A growing number of colleges and universities are using what is known as predictive analytics to spot students in danger of dropping out. Crunching hundreds of thousands and sometimes millions of student academic and personal records, past and present, they are coming up with courses that signal a need for intervention. First year students at U-M began using a tool in the fall that mixes their personal and academic data with data on how earlier students did, advice from them and study guides from professors. After students complete a survey about their expectations for success in a course, the program digs into the data to see if those expectations are realistic. When they sign on, it takes them through questions and answers in what feels like a conversation. Tim McKay, the professor of physics, astronomy and education who created the application, called ECoach, said thousands of students who regularly used the application over six years of testing often earned a third of a letter grade higher than those who did not use it.
