Relevant data for education post-2015 need not be ‘big data’

post2015_data_200With the 2015 deadline of the Millennium Development Goals (MDGs) approaching, planning for a new development agenda, known as the Sustainable Development Goals (SDGs), is taking shape. Concurrently, as the world embraces the notion of sustainability and sustainable development, a technology revolution is upon us. It is rooted in the enormous streams of information routinely captured by computers and other digital means in our workplaces, homes and communities. The scope and implications of this ‘data revolution’ are being linked to the new developments goals and their corresponding ambitious targets. This blog asks whether a revolution is really required for us to be able to measure progress in the post-2015 education targets.

UN Secretary-General Ban Ki-moon recently asked an Independent Expert Advisory Group to make concrete recommendations for bringing about a data revolution in sustainable development. The EFA Global Monitoring Report, which has been monitoring education goals since 2002, participated in the recent public consultation run by this group. We took the view that, while ‘big data’ may be an exciting concept, we must remember that most countries are still grappling with the compilation of reliable, high quality data in education. Getting the basics right is critical, before we embark on grander mechanisms. Doing so would go a long way in helping the international community measure new global education targets post-2015. Here is what the GMR team contributed to three of the consultation’s key questions.

Credit: Monika Nikope/UNESCO

Credit: Monika Nikope/UNESCO

First, on the prospect of measuring progress of the sustainable development goal on education, two concerns come to mind. The first is the need for better information on early childhood development, learning outcomes, and skills for youth and adults, including literacy. Understandings of terms such as ‘skills’ and ‘literacy’ have evolved considerably from how they were defined at Dakar. Adult literacy is now viewed on a continuum, for instance, rather than a black and white classification of an adult being either literate or not. We must be sure that data for post-2015 targets follow suit. However, while some are suggesting over-hauling ways of collecting data, and bringing about a ‘revolution’ through technological means, our position is that better coordination between agencies in order to develop ways to measure these outcomes, and more money to implement these ideas, would bring about the changes needed to measure education progress post-2015.

The second concern is our ability to measure and monitor inequality. For that we will need information that tracks the progress of diverse marginalized populations, including those with disabilities, children of nomad populations, unregistered migrants and urban slum dwellers. wide_logoThe World Inequality Database in Education, developed by the EFA Global Monitoring Report, presents an innovative way of showing progress in education by select sub-groups over time drawing together different sources of data, including DHS, MICS, national household surveys and learning assessments. It draws attention to unacceptable levels of education inequality across countries and between groups and age cohorts within countries, albeit with data gaps due to limited country coverage or infrequent intervals in data collection. But it also reminds us of the gaps in getting a global and updated picture, which is essential post-2015 if we are to ensure no-one is left behind. These gaps can also be filled with the help of coordination and better financing.

A second theme in Ban Ki-moon team’s consultation was how to use data and for what purposes. The first question about use refers to the accessibility, openness, protection and accountability of data, and is a question particularly relevant for the education sector. Many countries carry out household surveys, for example, but do not make the results or the data public. Paris21 is doing commendable work on this matter, but countries need to do more to promote the availability of data and encourage their use. We are not alone in feeling that the use of data must be a key part of any so-called revolution if it is to be in the service of all people.

Credit: © BRAC

Credit: © BRAC

Thirdly, the consultation asked how we can improve data systems. This is another key issue. It is clear that data is not coordinated efficiently in a way that helps address gaps in data: there is a lack of common standards and problems of timeliness persist. For example, there’s been little coordination in identifying countries for which we have no globally comparable information on education. This should be prioritized. In addition, as identified in a 2009 International Household Survey Network report, there should be a core minimum of essential questions on education across all national or international surveys to promote such comparability. We believe that standard modules on issues like literacy and skills should be developed and made available for use in all current household surveys.

There is also insufficient communication between surveys in different sectors. This limits the ability to draw associations and identify important correlates of inequity. For example, health surveys include limited information on education and so on.

We don’t need a revolution, therefore, but we do have our work cut out. We can improve our knowledge of progress in education at a relatively low cost just by doing better on the basics.

Stay tuned… There’s much more to come.

 

This entry was posted in Developed countries, Developing countries, Governance, Post-2015 development framework, technology, Uncategorized. Bookmark the permalink.

3 Responses to Relevant data for education post-2015 need not be ‘big data’

  1. Pingback: Relevant data for education post-2015 need not be ‘big data’ - Mtemi Zombwe

  2. Clinton Robinson says:

    Thank you for posing this question! As we move into a new set of international goals which apply universally across all countries, the question of how to monitor them is critical. In education, your plea to do the basics better is welcome, with hard work to be done on finding ways to measure changing approaches, such as the ‘literacy continuum’ you mention. Part of the problem in considering the ‘data revolution’ is that some may make assumptions that because we CAN now collect and process untold gigabytes of information, we SHOULD probably do so. The antidote to any headlong flight into bigger and better data is contained in two aspects you mention: use/purpose, and coordination.
    The question of the use and purpose of data should be asked before data systems are designed or upgraded: who will use the data? Are internationally comparable data necessary? For which indicators? For whom? Will the data in fact be used at all? Is there enough or too much data for the purposes envisaged? Who will have the capacity to access or process data and at what levels – equipment, skills, training? Who will be included or excluded from decision-making by the use of lots of data? What will be the marginal cost of obtaining and processing ever more data? These are questions for both the professionals and the politicians of education, certainly not for the guardians/experts of data alone.
    Coordination: this will always involve the hard work of forging and maintaining partnerships, thus defining and re-defining areas of common interest, strategy and effort. The relational dimension is crucial – as in all partnerships – and will require serious investment of time and persistent dialogue. A real sense of what data matter to whom and how each party intends or hopes to use the data will go a long way to promoting more transparent approaches to data collection and treatment – for purposes defined by all those with a stake in the decisions which data will inform. A personal observation to conclude: it seems unfortunately to be true that greater resources are found for developing and refining the methods and means of data collection and processing/analysis than for the broad and sustained dialogue upon which the ultimate benefits of data use depend.

    Like

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