When Software Suggests Students' Courses

Post date: Apr 13, 2011 11:25:0 PM

 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.

Jeffrey R. Young