Mining institutional datasets to support policy making and implementation
Yorke, Mantz Barnett, Greg Evanson, Peter Haines, Chris Jenkins, Don Knight, Peter Scurry, David Stowell, Marie Woolf, Harvey
Yorke, Mantz
Barnett, Greg
Evanson, Peter
Haines, Chris
Jenkins, Don
Knight, Peter
Scurry, David
Stowell, Marie
Woolf, Harvey
Editors
Other contributors
Affiliation
Epub Date
Issue Date
2005
Submitted date
Alternative
Abstract
Datasets are often under-exploited by institutions, yet they contain evidence that is potentially of high value for planning and decision-making. This article shows how institutional data were used to determine whether the demographic background of students might have an influence on their performance: this is a matter of particular interest where participation in higher education is being widened. Analyses showed that, whilst area of domicile appeared to be related to lower performance in a few disciplinary areas, much stronger relationships were evident in respect of other demographic variables. The use of nonparametric analyses based on cutting module performances at the median, rather than using raw scores, is of methodological interest since the distribution of raw marks is influenced by the subject discipline.
Citation
Journal of Higher Education Policy and Management, 27(2): 285-298
Publisher
Research Unit
PubMed ID
PubMed Central ID
Embedded videos
Type
Journal article
Language
en
Description
Series/Report no.
ISSN
1360080X
14699508
14699508