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Research on Course Signals and Academic Analytics

Research on the use of analytics to increase student success, and the implementation of analytics through Course Signals, has been conducted by Purdue staff associated with ITaP. The references below are part of a broader body of literature on academic analytics, and many of them are cited as the foundation for others' research. As more research is published, this listing will be updated.

Academic Analytics

  • Campbell, J. P. (2007) Proceedings from The Higher Learning Commission: Academic success: Using institutional data to predict student achievement. Chicago, IL.

  • Campbell, J. P. (2007). Seven things you should know about analytics. EDUCAUSE Learning Initiative. Boulder, CO. View PDF

  • Campbell, J. P. (2007). Utilizing Student Data within the Course Management System to Determine Undergraduate Student Academic Success: An Exploratory Study. Unpublished doctoral dissertation: Purdue University. View Online

  • Campbell, J. P., Collins, W.B., Finnegan, C., & Gage, K. (2006). "Academic analytics: Using the CMS as an early warning system." WebCT Impact 2006. Chicago, IL. View Online

  • Campbell, J. P., DeBlois, P. B., & Oblinger, D. G. (2007). Academic analytics: A new tool for a new era. EDUCAUSE Review, 42 (4), 40-42. View PDF

  • Campbell, & Oblinger, D. (2007). Academic analytics. Washington, DC: EDUCAUSE Center for Applied Research. View Online

  • Devany, L. (2010). Purdue's student achievement technology goes national. View Online

  • Oblinger, D. G. and Campbell, J. P. (2007). Academic Analytics, EDUCAUSE White Paper. View PDF

  • van Barneveld, A., Arnold, K. E., & Campbell, J.P. (2012). Analytics in Higher Education: Establishing a Common Language (white paper).  Boulder, CO: EDUCAUSE Learning Initiative . View PDF

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    Course Signals

  • Arnold, K. E. (2010). Signals: Applying academic analytics. EDUCAUSE Quarterly, 33(1). View Online

  • Arnold, K. E. & Pistilli, M. D. (2012). Course Signals at Purdue: Using learning analytics to increase student success. Proceedings of the 2nd International Conference on Learning Analytics & Knowledge. New York: ACM. View PDF

  • Arnold, K.E., Tanes, Z. & King, A.S. (2010). Administrative perspectives of data-mining software Signals: Promoting student success and retention. The Journal of Academic Administration in Higher Education 6 (2), 29-39. View Online (scroll to page 29 for article)

  • Campbell, J. P., Finnegan, C., & Collins, B. (2006). Academic analytics: Using the CMS as an early warning system. Paper presented at the WebCT impact conference 2006. View Online

  • Iten, L., Arnold, K., Pistilli, M. (2008, March). Mining real-time data to improve student success in a gateway course. Paper presented at the Eleventh Annual TLT Conference. West Lafayette, IN: Purdue University. View PDF

  • Pistilli, M.D. & Arnold, K.E. (2010). Purdue signals: Mining real-time academic data to enhance student success. About Campus: Enriching the student learning experience, 15 (3), 22-24. View PDF

  • Tanes, Z., Arnold, K.E., King, A.S., & Remnet, M.A. (2011). Using Signals for appropriate feedback: Perceptions and practices. Computers & Education 57 (4), 2414-2422. View PDF