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College 2.0

The Netflix Effect: When Software Suggests Students’ Courses

By Jeffrey R. Young April 10, 2011
Tristan Denley, of Austin Peay State U., hopes his course-picking software will “open students’ eyes to courses that they were dimly aware of.”
Tristan Denley, of Austin Peay State U., hopes his course-picking software will “open students’ eyes to courses that they were dimly aware of.”Joshua Anderson for The Chronicle

When Netflix suggests movies based on how much previous renters liked them, all that’s at stake is a night’s entertainment. Now a handful of colleges have begun using similar recommendation systems to help students pick their courses—a step that could change GPA’s and career paths.

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When Netflix suggests movies based on how much previous renters liked them, all that’s at stake is a night’s entertainment. Now a handful of colleges have begun using similar recommendation systems to help students pick their courses—a step that could change GPA’s and career paths.

Last week, undergraduates at Austin Peay State University were invited to visit its new online recommendation system before meeting with their academic advisers. When suggesting a course, the automated system considers each student’s planned major, past academic performance, and data on how similar students fared in that class. It crunches this information to arrive at a recommendation. An early test of the system found that it could lead to higher grades and fewer dropouts, officials say.

Human academic advisers usually don’t get five stars from students. The quality of course recommendation at colleges is often about as reliable as the level of movie advice you’d get at the local video-rental store (if you can still find one). Sure, some clerks are film buffs—Quentin Tarantino first worked in a video store, after all—but you can’t count on it. Many professors who help students plan their academic schedules have limited knowledge of courses outside their discipline.

In contrast, colleges themselves have vast hard drives filled with data about academic requirements and student performance.

That makes the advising process a natural area to try a more analytical approach to student services. If it works there, the number-crunching techniques and suggestion engines could be put to other purposes as well, pointing students toward majors, activities, and campus resources.

Call it higher education’s Netflix Effect.

I have also heard worries—not surprisingly, from those same professors—that students may interpret the suggestions from the software robot as commands, and miss the more creative ideas that they say are more likely to come out of a free-flowing discussion.

Absent Advisers

Margaret Suddarth, a junior majoring in business at Austin Peay, in Clarksville, Tenn., says she has seen her academic adviser only once in her time at the university, even though they are supposed to get together to talk about her schedule every semester. “He’s hard to catch up with,” she says.

Her usual ritual is to flip through the course booklet on her own, then call or e-mail her adviser with her plans. He approves them and gives her a code number required to register.

The new software robot, on the other hand, is available anytime, and its ideas seemed on target to her. “The suggestions were all good,” she says.

For the coming semester, the program advised her to take a course in management-information systems, which reminded her that she could do that to get a requirement out of the way. It even predicted she would get a good grade.

Tristan Denley, Austin Peay’s provost and a former professor of mathematics who designed the course-picking software, says he tested it using students’ performance from past semesters. Those who took the courses the software recommended, he found, earned GPA’s that were half a point higher than those who chose courses not suggested by the program.

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One possible reason for the difference, he says, is that students sometimes take advanced courses before they are ready, whereas the system can guide them to material closer to their level. In some cases, he argues, it might even guide them to subject matter they have a propensity for but may not have realized.

To me, the software robot —which in the online system is represented to students as suggestions from the university’s mascot, a monocled figure called the Gov, seemed as if it could guide students to “gut” courses rather than challenging ones.

“I don’t think the major thrust will be to push people to classes that are sort of easy A’s,” argues Mr. Denley. “I hope the major effect will be instead to open students’ eyes to courses that they were dimly aware of.”

David Major, chairman of the Faculty Senate and a professor of languages and literature, confesses to being “a little nervous” about the system when he first heard about it. But so far he does not see it elbowing humans out of the process. “I haven’t heard any grumbling” among other faculty members, either, he says.

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The reality is that students already go online to help pick their courses. For years many have turned to unofficial online forums such as Rate My Professors, where students anonymously describe professors whose courses they’ve taken, including how strictly they grade and even how attractive they are.

Professors say they like that Austin Peay’s system recommends courses, not professors, basing its decisions on content rather than teaching style.

Ms. Suddarth, the business major, uses both the official system and Rate My Professors to design her schedule, though she says her goal is to find the best teacher, not the easiest.

Mr. Denley hopes his software program will have an impact on retention. Specifically, it may help some scholarship students keep their GPA’s high enough to maintain their awards. “The loss of those scholarships for some students means they are no longer able to carry on with their degrees,” he says.

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If his calculations work, the number-crunching provost hopes to add a tool to help students choose their majors as well. If that sounds like too personal a decision for software, remember that these days, many people use online dating services to find their spouses.

As Mr. Denley puts it, “if eHarmony works well, why not this?”

‘Personal Connections’

The University of Colorado at Boulder, however, which also added online course-picking tools in the past few months, got a lesson in the importance of old-fashioned advising.

Boulder set up an online service to help students plot course plans to satisfy their majors, though it doesn’t make suggestions.

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One goal of building the online guide was to fight what Michael C. Grant, associate vice chancellor for undergraduate education, says is the mistaken impression that the university wants students to stay extra semesters to take just one stray course, one that probably would have fit into a previous term with proper planning.

“That perception is a big problem for us,” he told me. The online tool makes it clearer to students what they need to take to stay on track.

But a recent survey at the university found that despite the online information, students are seeking personal advising more than ever. It continues a trend at Boulder in which 115,000 contacts between students and advisers were reported in the 2008-9 academic year, compared with 70,500 in 2005-6.

“It’s clear that the students oftentimes have pretty personal connections with their advisers, and most of the time those are very positive,” Mr. Grant says.

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The Netflix Effect, though, suggests that a little number crunching can still be a powerful force.

Some two-thirds of movies rented on Netflix result from recommendations made by the site, and users rate recommended films half a star higher than those they find on their own. That’s according to the book Super Crunchers: Why Thinking-by-Numbers Is the New Way to Be Smart.

I asked the book’s author, Ian Ayres, a Yale Law School professor, why he trusts machines with such personal decisions.

He says humans tend to have blind spots when handling tasks like advising, which involve complex systems. People often give too much weight to certain details based on personal preferences.

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The question, from his point of view, is why colleges haven’t done more quantitative experiments to test their own educational and business practices. In a column he wrote for Forbes magazine, he challenged elite colleges to admit a few applicants who don’t meet admission criteria, so the colleges can track whether the students really perform more poorly than other students do. No one has tried it.

“It’s kind of perplexing that they have this unvalidated reliance” on tradition, Mr. Ayres says. “We’re willing to do randomized testing on drugs, where people’s lives are at stake, but we’re not willing to do it with people’s education.”

At another college system that set up a course-recommendation tool, the South Orange County Community College District, in California, leaders compare educational data with baseball statistics and note that colleges are getting more sophisticated in how they measure success, just as Major League Baseball has over the years.

“Right now this is kind of a zeitgeist thing,” says Robert S. Bramucci, vice president for technology and learning services. “We’re starting to see a lot of independent efforts to improve analytics.”

We welcome your thoughts and questions about this article. Please email the editors or submit a letter for publication.
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Portrait of Jeff Young
About the Author
Jeffrey R. Young
Jeffrey R. Young was a senior editor and writer focused on the impact of technology on society, the future of education, and journalism innovation. He led a team at The Chronicle of Higher Education that explored new story formats. He is currently managing editor of EdSurge.
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