He wanted to send every student personally relevant information, and it turned out that his colleagues at the School of Public Health had created a tool for doing just that. The Michigan Tailoring System is free software that users can program to send specific messages to selected groups of people.
"The EÂ²Coach system is 'e squared coach,'" says McKay. "That stands for 'expert electronic coach.'" Since fall 2012, his students have been invited to sign up for the system at the beginning of the semester. They take a short survey that explores their goals, their experience in previous physics classes, and whether they believe they're good at physics.
"We're trying to work on helping them understand what they have to do as a student," McKay says. Throughout the course, students can log on to a personalized website that offers encouragement and study tips based on their survey responses and how their performance in class compares with their peers and the experience of past students. Information might be delivered as a graphic, or as a testimonial.
Early studies suggest that students who use the EÂ²Coach system extensively earn higher grades than they otherwise would. The tool is now being used by introductory chemistry, statistics, and microbiology courses, and reached about 5,200 students per semester last year.
McKay says the system has wider implications. "We also want to start to use computer-tailored communication across the spectrum of interactions between the university and the student," he says, everything from recruiting to academic advising to career services. "It seems obvious that all those kinds of communications ought to be personalized."
Not too long ago, the engineering department asked Steve Lonn's lab for help with a challenge. "By the time the student actually shows up and says, 'I have a problem,' it's often too late to make a difference," Lonn says. Advisers in the department wanted earlier information about a student's progress through a course.
His team looked at student data such as course grades and dug into the university's learning management system, the online portal where students can do everything from participate in discussion sections to download practice problems, and where professors enter assignment grades. Lonn's team then tested to see what predicted a student's success in a course.
The result was Student Explorer. The current version pulls grade data automatically from the learning management system, compares each student's performance with the course average, and factors in how often students log into the course website—a variable that stands in for a student's effort.
It's easy for advisers to use because it classifies students in one of three ways: Encourage (which means the student's doing great), engage (which means the student's falling behind), and explore (which means the student is somewhere in the middle). "We always want the adviser to take some action," Lonn says, whether that's expressing praise or reaching out to see what's wrong.