New research — Towards an Inclusive Analytics for Australian higher education
A new La Trobe University report, led by Bret Stephenson, recommends institutions embed greater data literacy and equity consciousness, in light of increasing interest in advanced data analytics techniques.
According to the NCSEHE-funded research, artificial intelligence (AI) and machine learning (ML) applications now quietly power countless automated decision-making, and predictive processes, across university business areas and throughout the student life cycle. The recent challenge of the COVID-19 crisis, and the emergency shift to online learning, has also notably increased institutional interest in the adoption of Artificial intelligence (AI) and machine learning (ML) “business solutions”. However, these technologies must be applied critically and responsibly to advance student equity interests, rather than amplifying social inequalities.
Recommendations for universities:
- Develop data analytics policies and procedures that protect equity interests throughout the full student life cycle and across all business areas.
- Broaden distribution of analytic expertise, particularly within the DVC (Academic) divisions.
- Broaden distribution of equity and ethics expertise, particularly including within data analytics (institutional research and performance), Information Services, and ICT divisions of the university.
- Increase professional education of staff, including academics, engaged with analytics projects at each stage of the development and deployment process.
- Establish in-house regulatory structures and professional expertise to ensure equity and fairness are protected through the deployment of advanced data analytics, e.g., standing committees to oversee analytics, similar to ethics committees.
- Ensure that analytics-informed interventions are tailored, based on behavioural factors, and designed to reduce self-fulfilling prophecies based on immutable characteristics.
- Regularly monitor and evaluate the analytics project lifecycle for impact on equity and “fairness” interests.
- Work towards benchmarking/collective agendas, potentially involving Universities Australia (UA) leadership.
- Conduct and facilitate further interdisciplinary research into the intersection of equity in higher education and advanced data analytics as an urgent priority.
Read the full report, Towards an Inclusive Analytics for Australian higher education
This research was conducted under the NCSEHE Research Grants Program, funded by the Australian Government Department of Education, Skills and Employment.
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