Yesterday I spent some time on my campus advising students as they enrolled in their fall courses. This is alternately an exhilarating and frustrating experience: some students are so excited to get started in college that every task is a pleasure. But others struggle with the process, unsure of their majors and their interests. They get confused, feel pressured, and their whole college experience starts off on a negative note.
For those students, the agony of course selection may soon be a thing of the past. One new trend emerging on college campuses is the use of data mining to guide students toward courses and careers that are “appropriate” for their abilities. As profiled in The Chronicle of Higher Education, schools like Arizona State University have enrolled their students in computerized degree-monitoring programs that monitor student coursework, warn them when they are not doing well in classes, and suggest that they change majors if they do poorly in a course. This is meant to ensure that students will succeed in courses that are “right” for them and make it through a degree program all the way to graduation.
Positive Ways This Can Change Higher Education
The use of data mining to steer students toward their strengths may be a positive development in terms of graduation rates. According to The New York Times, Complete College America reports that graduation rates have remained low despite higher enrollments. This is a problem at every kind of college. For example, community college graduation rates are very low, as “less than half of students who enter a community college graduate or transfer to a four-year college within six years.” Not only are low graduation rates a problem for individual students, who get stuck without a degree and student loans they can’t pay back, they are also an issue of national strength. The United States currently ranks only 16th in the world for the number of college graduates among its citizens, which means that many nations are outpacing us in terms of educational accomplishment. That deficit affects our technological, scientific, and economic strength. If data mining can help students complete their degrees successfully by assisting them in finding the best program for them, it may solve numerous problems.
Drawbacks of Data Mining for Student Choice
Despite the potential benefits of such data-driven educational programming, some potential concerns need to be considered. For example, University of Wisconsin Assistant Professor Michael Zimmer told The Chronicle of Higher Education, “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.’”
Zimmerman raises an important point, one that is related to another concern: Will all challenge be lost if we cater only to student strengths? How will students develop new strengths? Using data mining to direct students only toward what they do well may result in an education that only reinforces a limited skill set and does not allow them to challenge themselves, meet the challenge, and then enjoy the pride that comes with accomplishment. To a certain extent, college should present students with challenges, because that is the only way students can grow. Future employers in any field will expect them to rise to the occasion when faced with a challenge, and we need to prepare them for that.
In addition, the use of data that discounts student desire may be successful in terms of graduation rates, but catastrophic in terms of personal happiness. One of the great benefits of the college experience is that it can be a time when students can uncover unsuspected abilities or even discover their passion. I’ve dealt with many students who have entered college determined to major in one area, do well in it, and are absolutely miserable. Would the data still indicate that they should remain in that major? Data cannot indicate emotional or personal satisfaction. Despite our good intentions, if we rely on data alone, we may be creating a lot of very unhappy people.
That would be a shame. When I was a girl I spent a considerable amount of time daydreaming about my future. At various stages of my intellectual growth I wanted to be a physicist like Marie Curie, a great actress like Bette Davis, and was also pretty sure I had a good shot at becoming the first female President of the United States. All these career paths are of course very glamorous, the typical dreams of a smart young girl with big-even unrealistic–ambitions. They are also all proof of the infinite imagination and unlimited possibilities that all young students should feel and that I certainly relied on.
I would hate to squash that sense of freedom and possibility among students, who should be free to major in what they want, even if it’s not something that the computer says they would score as high in. Data mining to determine student educational choice may work for some students, but it may be unfair to others, whose dreams may need a little more time and hard work to accomplish. Students should feel free to explore their options, and college administrators should be able to support them in this.