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Wolverhampton Intellectual Repository and E-Theses > School for Education Futures > Centre for Developmental and Applied Research in Education (CeDARE) > Learning and Teaching in Higher Education > Mining institutional datasets to support policy making and implementation

Please use this identifier to cite or link to this item: http://hdl.handle.net/2436/26397
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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
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
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.
Type: Article
Language: en
Keywords: Higher education
Student demographics
Student performance
ISSN: 1360080X
14699508
Appears in Collections: Learning and Teaching in Higher Education

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