Predicting Success: How Predictive Analytics Are Transforming Student Support and Success Programs

Autor/in	Boerner, Heather
Titel	Predicting Success: How Predictive Analytics Are Transforming Student Support and Success Programs
Quelle	In: Community College Journal, 86 (2015) 1, S. 14-18 PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1067-1803
Schlagwörter	Forschungsbericht; Prediction; Academic Support Services; Two Year College Students; Community Colleges; Academic Achievement; Data Analysis; Technology Uses in Education; Florida; Texas + Suchen Sie Ihr Suchwort? Vorhersage; Community college; Community College; Schulleistung; Auswertung; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen
Abstract	Every year, Lone Star College in Texas hosts a "Men of Honor" program to provide assistance and programming to male students, but particularly those who are Hispanic and black, in hopes their academic performance will improve. Lone Star might have kept directing its limited resources toward these students--and totally missed the subset that is really struggling--had it not been for a new way of looking at the data using predictive analytics. An internal team led by Marian Burkhart, executive director of analytics and institutional reporting for the system, explored the issues and found a significant difference among male persistence rates. The team continues to study male persistence, now with a focus on behavioral characteristics related to GPA, academic program and STEM course loads. There are many useful ways to use data. But predictive analytics are something different, explains David Jarrat, vice president of marketing at InsideTrack, a student services company that has offered in-person, telephone and virtual student coaching since 2001. Now there are vendors and programs that range from high-level overviews to analytics programs designed to provide early warnings to advisors or faculty. Inspire for Faculty, an application from Civitas Learning, feeds data through a customized algorithm that analyzes how often students in online courses log in, click and respond to determine which students are struggling and likely to drop out. Then, the program automatically sends an email from the instructor, asking the student if everything is OK. There are also predictive analytics programs that can flag students who are veering off pathways that lead to transfer, graduation or certificates. Civitas is working on such a program now, and InsideTrack is adapting its long-standing advising program to be informed by predictive data. Institutions like Valencia College, which has been using predictive analytics the longest, is seeing anecdotal evidence that the data are catching students and connecting those students to faculty support right away. However, the College has determined that both college-wide leadership that empowers faculty and the faculty themselves are what give predictive analytics their power. (ERIC).
Anmerkungen	American Association of Community Colleges. One Dupont Circle NW Suite 410, Washington, DC 20036. Tel: 202-728-0200; Fax: 202-833-2467; Web site: http://www.aacc.nche.edu/bookstore
Begutachtung	Peer reviewed
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01