This article reports that several colleges and universities like Purdue University are mining data they have about students to try to improve retention. The institutions analyze years' worth of data on which students did well and which did poorly, and what variables--whether they be SAT scores, financial-aid status, or attendance at the dining halls--correlate with those successes or failures. Using those data, colleges try to predict which students are likely to drop out--and intervene before the students themselves even know they're in trouble. At Purdue the risk algorithm, which predicts when students are at risk of failing, is based on academic variables like GPA's and standardized-test scores, as well as how often students log into the course site. Students who have some combination of poor preparation and slack engagement with the Web site will see the red or yellow light on the course-management system and will also get a warning by e-mail asking them to meet with an instructor or seek outside help.