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Autor/inn/enLangan, A. M.; Harris, W. E.; Barrett, N.; Hamshire, C.; Wibberley, C.
TitelBenchmarking Factor Selection and Sensitivity: A Case Study with Nursing Courses
QuelleIn: Studies in Higher Education, 43 (2018) 9, S.1586-1596 (11 Seiten)Infoseite zur Zeitschrift
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0307-5079
DOI10.1080/03075079.2016.1266613
SchlagwörterBenchmarking; Nursing Education; Prediction; Graduation Rate; Comparative Analysis; Educational Administration; Higher Education; Databases; Computer Software; Data Analysis; Foreign Countries; Universities; United Kingdom
AbstractThere is an increasing requirement in higher education (HE) worldwide to deliver excellence. Benchmarking is widely used for this purpose, but methodological approaches to the creation of benchmark metrics vary greatly. Approaches require selection of factors for inclusion and subsequent calculation of benchmarks for comparison. We describe an approach using machine learning to select input factors based on their value to predict completion rates of nursing courses. Data from over 36,000 students, from nine institutions over three years were included and weighted averages provided a dynamic baseline for year on year and within year comparisons between institutions. Anonymised outcomes highlight the variation in benchmarked performances between institutions and we demonstrate the value of accompanying sensitivity analyses. Our methods are appropriate worldwide, for many forms of data and at multiple scales of enquiry. We discuss our results in the context of HE management, highlighting the value of scrutinising benchmark calculations. (As Provided).
AnmerkungenRoutledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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