The use of narrow data sets in education to judge performance is not slowing. Data can be useful, but also problematic if used at the expense of a rich educational experience. However, used well, data can help boost educational experiences and outcomes.
Problematic aspects of data usage in education are associated with the translation of New Public Management (NPM) approaches into education. NPM emphasises target-setting and continuous follow up in pursuit of tangible results, yet generally in a narrow set of areas. Since the 1990’s NPM has promised transformation (Auld & Morris 2023). Lauded at the time as the saviour of the UK health system (Simonet 2013), the decision by the UK government in March 2025 to disband the NHS might raise a question mark about the effectiveness of NPM in public service organisations.
In education NPM has been widely accepted by the UK, Australia and New Zealand. Yet if PISA testing results are any indication, there is little evidence that it is delivering what it promised, especially in Australia. Whereas approaches in countries who do consistently well, such as Singapore, are only now starting to gain attention in the same countries (For a more in-depth treatment of this see Auld & Morris 2023).
Voices which raise concerns about current approaches related to NPM include:
- Diane Ravitch: on the negative impacts of standardised testing and metrics driven reforms
- Bronwen Jones and Stephen J Ball: on the predominance of neo-liberal approaches in education
- David Gillborn: on the inherent bias in education systems and testing.
Focussing only on narrow sets of data hollows out education and reduces the likelihood that it will be a vehicle for personal and social transformation. And education is not complete if it does not introduce the heart to beauty (Francis 2020).
Yet data usage, in some form, can serve the best interests of our students and community, can focus efforts and broaden the educational experience. Here are some tips:
- Work with key groups to establish agreement on what data will and will not be used for
- Ensure that a broad range of data are used- including social and engagement measures
- Focus on growth over time, not just outcomes
- Avoid the temptation to disregard or explain away unfavourable data sets
- Develop data literacy skills across your team to encourage critical dialogue, avoid superficial interpretation and improve decision making.
References
Auld, E. & Morris, P. (2023): Global Salvation Inc.: Sir Michael Barber’s education for the apocalypse and the church of Deliverology®, Comparative Education.
Francis. (2020). A gift of joy and hope. Hodder and Stoughton.
Gillborn, D. (2008). Racism and education: Coincidence or conspiracy? Routledge.
Jones, B., & Ball, S. J. (2023). Neoliberalism and education. Oxon & New York: Routledge.
Ravitch, D., Forte, D., Moss, P. & Reville, P. (2022). Policy dialogue: Twenty years of test-based accountability. History of Education Quarterly. Vol. 62 Issue 3 Pages 337-352.
Simonet, D. (2013). The New Public Management Theory in the British Health Care System: A Critical Review. Administration & Society. Vol. 47 Pages 1-25.
Winkler, C. E. & Wofford, A. M. (2024). Trends and Motivations in Critical Quantitative Educational Research: A Multimethod Examination Across Higher Education Scholarship and Author Perspectives. Research in Higher Education.
5 April 2025