Thunderbird Data Scholars: Community College Employee Professional Development to Promote Data Literacy and Equity Mindedness

Data use in higher education continues to increase as college and university leaders aim to meet accreditor and governmental expectations to use data to improve student outcomes. However, the steady increase in data use over the past decades has not been accompanied by an increase in employee data literacy in order for employees to use the data effectively. Further, inequitable student outcomes continue to persist in higher education, and more specifically at two-year community colleges, as potentially exacerbated by a lack of employee equity-mindedness. These concurrent problems—inadequate employee data literacy and persistent inequitable student outcomes—provide an opportunity to address both with one intervention. In this critical race, mixed-methods, action research study, I piloted an online professional development course, aimed at community college employees with the purpose to build data literacy and equity-mindedness. I used Bandura’s (1989) Social Cognitive Theory as a guiding theoretical framework paired with a quasi-experimental, delayed-start research design to study the effectiveness of the course in building employee data literacy and equity-mindedness, in addition to better understanding the impacts of environmental factors (i.e., organizational culture) on the implementation of the course. Using pre- and post-intervention surveys, pre- and post-intervention knowledge assessments, and post-intervention participant interviews, I determined that the professional development course contributed to improvements in employee data literacy and equity-mindedness. In particular, the course helped increase employee self-efficacy for data use, increased employee knowledge of data use and equity-mindedness, and increased employee intent to use data in the future. I also found that the organization’s culture related to data and equity to be complex and evolving, both hindering and facilitating data use, in general, and data use specifically, to address inequitable student outcomes.