Students worry predictive analytics will restrict their choices

Experts say they help them make more informed choices

Predictive analytics in education can pinpoint "at risk" students who may need a little extra attention. The idea goes like this: if a student has any red flags in academic performance or otherwise, advisors and faculty can swoop in and help them get to where they need to be to receive their degree. 

But some students fear the tools will change the way advisors interact with them.

Speaking at EduCon 2.9 last month, a panel of students said they "worry that the data will be used to label them before they have a chance to make their own impressions on a teacher," Nichole Dobo reports for the Hechinger Report.

Specifically, the students expressed concern that analytics tools:

  • Will write them off as failures;
  • Would let one bad grade haunt them;
  • Will restrict their academic choices; and
  • Make their teachers view them as numbers from an algorithm, not a person.

Students aren't inclined to trust the data, Dobo writes, partially because they aren't able to view it. Students also note that the algorithms don't have the power to take external context into consideration when evaluating specific students' records.

After refocusing their advising efforts, one university retained 400 additional students

"Bad grades one semester might not be predictive of academic ability if, for example, [the student was] failing because of a problem outside of school," Dobo writes. 

Ed Venit, senior director at EAB and expert on the use of data analytics in advising, says he can see why students are wary.

"Today's students are no strangers to data analytics—after all, Google is roughly as old as they are—so it is understandable that they would be concerned that their data would be used against them," he told the EAB Daily Briefing.

But, he explains, there's nothing inherently nefarious about data analytics.

"Analytics are just another tool in the toolbox," Venit says. "Everything hinges on how the tool is used. And the vast, vast majority of faculty and other higher education professionals want to use analytics to help their student succeed, not to tear them down" (Dobo, Hechinger Report, 3/1).


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