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All winners in the global measurement sweepstakes? Alexandra Draxler. “The Brave New World of Data for Education and Development” 23 September 2013 Graduate Institute of International and Development Studies. Solutions in search of relevant problems?.
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All winners in the global measurement sweepstakes?Alexandra Draxler “The Brave New World of Data for Education and Development” 23 September 2013 Graduate Institute of International and Development Studies
Solutions in search of relevant problems? More and better international normsMore and better data More and better standardized tests More and better comparisons = Equality of opportunity and learning?
Or Solutions to expanding private sector opportunities? More and better international normsMore and better data More and better standardized tests More and better comparisons = Shiny new markets
About testing: do we know why what is counted counts? Some common assumptions. • Widespread standardized testing reliably informs about learners’ knowledge and skills, and ultimately improves learning outcomes • High-stakes testing encourages competition and reform of schools • Accountability based on classroom metrics is essential to ensure teachers teach well • School choice, buttressed by charter schools, results in better education for all • Performance-based evaluation and pay enables schools to lay off low performing teachers, therefore improving educational outcomes • International comparisons help improve national education performance
Can we be sure? • Testing doesn’t improve learning; in fact we don’t actually know how to measure learning • High-stakes testing distorts the curriculum, disempowers teachers, diverts resources, and fosters institutional cheating • Good institutional environments are not built principally by control and command • The rising tide of school privatization does not lift all childrens’ boats • Culling teachers and principals does not make the remaining ones perform better • National performance is based on too many intertwined factors to be amenable to reform by looking at other countries’ results
The answer is: data revolution To what question is the data revolution the answer? Who are the deciders? Who are the winners? Who are the losers? What might be the perverse effects?
Let them eat data… Study on what PISA tells us about equity (2005) : Policy makers should focus their attention on how basic skills vary between different groups of pupils and different schools within each country High-level Panel : • Make data freely available to all for good governance • Disaggregation to ensure all groups and individuals are covered first step a global strategy … Why? Why is complex internationally-comparable data essential for the majority of people? Will results and policy-relevant information trickle down? Will it build local capacity? Does global data drive local policy and practice? What is the evidence?
Whose Revolution? Who are the deciders? Global Partnership, with private sector. Deliverology enthusiasts: All the people advised by Michael Barber Where was the local demand? Who formulated it? UNDP is already in place with Human Development Report
From top-down to Bottom-up Who are the winners? • International benchmarking has some merit. But it cannot be adequate as the principal method and standard. • The large standardized tests are all created and sold by large corporations: Harcourt Educational Measurement, CTB McGraw-Hill, Riverside Publishing (a Houghton Mifflin company), and NCS Pearson. Educational Testing Service is also moving into the market. PISA tests are formulated by a mixed public-private consortium, with input from all countries. • Large international data collection will certainly be put out to tender. No prizes for guessing that developing country groups will not be in the running.
Lost in Translation Who are the losers? The poorest quintile, that is still not properly included in household surveys. Disparities within countries are still larger than those among countries. That is what needs primary attention. Local researchers’ capacity-building Teachers Measurement of what is taught and learned locally
Measuring Temperature with a spoon What might be the perverse effects? Are we measuring what counts? And if so, are we measuring with the right tools? Do we in fact know how to measure what use people make of skills? Global magical thinking: data not necessarily designed to tackle the main problems Starting at the center won’t necessarily trickle down Displacement effects of funding Capacity not built locally but internationally How much data is enough?
Thank you a.draxler@gmail.com