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dc.contributor.authorYorke, Mantz
dc.contributor.authorBarnett, Greg
dc.contributor.authorEvanson, Peter
dc.contributor.authorHaines, Chris
dc.contributor.authorJenkins, Don
dc.contributor.authorKnight, Peter
dc.contributor.authorScurry, David
dc.contributor.authorStowell, Marie
dc.contributor.authorWoolf, Harvey
dc.date.accessioned2008-05-16T08:52:31Z
dc.date.available2008-05-16T08:52:31Z
dc.date.issued2005
dc.identifier.citationJournal of Higher Education Policy and Management, 27(2): 285-298
dc.identifier.issn1360080X
dc.identifier.issn14699508
dc.identifier.doi10.1080/13600800500120241
dc.identifier.urihttp://hdl.handle.net/2436/26397
dc.description.abstractDatasets 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.
dc.language.isoen
dc.publisherRoutledge (Taylor & Francis)
dc.relation.urlhttp://www.informaworld.com/smpp/content~db=all?content=10.1080/13600800500120241
dc.subjectHigher education
dc.subjectStudent demographics
dc.subjectStudent performance
dc.titleMining institutional datasets to support policy making and implementation
dc.typeJournal article
dc.identifier.journalJournal of Higher Education Policy and Management
html.description.abstractDatasets 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.


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