Colleges urged to ‘save higher education’ with data analytics
“Analytics can save higher education. Really,” reads the eye-catching headline of a bold statement issued recently by three higher education groups serving almost 2,500 institutions across the US.
Many institutions are already investing in edtech solutions and in using data analytics models to boost graduation rates, some turning to predictive analytics to improve student outcomes.
The majority, however, still don’t see it as a priority.
In their statement, the Association for Institutional Research (AIR), EDUCAUSE, and the National Association of College and University Business Officers (NACUBO) said this needs to change.
And if US higher education were to improve and adapt to the needs of today’s digital-first world, that change, they said, must come now.
“We believe higher education must re-energise its efforts and unleash the power of data and analytics across higher education to support students and institutions,” they said.
“We strongly believe that using data to better understand our students and our own operations paves the way to developing new, innovative approaches for improved student recruiting, better student outcomes, greater institutional efficiency and cost-containment, and much more.”
“Data,” they added, “are an institutional strategic asset and should be used as such.”
Data analytics allows institutions to make better, more targeted decisions in all matters, whether that pertains to retention and graduation rates, or recruitment goals.
By studying patterns from historical data, educators are able to draw some relatively accurate conclusions on future outcomes of its students.
Armed with such information, they are able to act instead of react, by rolling out necessary measures to guide a student to success. For example, a student who, based on historical data of others before him or her, is headed towards failure, can be guided to a course where he/she is more likely to graduate with distinction.
In addition, data from tracked results can help inform future strategies and decisions, thus helping the school advance its institutional goals, improve the quality and efficiency of its systems, strengthen student outcomes, as well as enhance teaching, learning and advising.
In a statement to Education Dive, Jonathan Turk, the associate director for research at the American Council on Education, agreed that data and analytics can have transformative effects.
“While higher education leaders are increasingly using data and analytics to better support student success and increase institutional efficiency, there’s still more work to be done.
“We encourage (them) to continue to consider how these strategies can ensure student success at their own institutions.”
Speaking to Diverse Education, NACUBO President and CEO Dr Susan Whealler Johnston pointed out that data analytics was able to ensure that once students are recruited, “they’re not hitting stumbling blocks.”
“Although there are lots of ways data can be used for institutional decision making, most of the focus is on student success.”
An example of its successful application can be seen at Georgia State University. Among the earliest adopters of analytics in the higher education space, the university in Atlanta reportedly used the technology to raise its six-year graduation rate from 32 percent in 2003 to over 54 percent in 2017.
Although critics say there are certain downsides to such stringent use of the technology in terms of data privacy and the right to self-determination, it is quite hard to argue with its benefits, ie. helping institutions keep kids in school.
It must also be reminded that the knock-on benefits of keeping kids in school are that they increase their chances at employment later, which, in turn, opens the door to greater opportunities for a successful future, both for themselves and for their future generations.
Used for ethical means and carefully, educators can ensure to avoid the pitfalls of adopting the technology.
And per what the higher education groups said in their statement, meaningful use of analytics has the power to “save higher education”. It really does.
To drive home their message, they listed six guiding principles for institutions to follow that they say will help them get the most out of analytics.
#1: Go Big: Make an institutional commitment to analytics.
“Make your approach to data analytics transformational and connected to the institutional mission for real results that matter to your students, faculty, and staff.
“Don’t look for a one-size-fits all approach – each institution’s mission, culture, organizational structure, and analytics maturity will dictate the specific next steps.”
#2: Invest What You Can: You can’t afford not to.
“First, make sure the considerable data you already collect are available, shared, and used appropriately.
“Then, if you want to move hard-to-nudge needles like retention and graduation rates, you need to invest in a broader strategy to get the appropriate information in the hands of faculty, staff, and students and to develop the data literacy skills needed to use the information to make smart decisions.”
#3: Analytics is a Team Sport: Build your dream team.
“Establish a team approach with an unrelenting expectation for collaboration across colleges, departments, and divisions of all kinds.
“Give faculty and staff leaders throughout the institution the broad latitude to clear the way for teamwork.
“Analytics data and tools help senior administrators lead institutions effectively but must also be accessible for faculty and staff, empowering those on the front lines who are directly educating and supporting students.”
#4: Analytics has Real Impact on Real People: Avoid the pitfalls.
“Responsible use of data is a non-negotiable priority. To avoid intentional or unintentional misuse of data, investments in analytic tools must be coupled with an institution-wide program of awareness, transparency, and training.
“As your institution develops comprehensive processes, protocols, and skills in the collection and use of data, hold vendor partners accountable at both the procurement and implementation stages.
“Invest time early on to make sure your policies keep up with your implementations, and clarify expectations for data use and protection and for data privacy.”
#5: Prepare for Some Detours on the Road to Success
“Faculty, staff, and senior leaders will all need to see analytics as a long-term commitment, a core part of their day-to-day functions, and a driver for institutional decision making.
“This means each person on your campus—from the cabinet to the bursar’s office and from students to deans—will likely find some aspect of your analytics transformation jarring.
“Expectations must be managed: Aim high, but plan for setbacks, with the understanding that it is okay for some efforts to miss the mark. Learn from the mistakes and move on.”
#6: Tick-Tock, Tick-Tock: The time to act is now.
“A sense of urgency is critical as institutions commit to using data analytics. This urgency needs to come from the institution’s leaders.
“It’s possible to move forward decisively while also listening, collaborating, and building buy-in along the way.
“Whether you are encouraged by the significant opportunities or driven by the need to solve critical problems, it’s time to take a big step forward. Now.”