Using Data to Drive Decision-Making

Recognition of the value data brings to the table is increasing across the higher education space, but the processes behind that are still relatively fresh in this industry. For decades, colleges and universities have been collecting reams upon reams of data, but the end uses for all that data have changed. In this interview, Hadassah Yang shares her thoughts on what it takes to collect and analyze data, and then communicate that data effectively.

The EvoLLLution (Evo): Why has Big Data become so popular in higher education circles today?

Hadassah Yang (HY): In the past, universities collected data mainly to report for accreditation purposes and it was always retroactive or historical data that we were looking at. Now we’re able to look at data to really do predictive analytics and target and personalize student and faculty experiences at the university. That shift from other industries is now moving into higher education

Evo: What are a few of the most important benefits of Big Data that senior administrators should know about?

HY: From a student’s lens, one of the key benefits is that we can do targeted interventions and improve student experiences while they’re at the university and not after the fact. Where we used to look for ways to improve satisfaction for future students, we now try to figure out a solution for those currently enrolled.

As all the research says, if we improve student satisfaction while they’re enrolled in the university, then it’s more likely they’re going to persist and graduate at the university.

Evo: What are some places where predictive analytics can could be leveraged to improve the student experience?

HY: We can definitely leverage predictive analytics to transform the course experience.

Right now, as a faculty member teaching a course, all of the students are at different levels within the course. What Big Data can do, depending on the type of formative assessments that are available on the learning system, is actually start targeting different types of teaching interventions based on the student performance levels in the class.

Evo: On the flipside, what are the limits of Big Data and analytics that senior leaders need to keep in mind?

HY: As an institutional researcher, the first thing is that the data needs to be collected in a high-quality manner. It’s absolutely critical that there is a systematic and high-quality process for collecting data so that faulty data isn’t used to inform any type of decision making that will impact students and faculty. At the same time, it’s also critical to really triangulate all these different data factors and make an informed decision so that not just one specific factor is going to make a decision for all.

The other piece is that kinds of data collected may also be limited in the institution, so I also think it’s important that the senior leadership thinks through what types of answers they’re seeking and what kinds of solutions they’re looking for.

If institutions aren’t getting what they need, they have to looks at ways to start collecting the information that will be most useful.

The last piece is most important because now that there’s more access to data than ever. It’s crucial to make sure that all the correct protocols are in place to protect student privacy and security.

Evo: When it comes to data security and privacy, what are some of the steps that institutions can take to make sure that the data they’re collecting stays safe and is only viewable and visible to people who have permission to view it?

HY: Here at Brandman University every staff member goes through training before they’re provided access to any student or faculty information. When we create dashboards for end users, we work with IT to make sure that the proper security protocols are in place for folks to review the dashboard. Just because you work at Brandman University doesn’t mean you have access to all the information.

Evo: What role does leveraging data play in the effective management of a modern college or university?

HY: There’sa growing movement about this iron triangle of higher education and how can we reduce cost, increase quality and access for students and also serve a higher number of students, all at the same time. What I really appreciate about Big Data and predictive analytics is that it allows us to leverage technology to provide a high-quality education to students while lowering the cost.

Evo: Is there anything you’d like to add about what it takes to really leverage data effectively in the university environment and some of the points that you’d hope senior leaders would keep in mind?

HY: I think it’s important also to think through training staff to not only put high-quality dashboards and data together, but also to interpret data and question data when something seems off, rather than take it at face value. Just like any researcher, it’s important to think through all the possibilities and ensure the integrity of the data that you’re reading before it’s presented to senior staff for decision making.

Evo: How important are strong data visualizations to helping senior leaders understand the outcomes or analysis that the data is trying to provide?

HY: I think data visualization is this broad bucket where, depending on the end user, there’s a variety of ways to do it. In the same way that different students have different learning styles, it’s really about finding the right fit for the senior leadership on visualization.

This article has been edited for length and clarity.