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International benchmarking and measuring the quality of learning. Panel II: Alternative and complementary methodologies

Fri, March 13, 9:40 to 11:10am, 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".
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 panel, complementary to the one titled Big data, big questions will look at initiatives that focus on quality, citizen participation (including education personnel), examples of broad measures of quality, and evaluating the evaluators.
The proposed panel will be organized around three complementary perspectives to current approaches to the post-2015 "data revolution":
1. A focus on longitudinal studies and effects: many desirable outcomes of education are medium and long-term e.g., as productive workers, active citizens, discerning consumers, problem solvers, and family formers. Most benchmarking of "learning outcomes" is necessarily a snapshot at a particular time point, which thus provides limited evidence about longer-term impacts of education. It is entirely possible that existing data can be better utilized to tease out longer-term impacts of learning on individuals, families, communities and countries to support more longitudinal approaches to data collection and analysis.
2. Impact assessment: there is an urgent need to understand the impact of assessment practices. How do we develop, test and promote ways to more closely scrutinize reforms in learning assessment and related processes, notably in light of both expected desirable and unintended consequences?
3. Capacity building and empowerment for national and local data gathering: What kinds of assessment practices and information are more likely to result in real change in schools and classrooms? What should be the roles of teachers, citizens, school leaders, academics, and assessment specialists in improving and conducting learning assessments? How can different actors be empowered to increase their voice and participation in existing assessment techniques?

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