent that modifications could be made while also continuing to ensure applicant and program anonymity.