In May 2017, the CSU Student Success Network convened, and Fresno State hosted, a one-day meeting focused on data use. The convening drew participation from teams of faculty and staff from ten CSU campuses. Afterwards, the team from CSU San Marcos (CSUSM) decided to create a data fellows program to improve their campus’ capacity to use data in decision-making. This is their story of why—and how—they created their program.
In examining the common attributes of institutions with unusually strong performance in measures of student success, George Kuh and his co-authors highlight the importance of “positive restlessness,” an attribute that allows these institutions to “stay focused on the quality of [their] work and its impact on students and institutional performance” (Kuh, Kinzie, Schuh, & Whitt 2010, p. 146). Developing a shared sense of positive restlessness on university campuses requires a real commitment to data-informed decision making across all roles: a practice not just of collecting and reporting data but also of using those data to understand challenges and guide decisions. To support this kind of practice, campuses need to build their capacity for data use and access focused on student learning and success.
Building capacity is not only about technology and server space, or about data analysts who can crunch numbers. As demand for data increases, so does the need for data literacy: the ability to collect, manage, evaluate, and apply data effectively. The evolving nature of data in higher education requires that data literacy skills and knowledge no longer be limited to institutional research offices and must instead be distributed throughout modern campuses, so that every unit at every level can contribute. As the Association for Institutional Research (AIR) has suggested, institutional research professionals have an opportunity to champion this effort by “coaching and professional development of employees across the institution in a purposeful and intentional process that increases capacity for data-informed decisions” (Swing & Ross 2016, p. 12).
The need for this kind of capacity building across the CSU became evident to our team at the May convening. In response to a survey, over 95% of participants at the meeting said they agreed that using data to support student success was a “high priority” on their campus, but only about half agreed that their campus “regularly uses data to inform key decisions at all levels.” At CSUSM, Institutional Planning and Analysis and the Office of Undergraduate Studies have experienced first-hand the need to build data literacy. Requests for data have increased exponentially and the data have become increasingly complex as we collect more information about students. On the ride home from Fresno, we discussed how to help staff and faculty make sense of all that data. From that discussion, the CSUSM Data Fellows program was born.
Through our cohort model, our Data Fellows bring their unique experiences and perspectives to each discussion, a process that enhances each other’s learning and hopefully builds a stronger network of data-literate decision makers across campus. We try to make each session as hands-on as possible, intentionally designing a curriculum that is accessible, engaging, and useful. One method we focus on is providing key terms for each session, explicit definitions of words and phrases that we as data analysts tend to throw around. For example, the word retention is used in multiple ways on a college campus; if our Fellows can settle on and then propagate a common definition for CSUSM, we would be able to reduce confusion and promote more meaningful conversation about the topic.
Our pilot cohort will conclude in March 2018, and we have already learned a great deal for next year’s implementation. For example, this program is relatively low-cost, but we have found that developing the curriculum requires a significant time commitment and that adapting it to an audience with a very wide range of skills and prior experience with data is challenging. A key benefit for us as data analysts, however, is a better understanding of the practical needs of faculty, staff, and administrators in using data. That is, these sessions serve as two-way streets: we are now more experienced in viewing data literacy from the perspectives of our Data Fellows and the challenges they face in seeking to make data-informed decisions.
We understand that this kind of data literacy project might look different on different campuses, but we think it is critical to work on the challenge of data literacy across the CSU. CSU Northridge and Cal Poly Pomona, for example, have instituted similar projects with a distinct faculty focus, providing faculty with access to data to improve instruction, support students, and address other issues. Through sharing information about these kinds of programs, we can support each other in building cultures of inquiry focused on helping our students succeed.