Benchmarking factor selection and sensitivity: a case study with nursing courses

摘要: ABSTRACTThere is an increasing requirement in higher education (HE) worldwide to deliver excellence. Benchmarking widely used for this purpose, but methodological approaches the creation of benchmark metrics vary greatly. Approaches require selection factors inclusion and subsequent calculation benchmarks comparison. We describe approach using machine learning select input based on their value predict completion rates nursing courses. Data from over 36,000 students, nine institutions three years were included weighted averages provided a dynamic baseline year within comparisons between institutions. Anonymised outcomes highlight variation benchmarked performances we demonstrate accompanying sensitivity analyses. Our methods are appropriate worldwide, many forms data at multiple scales enquiry. discuss our results context HE management, highlighting of...