The 21st-century skills gap

Chapter 2

The 21st-century skills gap

An in-depth analysis of performance indicators across 91 countries has found stark differences for different skill types not only across income clusters, as defined by the World Bank, but also within the same income cluster and within countries. While the differences are most pronounced between developed and developing countries, we also found wide variations in performance among high-income countries. In addition, we found differences within countries in terms of performance on foundational literacies versus higher-order competencies and character qualities.

Starting with differences between developed and developing countries, we found that higher-income countries in the OECD – which includes developed countries such as the United States, Germany, Japan and the United Kingdom – tend to perform much better on average across most skills than developing countries in the upper-middle-income group, which includes countries such as Brazil, Malaysia, South Africa and Turkey (see Exhibit 3; Appendix 4 includes the members of each income group). For instance, median performance for upper-middle-income countries in our sample on the 2012 literacy test by the Programme for International Student Assessment (PISA) was 416, while high-income OECD countries scored significantly higher at 499.

Exhibit 3: A wide variation in skills exists within countries and among income groups

Country percentile rank compared to world

Source: World Bank income clustering for 91 sample countries. See Appendix 3 for select indicators behind each skill. Note that for some skills there were very few data points.

While broad differences between high-income OECD countries and upper-middle-income countries can be discerned, it can be much more challenging to draw comparisons between these income clusters and lower-middle and low-income clusters. Virtually none of the lower-income countries take part in comparable tests such as PISA. A high-level analysis of regional tests, such as the Southern and Eastern Africa Consortium for Monitoring Educational Quality (SACMEQ), does allow a ranking comparison inclusive of some lower-income countries for literacy and numeracy (see Appendix 5 for a comparison of data across three tests we used in this report). The analysis confirms that higher-income countries do indeed perform better. However, notable exceptions exist, such as Vietnam, which ranks on par with Germany and ahead of France on literacy, and Tanzania, which ranks ahead of Brazil, Malaysia, Indonesia and South Africa on literacy in our sample. These exceptions show that income is only one of many factors affecting educational outcomes. As such, it is important to holistically evaluate unique country contexts when devising solutions to address skills gaps.

Broad differences in performance based on income make intuitive sense. More surprising are the wide variations in skills performance within even high-income clusters. Explore the interactive map in Exhibit 5 to compare the differences in skill performance between countries and clusters.

As one high-profile example, the United States performs relatively well on most skills when compared with the entire world. But when compared with high-performing peers such as Japan, Finland or South Korea, the United States shows significant gaps in numeracy and scientific literacy. The United States ranked 36th out of 65 countries that took the 2012 PISA mathematics test (with a score of 481) and 28th out of 65 countries on the 2012 PISA science test (with a score of 497), for instance, compared with Japan’s 2012 ranking of 7th in mathematics (a 536 score) and 4th in science (a 547 score).

In addition to gaps found vertically between countries, horizontal gaps also exist within the same country. At an individual country level, a gap exists between foundational literacies and competencies and character qualities such as critical thinking, creativity and curiosity. For example, Poland performs well on a range of indicators representing foundational literacies, even while displaying gaps in critical thinking/problem-solving and curiosity. Similarly, Ireland stands out in terms of foundational skill indicators relative to other OECD countries, but shows gaps when compared to peers on critical thinking/problem-solving, creativity and curiosity.

Some income clusters display strong performance across all skills. For example, Canada, Finland, South Korea and Japan are among the top performers within the high-income OECD group on all skills.

Context matters

Underlying the skills gap are significant macro-level issues that impede learning. These factors include fundamental economic and social problems, such as poverty, conflict, poor health and gender discrimination. Progress in addressing the 21st-century skills gap cannot be made without tackling these basic elements.

In addition, we identified four key country-level educational areas in which many countries outperform or underperform (see Appendix 3 for the indicators used to measure them and the challenges in doing so):

  1. Policy enablers: Standards that govern K-12 education
  2. Human capital: Teacher quality, training and expertise
  3. Financial resources: The importance of education in public budgets
  4. Technological infrastructure: Access to new digital tools and content via the internet

Deficiencies in each of these areas disproportionately affect low-income countries. Exhibit 4 explores how five income groups rate on these educational factors. For example, lower-income countries rank in the bottom quartile of our sample (the median rank is in the 26th percentile) in terms of the number of students per trained teacher in primary school – a proxy measure of human capital – compared with high-income countries, which tend to have many more trained teachers (the median rank is in the 86th percentile). Similarly, wide disparities can be seen in the other indicators.

The issues also manifest themselves in different ways: some educational systems face high teacher absenteeism, while others have too many teachers who have not mastered the content they are required to teach, for example. Each country and culture therefore requires unique solutions.

Technology has a role to play in addressing some of these contextual factors. The Varkey Foundation, through its Making Ghanaian Girls Great (MGCubed) project, is an example of an organization working around the constraints of human capital with the help of technology.[6] Since 2013, the project has established a network of 72 state schools in two regions of Ghana to improve access to education through satellite-based interactive distance learning. The project provides daily English and mathematics classes and aims to reach more than 3,000 marginalized girls. The project is supported by the UK government’s Department for International Development, as part of its Girls’ Education Challenge.

MGCubed equips each classroom with a satellite dish and technology hardware powered by solar energy to combat the challenges of poor electricity and internet infrastructure. Through a high-speed satellite broadband connection, the project connects each classroom to a professional TV studio based in the capital city of Accra, where master teachers deliver lessons across multiple classrooms to up to 1,000 students at a time. The interactive system enables master teachers to take questions in real time from students working with their own teachers, who facilitate the learning in local classrooms.

The project helps address endemic problems with teacher quality and absenteeism, which can be as high as 35% in some regions of the country, according to the organization. Local teachers in each of the network schools also receive technology and teacher training to participate in the programme. Over time, the project aims to instill some of the teaching practices modeled by the project’s master teachers in local teachers.

The MGCubed project’s results will be tightly monitored – the pilot is undergoing an independent randomized control trial to evaluate its outcomes and effectiveness – providing intelligence about the extent that distance-learning projects can transform the prospects for girls who participate, as well as whether it can be replicated across Africa.

Exhibit 4: Four key factors are holding countries back

Country percentile rank compared to world

Source: World Bank income clustering for 91 sample countries. See Appendix 3 for select indicators behind each skill. Note that for some skills there were very few data points.

  1. ^ The Varkey Foundation is the philanthropic arm of GEMS Education, which designed the pilot.

Exhibit 5: Wide gaps exist between countries and among skills

Country percentile rank compared to world

  • 0%
  • 100%
  • 0%
  • 100%