Course Signals at Purdue: Using learning analytics to increase student success

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Course Signals at Purdue: Using learning analytics to increase student success

Kimberly Arnold
Matthew Pistilli

Abstract

In this paper, 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 Blackboard Vista, Purdue’s learning management system. The outcome is delivered to the students via a personalized email from the faculty member to each student, as well as a specific color on a stoplight – traffic signal– to indicate how each student is doing. The system itself is explained in detail, along with retention and performance outcomes realized since its implementation. In addition, faculty and student perceptions will be shared.

Keywords

Learning Analytics, College Student Success, Early Intervention, Retention

Annotation

Course Signals (CS), a student success system employed at Purdue University, helps to promote academic integration of students to universities. A predictive student success algorithm (SSA) is executed for data mining on multiple university sources, including grades, student demographics, past academic history, students’ performance recorded through Blackboard Vista. Purdue University adopted this system in 2007. CS has been recognized to increase satisfactory grades and decrease unsatisfactory grades and withdrawals. CS also has an impact on student retention. The earlier in their academic career students have a course with CS, the higher the retention rate. 89% of the student respondents reported their positive attitude towards CS. Majority of the respondent (n = 1,500) seem to have connection with computer-generated messages and emails. Faculty and TAs noticed that students are less likely to procrastinate with CS system. Faculty and instructors are found to have a positive response, but they are careful in utilizing CS. Their concern included lack of best practice, and making students more concerned.

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