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Home Casestudy Attracting diversity: University of Dundee

Attracting diversity: University of Dundee

Published: 23/02/2016

Lessons learned

  • Consider looking at only one protected characteristic at a time.
  • Attempt to ensure that the selected filters that have been used for the data report (benchmarked HEIDI data) are communicated throughout the report.
  • The lead of the qualitative and quantitative groups should attend both working group meetings.

Background

As a ‘redbrick’ institution, the University of Dundee has always sought to attract excellent students. It is now looking more closely at the demographic characteristics of applicants and is aware that some courses attract a narrower range of students. In keeping with its vision statement it is attempting to ensure that no group feels excluded.

Aims

By participating in the programme the university aimed to attract applicants, regardless of background, by ensuring that it has a positive, inclusive culture reflected in the applicant experience. Its core purpose is to transform lives, reflecting its core value of valuing people. It aimed to achieve this by understanding and addressing barriers through quantitative analysis of specific characteristics of the current student intake, namely gender, ethnicity, age and disability. It would also undertake qualitative analysis of the experience of applicants and devise a plan of action to remove barriers, real and perceived.

While participating in the programme the university identified the key protected characteristics that it sought to investigate, but subsequently gender was selected as the priority. Two working groups were formed (quantitative and qualitative) that met to discuss best practice in data collection and analysis, and focus groups are planned once ethical approval has been granted.

Planned outcomes

Short term: by the end of the programme (July 2015):

  • Complete quantitative research for gender
  • Complete preparation of qualitative focus group, ready for earliest use

Medium and longer term objectives and expected outcomes (by July 2016):

  • Deliver qualitative focus group comprising students who by gender are significantly underrepresented within their programme, to undertand what underrepresentation may be due to, for example, cultural stereotypes, peer or parental pressure, media and promotional material portrayal etc.
  • Report on outcomes from the focus groups.

Successes to date

  • At this early stage the main output has been to illuminate the current demographic distribution and to begin informed discussion on how the university feels about this distribution, while raising awareness that the university has a duty to evenly promote provision to all.
  • Some subject areas are heavily dominated by particular genders, with some differing greatly from the benchmarked data from comparator HEIs.
  • Dividing the quantitative and qualitative tasks into two groups initially worked well, as it allowed the quantitative group to focus purely on the data without being influenced by its context. The group approach also allowed for work delegation and subsequent sharing of ideas on how best to proceed with the benchmarking data.
  • Wider engagement with staff and students in the institution has evolved as the qualitative group expanded as interest from colleagues grew, while the university’s student association led recruitment of students for focus group involvement.
  • The work has some considerable way to go before it becomes sustainable and embedded, as this might for example require all staff to have the capacity to review the demographics of their classes and develop an understanding of why distributions are as they appear and what steps they might support through admissions and student recruitment to portray their subject to a more diverse audience.
  • There is potential for the quantitative data report to be updated, resource permitting, after the release of the Higher Education Statistics Agency data to keep it current.

Challenges

  • Benchmarking data, was difficult and time consuming to extract. Specific factors were filtered for the data extraction and because of this, university data used may be different to other institutional benchmarking reports, limiting accurate comparison.
  • Quantitative analysis was an individual task once the benchmarked data had been generated and because of this it has been difficult to fit the work into an existing analysts’ time.
  • Protected time for group members was not available.
  • Ethical approval needed to be sought to approve survey instruments, partly due to best practice but also due to sensitivities around the issue of inclusion, which required an approach that, for example, allowed participants of a focus group to withdraw from comment or involvement at any point.

If the university were to undertake the project again it would select a smaller number of protected characteristics to monitor and feels it would have been more productive to focus on one.

The (understandable) absence of targets diluted interest in effecting change, which itself would have proved difficult to measure against baselines. It was also felt that the team’s effort might not be directly rewarded.

Next steps

  • In academic year 2015/16 the university intends to complete its initial focus group activity and use what is found to guide its next activities.
  • At an elementary level, informing its academic schools of data relating to protected characteristic groups will provide them with what for some will be their first insight into the demographics of their cohorts, how these may vary across time and between subjects.
  • This in turn may lead to deeper reflection on the mechanisms by which they promote their provision.