In the second of our guest blogs as part of a series on the five proposed outcome-oriented post-2015 global education targets, Ray Adams of the Australian Council for Educational Research (ACER) examines the challenges involved in reaching agreement on how to measure the second target proposed by the EFA Steering Committee:
“By 2030, all girls and boys complete free and compulsory quality basic education of at least 9 years and achieve relevant learning outcomes, with particular attention to gender equality and the most marginalized.”
In the discussion of post-2015 global education goals, there appears to be general agreement that the assessment of learning outcomes must have a place alongside ensuring equitable access to good quality education. The EFA GMR has calculated that there are 250 million children not learning. It is now time to start looking at these figures in more detail, and across time. We need be able to identify exactly how many children around the world face compromised life opportunities because they do not possess foundational reading and mathematics skills.
Before we venture down this path, however, we need to consider two issues carefully: how to define foundational reading and mathematics skills, and how to use the assessment data that are collected.
At the core of these issues is the development of internationally accepted learning metrics. A learning metric, which describes what learners know, understand and can do in a particular subject area or domain at different stages of their development, is a basic tool for reporting progress in learning. Teachers and curriculum developers can use this information to help plan their pedagogy and materials development.
Learning assessments that repeatedly show that students are performing well below expected or desired levels are seldom helpful, however. In our work at ACER, we are often asked to develop assessments of whether students are achieving the standards specified in a curriculum? Sadly, all too often, the answer is that many students are falling well short of expectations. It is usually difficult to know what to do with such information.
As an alternative, is identify where students are in their progress along well-defined learning metrics. This is the most valuable thing we can do with learning assessment, since the core of developing strategies for improving learning is understanding where students are in their educational progress, not stating how far they are away from where you would like them to be.
A further benefit of learning metrics is that they can reveal information about growth for all learners, regardless of their starting points or backgrounds, which should be a goal for all education systems and practitioners. This is the core of an equitable approach to education. Gathering data about growth over time – for individual students and cohorts of students – is a central element in monitoring educational outcomes.
The UNESCO Institute for Statistics (UIS) with the support of ACER and others, has begun to develop learning metrics for reading and mathematics to monitor global learning outcomes and for use in national and international learning assessments. This work presents several challenges, many of them technical, but they are surmountable. Perhaps the greatest challenge will be achieving the close cooperation required to construct, validate and implement the metrics.
Key players from around the world need to contribute and be willing to compromise in the process of drafting learning metrics that are fit for purpose. In the case of mathematics, a description of the development of early mathematical concepts, knowledge and skills has already been drafted by the Working Group on Numeracy Indicators, established by the World Bank and UIS and coordinated by the German development agency GIZ.
The next main step will require participation and support from assessment programmes such as PASEC, SACMEQ, LLECE, PILNA, TIMSS, PIRLS, and many others deemed relevant in a process of validating the metrics.
This is an excellent opportunity for the learning assessment and educational development communities to work together. Effective collaboration and sharing of knowledge at this stage will lay the foundation for a system that supports all countries in their efforts to measure their progress towards achieving a post-2015 learning goal.
– Read the third in this series by Bryony Hoskins on how can we measure global citizenship skills post 2015.
I would also be interested to know how it is envisaged that this data-gathering exercise will deal with bilingual contexts. In particular:
a) how the data will be gathered in a wide range of first languages, these being the languages in which learners in many contexts acquire subject concepts in pre-primary and lower primary education
b) how data gathered in a learner’s second language – for example after a switch of medium of instruction at say years 3-4 (but also in cases where the switch occurs earlier, or where school learning starts in the second language) – will be interpreted. Assessment in a second language notoriously distorts the picture of a learner’s actual conceptual achievement and can seriously under-represent what a learner knows. This also makes comparison across cohorts who are learning in first and second languages very unreliable.
I think it is the first language which is important as the interest should be in measurement of comprehension and expression rather than proficiency in a particular language.
The UNESCO World Inequalities Data Base on Education (WIDE) has recently added language of instruction to gender, poverty and rural or urban location to its invaluable disaggregated country analyses (http://www.education-inequalities.org) but continues to omit children with disabilities who make up one third of the world’s out of school children (see today’s post in response to the first article in this series.
The necessity for data on language of instruction is another example of lack of co-ordination between the increasing number of organisations who are now developing indicators for monitoring post-2015 Goals and the apparent absence of oversight by the UN to ensure that these indicators match the UN commitment to the reduction of inequalities arising from poverty and exclusion.