Data is more compelling when used to tell a story. So let’s start with one of my favorites.

When it comes to transferring champions, Robert (Bob) Templin is one of the greats. While president of Northern Virginia Community College (NOVA), one of the nation’s largest community colleges, Bob advocated for increased and more equitable opportunities for transfer students. He negotiated programs like Path to the Baccalaureate, designed to catapult students of color from modest means to economic mobility and security. He understood the importance of the transfer, in part because he had been a transfer student and had first-hand experience the transformative power of the journey.

One year, Bob had a special guest at NOVA’s opening ceremony: the new president of George Mason University, NOVA’s main transfer partner. Bob wanted to make a lasting impression about the importance of transferring from community college to university, so he asked the new president to shake hands with every graduate related to Mason. It was an important moment to cement what would become one of the most successful transfer partnerships in the country. A few years later, on the eve of Bob’s retirement from the presidency of NOVA, George Mason returned the favor, welcoming Bob early in college. President George Mason asked graduates to introduce themselves if they had transferred from NOVA. Bob will never forget the thunderous sound of thousands of people standing up, the unassailable symbol of their success, their diversity and their numbers on display for all to see.

What does this story have to do with data? Both presidents knew the power of those gestures because they both knew the numbers.

The most successful transfer partnerships often rely on data to justify the investment, set strategic direction, and create a culture of continuous improvement. Unfortunately, most institutions cannot rely on federal or state requirements to guide the reporting of most basic community college transfer measures. For example, even when states report the results of transfer students, this data is often not available, disaggregated by race, ethnicity or income. Leaders must invest their time, influence and resources to activate the internal processes, infrastructure and capacity necessary to obtain this fundamental information.

The level of investment may differ: assign staff to create a manual patchwork of data from different institutional or state sources, hire vendors to organize master data, or enter into a major data-sharing deal with dashboards. high-tech between transfer partners. To help guide these investments, at the Aspen Institute College Excellence Program, we synthesized four ideas from our Tackling Transfer report on the evaluation of the transfer:

  1. Know the basics: How many of your students are current or potential transfer students? How many transfer and / or diploma with a baccalaureate? How long does it take and how much does it cost to get their degrees? How much of your enrollments and completions depend on transfer channels? Where are there inequalities based on race and ethnicity, income, or other student subpopulations? Every community college and university leader should have the answers to these questions.
  1. Set goals and use them as a framework for auditing transfer data needs: According to the leaders and practitioners we have worked with, sometimes the challenge with transfer data is that the data is not collected. For example, some community colleges do not ask for the bachelor’s degree, while some universities do not include key credentials for students transferring to community college in their student information systems. Even when data is not yet available, setting longer-term transfer goals can provide a useful framework for institutional research analysts to understand whether their own data collection, entry and storage systems institution would support the evaluation of desired outcomes. Examples of state-level goals can be found in this report.
  1. Turn student experiences into data transfer: Qualitative data from focus groups and surveys specific to transfer students provide essential information about the experiences of transfer students. Qualitative assessment is essential for interpreting outcome data and how it relates to transfer practice and policy.
  1. Create spaces for key stakeholders to interact with the data: This step is too often underestimated. Leaders need to invest in creating structured, routine places where staff, faculty, and counselors – both within and across partner institutions – can examine and connect data on the success and equity of transfer students. to practice reform. Benchmarking this data against clear and measurable targets suggests that transfer practices and policy reform will be data-driven. These routines are essential to a continuous improvement mindset.

A final idea is to use the transfer data to tell transfer stories, like the one I started with. We don’t have to look far to find stories of transfer students using their talents in extraordinary ways or find stories of transfer students getting trapped in the complexity of systems not designed for them. Both sides must be informed. The data shows that these are not random anecdotes; these stories belong to The 8th0 percent to enter community college students who want a bachelor’s degree. If anyone needs to be convinced, ask the transfer students in your class to stand up. You probably won’t be able to count them, so make sure your team has collected the data.

Tania LaViolet is Director of the Aspen Institute College Excellence Program.