©Commonwealth of Australia 1998
ISBN 0 642 23788 3
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This report is funded under the Evaluation and Investigations Programme of the Department of Employment, Education, Training and Youth Affairs.
The views expressed in this report do not necessarily reflect the views of the Department of Employment, Education, Training and Youth Affairs.
Executive Summary
The authors of this report, members of the Department of Anthropology and Sociology at The University of Queensland, were contracted by the Department of Employment, Education, Training and Youth Affairs (DEETYA) to develop measures to identify higher education students from low socioeconomic and rural and isolated backgrounds. Of the six designated equity groups in Australian higher education, these two groups have been the hardest to define. The postcode methodology currently used by the Department of Employment, Education, Training and Youth Affairs to identify students from these groups is seen, notwithstanding its simplicity and practicality, as being unsuitable in many cases.
This report examines and evaluates suitable and practicable alternative methods of identifying students from low socioeconomic, rural and isolated groups. Chapters 2 and 3 are concerned with socioeconomic status; and Chapters 4 and 5 focus on rurality and isolation. In these chapters, we review past approaches to the identification of persons from low socioeconomic, rural and isolated groups; examine current measurement methods adopted by the Department of Employment, Education, Training and Youth Affairs and individual higher education institutions; and develop new measures.
The new measures are based upon the results of an analysis of the Participation in Higher Education Survey. This survey was conducted in Semester 2, 1997 and was based upon a sample of approximately 3000 students enrolled in first year undergraduate subjects at a range of higher education institutions throughout Queensland. The survey was designed specifically for this project (see Appendices 1 and 2).
The Identification of Students from Low Socioeconomic Backgrounds
Socioeconomic status is a broad concept that comprises three main dimensions: occupation, education and wealth. In the higher education context, the dimensions relating to parental occupation and education are most salient. These dimensions have been both theoretically and empirically linked to educational attainments (see Chapter 2).
The measure of socioeconomic status currently collected for DEETYA’s student statistical collection is based upon the Index of Occupation and Education developed by the Australian Bureau of Statistics. The Index provides a measure of the average occupational and educational characteristics of residents of postcode areas. The socioeconomic status of a student is estimated by the Index value for the postcode of the student’s permanent home address. This measure is subject to error as a student is allocated the ‘average’ of all persons living within a particular area, and areas can contain a mix of people from low, medium and high socioeconomic backgrounds (see pp. 19–25).
In order to accurately identify students from low socioeconomic backgrounds, measures based upon the characteristics of individual students, rather than the characteristics of the area in which they reside, are developed. Our findings suggest that individual-based measures relating to the occupation and education of parents at the time when the student was in high school, are appropriate for both recent school leavers and mature aged students. Together, these characteristics represent the family socioeconomic situation while the student was completing their secondary schooling (see Chapter 3).
It is therefore recommended that:
Recommendation 1
- mother’s occupation;
- father’s occupation;
- mother’s educational level; and
- father’s educational level (see pp. 32–33)
Recommendation 2
Recommendation 3
- parental occupational status, defined by the occupation of the parent with the highest occupational status as measured by the ANU3 scale; and
- parental educational level, defined by the education of the parent with the highest educational level (see pp. 26–27)
Recommendation 4
Occupation coded to the ANU3 scale ranks occupations on a scale from 1 to 100, while educational level as measured in this study is ranked from 1 to 6. As such, the occupation measure provides a finer classificatory scheme, allowing more flexibility in the setting of thresholds to distinguish between socioeconomically disadvantaged and other students.
It is therefore recommended that:
Recommendation 5
Recommendation 6
The setting of thresholds to indicate socioeconomic disadvantage, when using either the occupational status or education measure, is somewhat arbitrary. Appropriate thresholds may vary, depending upon the purpose to which the measure is being applied. This is an issue which needs to be addressed by policy makers in consultation with the higher education sector.
It is therefore recommended that:
Recommendation 6
In order to monitor the higher education participation rates of students from socioeconomically disadvantages backgrounds, it is necessary to compare the student population with the general population. There are no directly comparable population measures available. However, two approaches to the development of comparable measures are outlined on pages 38–42. The first approach will permit a comparison of the entire higher education student body with the general Australian population. Such a comparison may yield more accurate results for the recent school leaver group than for mature age entrants. In order to determine which of the two approaches will provide the most reliable basis for comparison, analysis of Census data must be undertaken. The costs and time involved in undertaking such an analysis are beyond the scope of the present consultancy.
It is therefore recommended that:
Recommendation 8
The Identification of Rural and Isolated Students
Rurality and isolation are most commonly defined in terms of population density and distance to urban centres. However, many university campuses in Australia are located outside major metropolitan areas. Due to the location of campuses in some provincial centres, not all rural students are disadvantaged in terms of proximity to a higher education institution. Therefore, a more appropriate conceptualisation of locational disadvantage in the higher education context is related to access to institutions of higher education. This involves a consideration of location in relation to university campuses, rather than urban centres (see Chapters 4 and 5).
DEETYA’s current method of classifying students’ locational background in its Student Statistical Collection is based upon location in relation to urban centres. The postcode-level measure developed by the Department of Primary Industries and Energy (DPIE) and the Department of Human Services and Health (DHSH) is used to classify students’ permanent home addresses as urban, rural or isolated. We argue that the conceptual basis of this measure is inappropriate, and develop new measures of locational disadvantage based upon the notion of access to university campuses (see Chapters 4 and 5).
The strategy adopted here has been first to revise the DPIE–DHSH postcode measure so as to take into account the location of university campuses. Students are classified as having high, moderate or low access on the basis of distance from their permanent home address to higher education institutions. This measure provides an improved method of classifying students for monitoring purposes, and will not entail the collection of additional data from students. It can be used to compare the locational characteristics of students with those of the general population (see pp. 62–68).
Second, we develop a measure of access that relates the location of the student’s permanent home address to the location of the campus at which the student is enrolled. This provides a more direct and accurate assessment of individual disadvantage, and therefore is appropriate for the identification of individual students. However, comparable measures are not available at the population level, making this measure inappropriate for more broad-based monitoring purposes (see pp. 68–72).
In the identification of rural and isolated students, it is recommended that:
Recommendation 9
Recommendation 10
Recommendation 11
Recommendation 12
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