Home > Research > Publications & Outputs > Mining institutional datasets to support policy...
View graph of relations

Mining institutional datasets to support policy making and implementation

Research output: Contribution to Journal/MagazineJournal articlepeer-review

  • Mantz Yorke
  • Greg Barnett
  • Peter Evanson
  • Chris Haines
  • Don Jenkins
  • Peter Knight
  • Dave Scurry
  • Marie Stowell
  • Harvey Woolf
<mark>Journal publication date</mark>2005
<mark>Journal</mark>Journal of Higher Education Policy and Management
Issue number2
Number of pages14
Pages (from-to)285-298
Publication StatusPublished
<mark>Original language</mark>English


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.