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International benchmarking and measuring the quality of learning. Panel I: Big data, big questions

Fri, March 13, 8:00 to 9:30am, Washington Hilton, Floor: Concourse Level, Lincoln West

Session Submission Type: Group Panel

Description of Session

Current proposals for universal goals, targets and indicators, and the mushrooming of global initiatives, meetings and reports, suggest a shift of focus away from developing country contexts and towards a global framework of development. One of the key elements of this framework seems to be a strong push for internationally comparable data on learning outcomes, notably through a “data revolution" called for by the UN High Level Panel in 2013.

In the spirit of Ubuntu as described for the theme of CIES, NORRAG is looking at pluralistic approaches to the assessment of learning, which envision education as a cornerstone for the development of the whole individual who would become an active and thoughtful citizen in both social and economic spheres. In the words of one of our panellists, data should demonstrably benefit the whole education process and ensure it is not a "tail wagging the dog". These panels are planned in close collaboration with Education International, GLOBED Master Consortium and the Open Societies Foundations.

The collection of massive amounts of data on systems and participants in education, for example, could benefit by being examined in the light of potential unintended consequences, national and local needs, corporate vested interests and a more holistic approach to education only partially captured through standardized testing metrics. Moreover, funding is not unlimited, and international calls for comparable data on learning will likely strengthen global and regional institutions in contrast to national or local ones. This proposed panel, complementary to the one entitled ‘Big data and measurement of quality: Alternative and complementary methodologies’, will explore questions concerning the political economy of big data collection efforts and administration of standardized tests designed to evaluate and rank student and teacher performance. Panellists will critically look at key assumptions about the need for, and characteristics of, large-scale data collection and testing. Who defines quality, and how? Is comparability truly possible and when is it necessary? Once needs have been defined, how can projects and interventions be taken to an appropriate scale? Who are and who should be the actors in deciding the what, how and why of measurement? Who are the custodians and purveyors of the results? Who has access and who should have access? What obligations do private sector actors have with respect to the collection, storage, ownership and use of tools and results, and with what controls? How will it be possible to determine whether principles of social justice and quality are being followed or compromised?

And, finally, what mechanisms and conditions need to be established to make sure decisions and implementation are both fair and open to those who will be most affected by the use of data?

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