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At risk? The algorithm knows

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Georgia State has boosted its graduation rate and eliminated the graduation gap for blacks, Latinos, first-generation students and low-income students. Among other things, the university uses predictive analytics to keep student on track for graduation, report Jill Barshay and Sasha Aslanian on the Hechinger Report.

Georgia State’s student newspaper, The Signal, reported on data monitoring in April. Many students didn’t know their risk of dropping out was being monitored.

Analyzing data on who’s at risk and who’s doing fine is catching on at less-selective colleges, they write. But some say it invades students’ privacy, discourages exploration and disproportionately encourages disadvantaged students to choose easier majors.

Keenan Robinson, who’s black, started Georgia State as a nursing major.  In the second semester of his first year, he learned that the school’s computer algorithm had flagged his 3.0 average as too low get into nursing, which requires a 3.5. He was more likely to succeed as a respiratory therapy major, the data suggested. He switched his major.

“I have asthma,” he said. “I know both my grandparents on my mother’s side had lung issues. And once it kind of clicked, it was something I wanted to do.”

. . . the university’s data analysis showed that many students who didn’t get into the nursing major ultimately dropped out of college because they had wasted their first two years taking prerequisites that didn’t count toward another major. It was critical to steer these students — many of them with above average grades — to something else early in their college careers.

The dropout rate is enormous, especially at less-selective colleges. “Nationally, only about half of students who start college actually earn degrees,” write Barshay and Aslanian. “Many drop out mired in debt and lacking earning power . . .  often worse off than if they’d never gone to college.”

However, “in 2016, after years of declines, national college graduation rates started ticking back up again and have continued rising for the past three years,” they write.

Critics of predictive analytics see downsides.

They worry about invasion of privacy and surveillance of students. And they say that the algorithms might be reinforcing historical inequities, funneling low-income students or students of color into easier majors. There are also fears that the data could unintentionally discourage students and prompt some who might have otherwise stayed in school to drop out.

In 2006, only 18 percent of black males at Georgia State earned a degree; the white graduation rate was 32 percent. The university added advisers, armed with analytics, and tutoring to raise its overall graduation rate by 23 percentage points.


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