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article imageQ&A: Why higher education needs data analytics Special

By Tim Sandle     Feb 6, 2019 in Technology
Many universities still are not embracing data analytics, and are instead making huge decisions based not on data, but on their gut or historical trends. Yet data analytics can assist with an array of higher-ed services.
The impact of not collecting and analyzing data limits the student success rate and has implications for finance departments. The biggest risk is heading off a financial cliff and not knowing it, in the absence of data-informed decisions. In contrast, data analytics can help universities to recruit students and to plan finances effectively.
To understand how data analytics can assist the higher education sector, Digital Journal spoke with Jenzabar Analytics Product Manager, Meghan Turjanica.
Digital Journal: Are schools and colleges making good use of data analytics?
Meghan Turjanica: Some schools and colleges are definitely making good use of data analytics – they have become thought leaders and are proactive. Typically, they are the larger schools that have basically funded an entire analytics department. They recognize that institutional research and reporting are not the same as analytics and are doing some really great things.
That being said, most institutions are not leveraging all that they could. They are small to midsize schools and do not have resources to hire and maintain departments dedicated to answering strategic questions. Many are overwhelmed and bogged down on institutional reporting needs.
I think you'll find that for-profit schools are better at it because they are more business model-driven whereas non-profit schools can't agree on using the term business model or may not think of themselves as a business.
DJ: Why are data analytics not being utilized fully?
Turjanica: There are two primary reasons why data analytics are not being fully utilized. First, many institutions do not have the manpower or talent. Data science and scientists are a hot commodity right now. Many times when an institution finds staff that have the right skillset, they can't keep them.
Second, the institutions themselves are conservative. If you think about American higher education today, it's built off of a couple of different models from centuries ago. It's actually amazing if you look at some of the first writings about students in history at universities in Europe. For example, in Hutchins’ 1936 book Higher Learning in America, they talk about students the same way that we talk about them now. We’re at a point where disruption is going to happen. But for the institutions themselves, making that jump is really difficult for them. It’s a cultural change.
Think about data science. With the advent of what we can do with cloud and spark processing, data science has rapidly changed from a difficult manual process to this almost automated process. Institutions are slow to change.
DJ: What is the impact of this on students?
Turjanica: The biggest issue that remains is that higher education is still doing everything the same way they’ve always done it. So even though the context has completely changed, institutions are not reevaluating what type of students are going to college and what programs they are choosing. We're still lecturing. We know that people don't learn very well in lecture. Professors are still writing out grades by hand. They're giving a midterm final and a final paper even though we know the data says that's not the best teaching strategy.
A really big part of the data impact is how to appeal to today’s students - how are we delivering courses, which courses, what teaching strategies are working, and which are not. Not many institutions are making decisions or changes based on what is working and the data. With the data, we can be sure students are getting the most out of their education and their investment in college. So for example, we know that academically relevant engagement is huge. Learning communities have a tremendous impact on students actually getting something out of their education but almost no institutions are employing this regardless of what the data says.
DJ: How is this impacting the overall health of the institution?
Turjanica: Colleges have been having difficulty focusing on finances in a strategic way. It’s become clear that most make decisions without the data to show how their decisions impact the bottom line. For instance, some may make a decision or launch a new program with high costs but without any data showing a return on investment. Institutions have a terrible time just deciding what programs to cut, expand, or transform.
Analytics also can help institutions figure out how to retain students instead of spending so much money on recruiting new students. Having a student drop out of school after spending thousands of dollars for that student? What a waste for everybody.
DJ: What advantages can data analytics deliver for higher education?
Turjanica: The advantages that data analytics can provide are limitless – everything from which students we choose to recruit and how we best support them to ensuring that we’re helping them achieve actual outcomes. These advantages can now be answered by looking at the data. Even what to teach students. That's a pretty big decision that needs to be made and many times these curriculum choices are made just on the basis of history and tradition. So by analyzing data, institutions can now deliver courses in a way that our students are able to learn, delivering topics that are relevant to their life and are inspiring.
We now can further help move that needle on student success, making them successful while at school but also for their career and success.
Higher ed has a wonderful mission statement , but now they can make strategic decisions based on their objectives – to educate the student for a specific outcome. The data not only helps inform us but also allows us to go after our goals in a strategic way. It is revolutionary for higher ed.
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