Information and digital literacy in education via the digital path

It has been a few weeks since we issued our #DigCiz call for thoughts on the question “What do we owe students when we collect their data?” and there have been a few responses. The call is in conjunction with the interactive presentation at the EDUCAUSE Annual Conference that I’ll be helping to facilitate with Michael Berman, Sundi Richard, and George Station. The session will be focused around breakout discussions both onground and online during the session. We don’t necessarily have “answers” here – the session (and the call) are more about asking the questions and having discussion. The questions are too big for one session and often there are not easy answers; so we released the call early hoping that people would respond before (or after) the session. I’ve yet to respond to it myself so I’m going to attempt to do that in this post.

CHICAGO — Colleges are increasingly using Big Data to monitor students, control their access to information and set them on learning paths they may not have chosen, argues Chris Gilliard, a professor at Macomb Community College, who says the practices add up to “digital redlining.”

“I don’t think education is a predictive task,” said Gilliard, criticizing the use of data systems that allegedly forecast student success or failure. “I’m seeing a whole lot of wreckage in the process that people aren’t considering.”

As college students click, swipe and tap through their daily lives—both in the classroom and outside of it—they’re creating a digital footprint of how they think, learn and behave that boggles the mind.

“We’re standing under a waterfall, feasting on information that’s never existed before,” said Mitchell Stevens, a sociologist and associate professor at Stanford Graduate School of Education (GSE). “All of this data has the power to redefine higher education.”

The 2020 list of EDUCAUSE’s Top 10 IT Issues provides evidence that the higher education IT community is increasingly focused on using technology to better understand students and rethink systems, culture and process to improve student success. This focus is especially critical when it comes to using student data to improve retention and completion rates.

To develop the capabilities and systems that can provide students with personalized, timely support, institutions need to understand how data technology, such as predictive analytics, can address the factors that lead to student success. They also must know how to use information from institutional data to introduce changes that promote sustainable, effective and efficient practices, while considering students’ experiences and needs as their starting point.

As in previous years, it would be quite easy to fill a whole article in this series on “data insecurity,” on the data breaches and cyberattacks that continue to plague education – both schools and software. The issue extends well beyond education technology, of course, and in 2017 we witnessed yet again a number of high profile incidents (including some corporate admissions of breaches that had happened in years past): that over 140 million Social Security Numbers and other personal data had been stolen in a data breach at Equifax, for starters; that every single account at Yahoo – some 3 billion in all – had been affected in its 2013 breach.

Higher ed students believe universities can improve in the next 10 years by tracking their information.