Literaturnachweis - Detailanzeige
Autor/inn/en | Gandy, Rex; Crosby, Lynne; Luna, Andrew; Kasper, Daniel; Kendrick, Sherry |
---|---|
Institution | Association for Institutional Research (AIR) |
Titel | Enrollment Projection Using Markov Chains: Detecting Leaky Pipes and the Bulge in the Boa. The AIR Professional File, Fall 2019. Article 147 |
Quelle | (2019), (18 Seiten)
PDF als Volltext |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Monographie |
Schlagwörter | Markov Processes; Enrollment Projections; Higher Education; College Credits; Enrollment Management; Public Colleges; Undergraduate Students; Educational Attainment; Predictive Validity |
Abstract | While Markov chains are widely used in business and industry, they are used within higher education only sporadically. Furthermore, when used to predict enrollment progression, most of these models use student level as the classification variable. This study uses grouped earned student credit hours to track the movement of students from one academic term to the other to better identify where students enter or leave the institution. Results from this study indicate a high level of predictability from one year to the next. In addition, the use of the credit hour flow matrix can aid administrators in identifying trends and anomalies within the institution's enrollment management process. (As Provided). |
Anmerkungen | Association for Institutional Research. 1435 East Piedmont Drive Suite 211, Tallahassee, FL 32308. Tel: 850-385-4155; Fax: 850-383-5180; e-mail: air@airweb.org; Web site: http://www.airweb.org |
Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2024/1/01 |