The 12 papers in the special issue reveal a need to prioritise mastery of foundational skills for all children in order to steepen learning profiles and ensure children continue learning and reach their full potential. They also point to the need for systemic change that ensures a high-quality education for all children.

In their overview of the special issue, the three editors identified five key implications of the work included in it:

1. “The learning crisis is worse than we think it is, and more years of schooling will not resolve it.”

   While it seems natural to assume that more years of schooling will result in more learning, flat learning profiles show that this is not necessarily the case. Once learning trajectories have become flat, indicating that learning has stagnated, additional schooling has a limited effect on learning outcomes unless systemic improvements to learning are also implemented.

   Read more:

   A structured model of the dynamics of student learning in developing countries, with applications to policy

   Accounting for repetition and dropout in contemporaneous cross-section learning profiles: Evidence from Rwanda

2. “Achieving equitable outcomes requires raising the floor on learning levels, starting with foundations.”

   It seems natural as well to think that achieving equal learning outcomes for all groups within a country (for example, all poor children reaching the same learning levels that rich children reach) would be the path to equity in education systems, but the papers find that this also is often not the case. Why? Because in many countries, even the highest-performing children are not reaching the level of learning they deserve. In fact, the papers find that focusing on reaching global targets for foundational skills has a greater equitable effect.

   Read more:

   Eliminating global learning poverty: The importance of equalities and equity

   Learning equity requires more than equality: Learning goals and achievement gaps between the rich and the poor in five developing countries

   Looking beyond changes in averages in evaluating foundational learning: Some inequality measures

3. “Girls’ education—including schooling and learning—matters for later life outcomes, but a focus on gender will not be sufficient to realize the full benefits of girls’ education.”

   Building on the first two points, the papers find that girls’ schooling cannot be assumed to mean girls’ learning—but in fact literacy is powerfully beneficial to girls, and that is another reason why foundational skills are so crucial.

   Read more:

   Girls’ schooling and women’s literacy: schooling targets alone won’t reach learning goals

   Aiming higher: Learning profiles and gender equality in 10 low- and middle-income countries

   Effective investment in women's futures: Schooling with learning

4. “Improvements are needed in the early primary years to enable later learning.”

   Learning profiles are a unique tool because they track learning starting in the early years, while many assessments only measure learning at one point in time later in schooling. Early mastery of foundational skills is crucial because once children’s learning levels have fallen significantly behind the curriculum, it becomes nearly impossible to catch up. Furthermore, ensuring deep conceptual mastery is important as learning profiles reveal that current learning all too often is fragile, with learning progression frequently followed by stagnation or reversals as children have not sufficiently mastered the content.

   Read more:

   Schooling progress, learning reversal: Indonesia’s learning profiles between 2000 and 2014

   New evidence on learning trajectories in a low-income setting

5. “A variety of data sources can be used to analyse, diagnose, and inform approaches to improve learning.”

   Many of the papers in the issue demonstrate that learning profiles can be constructed from a variety of learning data, including non-traditional sources of learning data. It’s essential to glean the most knowledge we can from the range of data that is available.

   Read more:

   Assessing the assessments: Taking stock of learning outcomes data in India

   Average vs. distributional effects: Evidence from an experiment in Rwanda