This article is part of a collaboration between The New York Times and The Chronicle of Higher Education, a daily source of news and opinion for professors, administrators and others interested in academe. Marc Parry is a technology reporter for The Chronicle.
CAMPUSES are places of intuition and serendipity: a professor senses confusion on a student’s face and repeats his point; a student majors in psychology after a roommate takes a course; two freshmen meet on the quad and eventually become husband and wife. Now imagine hard data substituting for happenstance.
As Katye Allisone, a freshman at Arizona State University, hunkers down in a computer lab for an 8:35 a.m. math class, the Web-based course watches her back. Answers, scores, pace, click paths — it hoovers up information, like Google. But rather than personalizing search results, data shape Ms. Allisone’s class according to her understanding of the material.
With 72,000 students, A.S.U. is both the country’s largest public university and a hotbed of data-driven experiments. One core effort is a degree-monitoring system that keeps tabs on how students are doing in their majors. Stray off-course and a student may have to switch fields.
And while not exactly matchmaking, Arizona State takes an interest in students’ social lives, too. Its Facebook app mines profiles to suggest friends. One classmate shares eight things in common with Ms. Allisone, who “likes” education, photography and tattoos. Researchers are even trying to figure out social ties based on anonymized data culled from swipes of ID cards around the Tempe campus.
This is college life, quantified.
Data mining hinges on one reality about life on the Web: what you do there leaves behind a trail of digital breadcrumbs. Companies scoop those up to tailor services, like the matchmaking of eHarmony or the book recommendations of Amazon. Now colleges, eager to get students out the door more efficiently, are awakening to the opportunities of so-called Big Data.
The new breed of software can predict how well students will do before they even set foot in the classroom. It recommends courses, Netflix-style, based on students’ academic records.
Data diggers hope to improve an education system in which professors often fly blind. That’s a particular problem in introductory-level courses, says Carol A. Twigg, president of the National Center for Academic Transformation. “The typical class, the professor rattles on in front of the class,” she says. “They give a midterm exam. Half the kids fail. Half the kids drop out. And they have no idea what’s going on with their students.”
As more of this technology comes online, it raises new tensions. What role does a professor play when an algorithm recommends the next lesson? If colleges can predict failure, should they steer students away from challenges? When paths are so tailored, do campuses cease to be places of exploration?
“We don’t want to turn into just eHarmony,” says Michael Zimmer, assistant professor in the School of Information Studies at the University of Wisconsin, Milwaukee, where he studies ethical dimensions of new technology. “I’m worried that we’re taking both the richness and the serendipitous aspect of courses and professors and majors — and all the things that are supposed to be university life — and instead translating it into 18 variables that spit out, ‘This is your best fit. So go over here.’ ”
ALERT! YOU ARE OFF-TRACK
EVER since childhood, Rikki Eriven has felt certain of the career that would fit her best: working with animals. Specifically, large animals. The soft-spoken freshman smiles as she recalls the episode of “Animal Planet” that kindled this interest, the one about zoo specialists who treat rhinos, hippos and giraffes. So when Ms. Eriven arrived at Arizona State last fall, she put her plan in motion by picking biological sciences as her major.
But things didn’t go according to plan. She felt overwhelmed. She dropped a class. She did poorly in biology (after experiencing problems, she says, with the clicker device used to answer multiple-choice questions in class). Ms. Eriven began seeing ominous alerts in her e-mail in-box and online student portal. “Off-track,” they warned. “It told me that I had to seek eAdvising,” she says. “And I was, like, eAdvising?”
Read more at https://www.nytimes.com/2012/07/22/education/edlife/colleges-awakening-to-the-opportunities-of-data-mining.html?ref=education