Standing up to be counted: Data quality challenges in Aboriginal and Torres Strait Islander higher education statistics
Data quality and availability in relation to Aboriginal and Torres Strait Islander students' higher education participation and pathways remains a persistent challenge. In this paper we identify that, to date, there has been no systematic attempt to conceptualise and summarise many important as...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
Aboriginal Studies Press (ASP)
2016
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| Online Access: | https://search.informit.com.au/documentSummary;dn=521088118432418;res=IELIND http://hdl.handle.net/20.500.11937/69460 |
| _version_ | 1848762046391255040 |
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| author | Drew, N. Wilks, J. Wilson, Katie Kennedy, G. |
| author_facet | Drew, N. Wilks, J. Wilson, Katie Kennedy, G. |
| author_sort | Drew, N. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Data quality and availability in relation to Aboriginal and Torres Strait Islander students' higher education participation and pathways remains a persistent challenge. In this paper we identify that, to date, there has been no systematic attempt to conceptualise and summarise many important aspects of data quality. The research reported in this paper, enabled through funding from an Office for Learning and Teaching seed grant, redresses this and proposes a conceptual framework for identifying and understanding the impacts of matters of data quality. We argue that the pursuit of a shared statistical literacy is best viewed through the dual lens of whiteness and Aboriginal and Torres Strait Islander terms of reference. Borrowing from the health sector, we conceptualise data quality issues as upstream, midstream and downstream. This framework identifies the locus of responsibility and intervention as a catalyst for purposeful action to address data quality challenges at the national, sectoral and institutional levels. The benefits of applying the proposed framework include a conceptual lens through which cultural issues may be unmasked; enhanced sector-wide critical statistical literacy; and a systematic accountability framework for assessing efforts to improve data quality. Finally, it is proposed that key elements from this framework might be usefully applied to the development of sector-wide guidelines for the collection, interpretation, use and storage of quality data and statistics to enhance the transition, participation and retention experiences of Aboriginal and Torres Strait Islander higher education students. |
| first_indexed | 2025-11-14T10:41:20Z |
| format | Journal Article |
| id | curtin-20.500.11937-69460 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:41:20Z |
| publishDate | 2016 |
| publisher | Aboriginal Studies Press (ASP) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-694602018-10-04T03:18:42Z Standing up to be counted: Data quality challenges in Aboriginal and Torres Strait Islander higher education statistics Drew, N. Wilks, J. Wilson, Katie Kennedy, G. Data quality and availability in relation to Aboriginal and Torres Strait Islander students' higher education participation and pathways remains a persistent challenge. In this paper we identify that, to date, there has been no systematic attempt to conceptualise and summarise many important aspects of data quality. The research reported in this paper, enabled through funding from an Office for Learning and Teaching seed grant, redresses this and proposes a conceptual framework for identifying and understanding the impacts of matters of data quality. We argue that the pursuit of a shared statistical literacy is best viewed through the dual lens of whiteness and Aboriginal and Torres Strait Islander terms of reference. Borrowing from the health sector, we conceptualise data quality issues as upstream, midstream and downstream. This framework identifies the locus of responsibility and intervention as a catalyst for purposeful action to address data quality challenges at the national, sectoral and institutional levels. The benefits of applying the proposed framework include a conceptual lens through which cultural issues may be unmasked; enhanced sector-wide critical statistical literacy; and a systematic accountability framework for assessing efforts to improve data quality. Finally, it is proposed that key elements from this framework might be usefully applied to the development of sector-wide guidelines for the collection, interpretation, use and storage of quality data and statistics to enhance the transition, participation and retention experiences of Aboriginal and Torres Strait Islander higher education students. 2016 Journal Article http://hdl.handle.net/20.500.11937/69460 https://search.informit.com.au/documentSummary;dn=521088118432418;res=IELIND Aboriginal Studies Press (ASP) fulltext |
| spellingShingle | Drew, N. Wilks, J. Wilson, Katie Kennedy, G. Standing up to be counted: Data quality challenges in Aboriginal and Torres Strait Islander higher education statistics |
| title | Standing up to be counted: Data quality challenges in Aboriginal and Torres Strait Islander higher education statistics |
| title_full | Standing up to be counted: Data quality challenges in Aboriginal and Torres Strait Islander higher education statistics |
| title_fullStr | Standing up to be counted: Data quality challenges in Aboriginal and Torres Strait Islander higher education statistics |
| title_full_unstemmed | Standing up to be counted: Data quality challenges in Aboriginal and Torres Strait Islander higher education statistics |
| title_short | Standing up to be counted: Data quality challenges in Aboriginal and Torres Strait Islander higher education statistics |
| title_sort | standing up to be counted: data quality challenges in aboriginal and torres strait islander higher education statistics |
| url | https://search.informit.com.au/documentSummary;dn=521088118432418;res=IELIND http://hdl.handle.net/20.500.11937/69460 |