Course Signals at Purdue: Using Learning Analytics to Increase Student Success

Type: Evidence | Proposition: B: Teaching | Polarity: | Sector: | Country:

An early intervention solution for collegiate faculty called Course Signals is discussed. Course Signals was developed to allow instructors the opportunity to employ the power of learner analytics to provide real-time feedback to a student. Course Signals relies not only on grades to predict students’ performance, but also demographic characteristics, past academic history, and students’ effort as measured by interaction with Purdue University’s learning management system. The outcome is delivered to the students via a personalized email from the educator to each student, as well as a specific colour on a traffic signal, to indicate how each student is doing. The system is explained in detail, along with retention and performance outcomes realized since its implementation.

The study showed that students who began at Purdue University in autumn 2007, 2008  or 2009 and participated in at least one Course Signals course were retained at rates significantly higher than their peers who had no Course Signals classes but who started at Purdue during the same semester.

The paper also argues that students who had two or more courses with CS were consistently retained at rates higher than those who had only one or no courses with Signal. However, bloggers have since pointed out that the longer students stay at Purdue, the more likely they are to be on two courses using CS, so the figures in this area need to be re-examined in future.

Citation: Arnold, Kimberley E, & Pistilli, Matthew. (2012). Course Signals at Purdue: Using Learning Analytics To Increase Student Success. Paper presented at the LAK12: 2nd International Conference on Learning Analytics and Knowledge (30 April - 2 May), Vancouver, Canada.