Teach with Technology

To identify students at risk academically, Course Signals combines predictive modeling with data-mining from Blackboard. Each student is assigned a "risk group" determined by a predictive student success algorithm. One of three stoplight ratings, which correspond to the risk group, can be released on students' Blackboard homepage.

Intervention emails, composed by the instructor and based on grades and effort in the course can be released to each risk group. Course Signals communicates to students to use available resources on campus - like office hours and study materials - to increase their academic success. Both students and instructors benefit from Course Signals.

Course Signals can be set up by an instructor and accessed through the class in Blackboard. To do so, please review the setup documentation. There are then areas within Blackboard for the instructor and students to see the Course Signals feedback and run interventions. If you need assistance setting up your course(s), or have additional questions, please go to the following form.

When instructors follow recommended Course Signals best practices, grade performance improvement has been consistently demonstrated at both the course and at the departmental level. Overall, students in courses using Course Signals receive more Bs and Cs and fewer Ds and Fs than previous sections of the course that did not utilize courses Course Signals. As and Bs have increased by as much as 28% in some courses. In most cases, the greatest improvement is seen in students who were initially receiving Cs and Ds in early assignments, and pull up half a letter grade or more to a B or C.