Get 20M+ Full-Text Papers For Less Than $1.50/day. Subscribe now for You or Your Team.

Learn More →

Course signals at Purdue: using learning analytics to increase student success

Course signals at Purdue: using learning analytics to increase student success Course Signals at Purdue: Using Learning Analytics to Increase Student Success Kimberly E. Arnold Purdue University 519 Young Hall, 155 S. Grant Street West Lafayette, IN 47907 USA kimarnold@purdue.edu Matthew D. Pistilli Purdue University 517 Young Hall, 155 S. Grant Street West Lafayette, IN 47907 USA mdpistilli@purdue.edu 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. solutions should be focused on all students at an institution, not just a http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Course signals at Purdue: using learning analytics to increase student success

Association for Computing Machinery — Apr 29, 2012

Loading next page...
/lp/association-for-computing-machinery/course-signals-at-purdue-using-learning-analytics-to-increase-student-8sQzC4iGrJ

References

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Datasource
Association for Computing Machinery
Copyright
Copyright © 2012 by ACM Inc.
ISBN
978-1-4503-1111-3
doi
10.1145/2330601.2330666
Publisher site
See Article on Publisher Site

Abstract

Course Signals at Purdue: Using Learning Analytics to Increase Student Success Kimberly E. Arnold Purdue University 519 Young Hall, 155 S. Grant Street West Lafayette, IN 47907 USA kimarnold@purdue.edu Matthew D. Pistilli Purdue University 517 Young Hall, 155 S. Grant Street West Lafayette, IN 47907 USA mdpistilli@purdue.edu 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. solutions should be focused on all students at an institution, not just a

There are no references for this article.