2.50
Hdl Handle:
http://hdl.handle.net/2436/26397
Title:
Mining institutional datasets to support policy making and implementation
Authors:
Yorke, Mantz; Barnett, Greg; Evanson, Peter; Haines, Chris; Jenkins, Don; Knight, Peter; Scurry, David; Stowell, Marie; Woolf, Harvey
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:
Routledge (Taylor & Francis)
Journal:
Journal of Higher Education Policy and Management
Issue Date:
2005
URI:
http://hdl.handle.net/2436/26397
DOI:
10.1080/13600800500120241
Additional Links:
http://www.informaworld.com/smpp/content~db=all?content=10.1080/13600800500120241
Type:
Article
Language:
en
ISSN:
1360080X; 14699508
Appears in Collections:
Learning and Teaching in Higher Education

Full metadata record

DC FieldValue Language
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): 285-298en
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.en
dc.language.isoenen
dc.publisherRoutledge (Taylor & Francis)en
dc.relation.urlhttp://www.informaworld.com/smpp/content~db=all?content=10.1080/13600800500120241en
dc.subjectHigher educationen
dc.subjectStudent demographicsen
dc.subjectStudent performanceen
dc.titleMining institutional datasets to support policy making and implementationen
dc.typeArticleen
dc.identifier.journalJournal of Higher Education Policy and Managementen
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