Higher Education’s Big (Data) Bang: Part Two


A university recently crunched all of the “Big Data” it had gathered on a course and made a surprising discovery.

big-data
Some in higher education question massive investments in Big Data.

Out of the two professors who taught the course, one had significantly lower performing students. But this was a professor who had won several teaching awards and was well-respected by campus leaders.

What was going on here, the researchers wondered as they sifted through all of the data points at their disposal.

They could only draw one conclusion based on the data at hand: the poorer student performance was because the professor was not the level of teacher everyone believed him to be.

The conclusion, it turns out, was wrong.

This the second part in an eCampus News series about the power and pitfalls of Big Data. Read the first part here.

All the calculations and algorithms failed to point out something most professors now know nearly instinctively: the course was at 8 a.m., and so the class was mostly made up of procrastinators who had waited until the last minute to sign up for the course. Hardly a room full of over-achievers.

“When you have 5,000 data points, how do you know what question to ask?” said Sherry Woosley, former associate director of institutional effectiveness at Ball State University, as she related this real-life incident.

That, she said, is one of the primary concerns as universities and colleges turn to Big Data technology to help make sense of all the information they have accumulated. More than 1,000 institutions are working with Big Data in some way, and universities are investing millions of dollars in super computers and data research centers.

Critics like Harper Reed, the chief technology officer of President Obama’s reelection campaign, warn that universities are being romanced — by adaptive learning platforms or computer companies like IBM — into financially backing what will turn out to be a fad.

Ellen Wagner, executive director of the WICHE Cooperative for Educational Technologies, said while she doesn’t consider the interest in Big Data to be a passing phase, the criticism does help to ground the conversation.

“It’s great to remind us to put on our ‘reality glasses,’ to remind people that they need to be paying attention to the hype permeating this space right now,” Wagner said. “It’s really easy to talk about the ‘Amazonification’ of education. It’s easy to get seduced by what Amazon and these big transaction platforms do, but we have to remember that with education, we’re not talking about the same kinds of aggregated transactions.”

It may turn out that the kind of data gathering that online retailers have used so well for product recommendations may not be so easily applicable to college course recommendations.

Improving student outcomes is just one of many reasons a university may choose in invest in Big Data, however. Woosley said it’s important for a university to know what questions it’s hoping to answer with data before making the kinds of investments seen at Indiana University and the University of Rochester.

A large research university hoping to uncover a common thread in thousands of car accident reports would be utilizing Big Data in a completely different way than a college just focused on helping students graduate. Too much data can be just as useless as not enough.

Or even the same as no data at all.

“People talk about information overload in terms of just email,” said Woosley, who is now the Director of Analytics and Research at EBI MAP-Works. “We’ll see the same thing with data reports. If you’ve given someone too much information, they’ll throw it all out as they don’t even know how to pick through it. There’s definitely a risk here of getting enamored with the phenomenon. Do you as an institution even need this huge data warehouse? The devil’s in the details.”

Mark Milliron, Chief Learning Officer and co-founder of data analytics company Civitas Learning, said those details will decide an institution’s success with Big Data.

Milliron said too many students are “flying blind” as they try to chart their higher education pathways, and Big Data tools are what will help fix that problem.

“However, far too many data strategies end up as little more than expensive edu-voyeurism, focusing high-cost data work on accreditation, trustee updates, or little used reports that essentially watch if students succeed or fail,” Milliron said. “If that’s where the resources go, we doubt folks will see a return on the investment.”

Jim Spohrer, the director of Global University Relation Programs at IBM, said Big Data is something people are just now beginning to understand, so the concerns and skepticism aren’t surprising.

While he said he agrees that not all Big Data technology is for everyone – a community college may not need a supercomputer like IBM’s Watson – he cautioned those who dismiss the explosion in interest as just hype.

“This is a real phenomenon,” he said. “Every job is being impacted by this. It really is time now to make sure all professions have some level of understanding of these tools. That’s what it’s really about, taking smarter actions, helping us make smarter decisions.”

Woosley said Big Data’s role in higher education is not a black and white scenario. There are untold benefits to tapping into the wealth of information now available to universities, but there are some serious pitfalls as well.

The knowledge of those pitfalls could get lost in the noise as the hype machine’s engine continues to rev.

“I’ll admit I am starting to cringe whenever I see the term Big Data,” Woosely said. “It’s becoming this mythical thing, and that’s always scary.”

Follow Jake New on Twitter at @eCN_Jake, and join the conversation with #eCNBigData.

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