By Stéphanie Langstaff, NORRAG.
Though different in scope, both the “new data revolution” proposed by the UNSG’s Post-2015 High-Level Panel of eminent persons, and universal learning indicators recommended by the Learning Metrics Task Force, advocate the improvement of data and the measurement of outcomes – through globally comparable indicators and metrics – for better monitoring and evidence-based policy making. This drive towards more standardized and quantifiable data brings up a number of questions on the policy implications for education and development. What data will be given priority, how will it be collected and used, by whom, and at what cost? And most importantly, how and to what extent can quality education and lifelong learning be measured?
These issues, and more generally the importance given to results, evidence and outcomes in the post-2015 agenda, were critically discussed by about 40 development practitioners and researchers who attended the NORRAG meeting on “The Brave New World of Data for Education and Development” on 23rd September 2013 in Geneva.
After a brief overview of what is being promoted by global policy-thinkers, three speakers shared their insights to open up discussion among the meeting participants:
- Alexandra Draxler argued that global measurement would mainly benefit large corporations, to the detriment of local research and knowledge, as well as teachers.
- Nicholas Burnett, on the contrary, insisted on the potential benefits of more data to improve advocacy for education, apply evidence and ensure accountability.
- Jacques Malpel also underlined the importance of data for policy-making and accountability. However, based on the experience of PASEC, he suggested giving priority to capacity-building, monitoring and policy dialogue at the national and regional levels.
In the ensuing discussion, the need for more and better data as tools for advocacy, and means of accountability and reporting in the field of education, was acknowledged. However, concern was raised at the narrowness of what is being looked at in the HLP’s “data revolution” and in the LMTF’s learning framework.
Data as numbers
Despite a timely shift from access to learning (at school or outside school), the focus is on measurement rather than on the assessment of education, and on learning outputs rather than on learning outcomes. Quality education tends, therefore, to be narrowly conceived as what can be quantified and measured in terms of efficiency and outputs. This involves a great risk of teaching to the test. Besides, some dimensions of education – such as values – are particularly challenging to measure, and raise the whole issue of balance between universalism and particularism. On these issues, there is clearly a need for research and data which are not only based on neoclassical economics and functionalist sociology, econometric and statistical modelling. More generally, a true data revolution for education and development needs evidence that cannot be solely produced through randomized control trials and international expertise.
A top-down approach
The ‘data revolution’ gives considerable attention to statistical institutions, in particular to improve data collection through national household surveys. Local research would also need support to produce creative and context-sensitive data to enable quality education. A bottom-up approach to data, education and development is completely lacking at the moment, and a small group of institutions (World Bank, Brookings, LMTF) appear to be proposing what to learn and what to measure. Global data and international comparisons are potentially very relevant for analysing change, tracking inequalities and informing national policies. Yet, there is a risk of using them as aid conditionalities and tools for ranking countries without any impact on policies.
It is important to keep in mind the political dimension of data, and to think about the way data are built and used. As the Guardian’s Jonathan Glennie notes, “rather than evidence-based policymaking, we so often have policy-based evidence-making”, i.e. data and evidence can be manipulated and manipulating. This explains why a wealth of data and evidence does already exist but are ignored when not pushing a specific agenda. The current push for the global measurement of education and development promotes a certain vision of the world and the future that has yet to be discussed and agreed upon.
Stéphanie Langstaff is involved in the organisation of NORRAG events and the follow-up of post-2015 case studies. Email: Stephanie.email@example.com
Disclaimer: The views given in this blog are those of the author alone and should not be attributed to NORRAG or its members. Readers are invited to comment below.