‘Data Analytics Can Save Higher Education’, Say Top College Bodies

As state spending on higher education continues to decline and student enrollment falls sharply, data analytics could be a budget booster for universities.

Georgia State University has a proven record of using predictive analytics to improve student retention and graduation rates, and many other higher education institutions are using tools of data analysis to parse student data to figure out who is at risk of dropping a course or flunking out.

These data points can include such things as attendance, Wi-Fi usage, library visits, timely tuition payments and, of course, grades. Schools can give students in need an extra push or nudge them toward a more suitable program of study.

But while these efforts are laudable, they are still small projects, and colleges and universities have failed to follow through on the talk about using Big Data, three noted higher education bodies observed in a recent statement. This failure could negatively affect schools’ bottom lines. 

Consider this: Improvement in student retention alone can earn colleges approximately $1 million annually, according to RPK Group. If universities expanded data analytics to mine the wealth of information at their disposal they could use this data to innovate in student recruiting, institutional efficiency and cost-containment. As state spending on higher education continues to decline and student enrollment falls sharply, data analytics could be a budget booster for universities.

MORE FROM EDTECH: What Can Real-Time Data Analytics Do for Higher Education?

Stakes “Too High” to Not Use Data Analysis

Data analysis “could save higher education,” noted the Association for Institutional Research (AIR), EDUCAUSE, and the National Association of College and University Business Officers (NACUBO) in a joint statement.

The three organizations, which together represent 2,500 colleges and universities, outline six principles that they believe if followed will address some of the institutional, ethical, practical and bureaucratic flaws that beset the analysis of Big Data. They say following their guidelines will accelerate “the meaningful use of analytics and take advantage of the power of data to make the decisions and take the actions that just may save higher education.” 

MORE FROM EDTECH: Colleges Tackle the Retention Problem with Emerging Tech

Big Investments for Big Rewards

Universities need to make substantial investments with not just money but time and talent to effectively mine data, the joint statement says. Equally important, the data needs to be shared institutionwide — analytics shouldn’t take place in silos or be seen as the individual properties of separate offices within an institution. 

Analytics works best when clear, measurable outcomes are targeted. What worked for Georgia State may not work for another college. Alongside making sure these elements are in place, it’s important to ensure that faculty, staff and students develop data literacy skills to effectively parse the data to engender performance improvement in all areas. 

This kind of cohesive strategy can bring in more money for the university, the three higher education bodies noted. 

Be Ethical When Using Sensitive Student Data

While monetary gains from data analytics can be a big draw, the three education bodies say they cannot stress enough that training and awareness among personnel who are mining sensitive student data is crucial. 

Take the Georgia State University example. While there is no doubt the institution has had success using predictive analytics to improve graduation rates, vital questions have been raised about whether the process is reinforcing racial stereotypes, perpetuating inequality and invading privacy at the majority-black university, noted the Hechinger Report. 

Predictive algorithms “might be reinforcing historical inequities, (and) funneling low-income students or students of color into easier majors,” according to the Hechinger Report. A blind pattern hunt from data can seriously risk students’ career and confidence. 

It’s vital to have “a deep understanding of the assumptions underlying the analytic methodologies,” noted the AIR, NACUBO and EDUCAUSE joint statement.

Precautions about ethics, education and expertise aside, the most significant point the associations made is that universities need to get on board with data analytics now.

“For every semester we don’t do everything we can to ensure student success — including using analytics to increase student progress and completion — students leave our campuses without graduating, discouraged and more in debt than when they entered,” the three organizations noted. “The time to act is now.”

Artem Peretiatko/Getty Images Plus
Nov 26 2019

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