As part of my morning reading of the New York Times, I ran across an interesting article about ways in which colleges are using hard data to help their students.
With a shocking number of students at public colleges failing to graduate from college in four years (only 31% do) or even six years (only 56%), colleges are looking for ways to help keep their students on the degree-earning path by developing systems that look at student behavior to do things like predict success in a given major, predict courses students would find most useful or have the best chance at succeeding in, or work with students' existing knowledge to help plug in the gaps.
Some key points:
Under Arizona State’s eAdvisor system — in use from 2008-9 and based on a similar effort at the University of Florida — students must pick a major freshman year and follow a plan that lays out when to take key courses. (Students can still study broadly, by choosing from five “exploratory” majors, like “arts and humanities” or “science and engineering,” and staying in them for 45 credits.) If they fail to sign up for a key course or do well enough, the computer cracks a whip, marking them “off-track.” Wander off-track two semesters in a row, and a student may have to change majors.
Something like this makes a lot of sense. I knew a lot of people in undergrad who either did very poorly (or decided they didn't want to continue) in the major they started out in, but it was a while before they ultimately changed majors, delaying the completion of their degree. Some ultimately finished, but many others just disappeared after a while. A system like this may have helped them pick a new path (or at least see that changing paths was a good idea).
AUSTIN PEAY STATE, a midsize university about 45 minutes northwest of Nashville, takes the algorithmic approach to higher education one step further. Before students register for classes, a robot adviser assesses their profiles and nudges them to pick courses in which they’re likely to succeed.
Sounds a little like Pundit, no?
Later in the article, there is discussion of Knewton, the product Arizona State uses in its foundational/remedial math courses. Students place into those courses with various gaps in their skills, and traditional lecture courses tend to be inefficient and produce many drop outs.
What do you think about these systems? They seem to be more of them each year. Do you think they succeed in ultimately helping students? Would you have wanted to have an algorithm telling you what courses to take and when? Would that have been helpful?