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Mining institutional datasets to support policy making and implementation

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Mining institutional datasets to support policy making and implementation. / Yorke, Mantz; Barnett, Greg ; Evanson, Peter et al.
In: Journal of Higher Education Policy and Management, Vol. 27, No. 2, 2005, p. 285-298.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Yorke, M, Barnett, G, Evanson, P, Haines, C, Jenkins, D, Knight, P, Scurry, D, Stowell, M & Woolf, H 2005, 'Mining institutional datasets to support policy making and implementation', Journal of Higher Education Policy and Management, vol. 27, no. 2, pp. 285-298. https://doi.org/10.1080/13600800500120241

APA

Yorke, M., Barnett, G., Evanson, P., Haines, C., Jenkins, D., Knight, P., Scurry, D., Stowell, M., & Woolf, H. (2005). Mining institutional datasets to support policy making and implementation. Journal of Higher Education Policy and Management, 27(2), 285-298. https://doi.org/10.1080/13600800500120241

Vancouver

Yorke M, Barnett G, Evanson P, Haines C, Jenkins D, Knight P et al. Mining institutional datasets to support policy making and implementation. Journal of Higher Education Policy and Management. 2005;27(2):285-298. doi: 10.1080/13600800500120241

Author

Yorke, Mantz ; Barnett, Greg ; Evanson, Peter et al. / Mining institutional datasets to support policy making and implementation. In: Journal of Higher Education Policy and Management. 2005 ; Vol. 27, No. 2. pp. 285-298.

Bibtex

@article{b32162a34ff94f6382581506a860944b,
title = "Mining institutional datasets to support policy making and implementation",
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.",
author = "Mantz Yorke and Greg Barnett and Peter Evanson and Chris Haines and Don Jenkins and Peter Knight and Dave Scurry and Marie Stowell and Harvey Woolf",
year = "2005",
doi = "10.1080/13600800500120241",
language = "English",
volume = "27",
pages = "285--298",
journal = "Journal of Higher Education Policy and Management",
issn = "1360-080X",
publisher = "Routledge",
number = "2",

}

RIS

TY - JOUR

T1 - Mining institutional datasets to support policy making and implementation

AU - Yorke, Mantz

AU - Barnett, Greg

AU - Evanson, Peter

AU - Haines, Chris

AU - Jenkins, Don

AU - Knight, Peter

AU - Scurry, Dave

AU - Stowell, Marie

AU - Woolf, Harvey

PY - 2005

Y1 - 2005

N2 - 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.

AB - 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.

U2 - 10.1080/13600800500120241

DO - 10.1080/13600800500120241

M3 - Journal article

VL - 27

SP - 285

EP - 298

JO - Journal of Higher Education Policy and Management

JF - Journal of Higher Education Policy and Management

SN - 1360-080X

IS - 2

ER -