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How the SDG 4.1.1 Framework and Learning Poverty Can Help Countries Focus Their Education Policy Response to COVID-19

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João Pedro Azevedo, Lead Economist, Education Global Practice, World Bank Group and Silvia Montoya, Director, UNESCO Institute for Statistics (UIS)

Most governments and development partners are working on identifying, protecting, and supporting learning of the most vulnerable members of the COVID-19 generation. In this blog, we examine how the SDG 4.1.1 framework and the concept of learning poverty are well positioned to help countries understand and act on the impacts of COVID-19 on schooling and learning.

From the minimum proficiency level to a measure of learning deprivation

In October 2018, the international community agreed to be deliberate about tracking progress in learning of students using a global standard. The minimum proficiency level (MPL)­ agreed through the Global Alliance to Monitor Learning offers a unique benchmark to help countries and development partners work together to monitor and improve learning for these students that are falling behind. The interactive visualization linked to in the image below (Figure 1) allows you to explore the data used to monitor this SDG, using both the GAML MPL as well as different minimum proficiency levels by interacting with the slider.

Figure 1 shows how SDG 4.1.1. can be used to generate focus on students below the minimum proficiency level (MPL)

Learning poverty: a multidimensional indicator for the education sector

In October 2019, the World Bank and the UNESCO Institute for Statistics (UIS) launched a new multidimensional indicator called learning poverty. It is based on the notion that every child should be in school and be able to read an age-appropriate text by age 10.[1] This formulation reflects the aspiration and serves as an early warning indicator of Sustainable Development Goal (SDG) 4 that all children must be in school and learning[2] and builds on two deprivations.

Learning poverty (and Indicator 4.1.1 on learning deprivation) has many desirable characteristics, including simplicity and focus on those in the bottom of the learning distribution (for a longer discussion on some of the properties of the learning poverty measure please see a recent paper). It brings together schooling and learning indicators, as it combines the share of primary-aged children out-of-school who are schooling deprived (SD), and the share of pupils below a minimum proficiency in reading, who are learning deprived (LD). This measure implies that both “more schooling”, which by itself serves a variety of critical societal functions, as well as “better learning” which is important to ensure that time spent in school translates into acquisition of skills and capabilities.

Figure 2 provides an animation which numerically and visually illustrates the concept of learning poverty

The learning poverty indicator is calculated as follows:

LP = [LD x (1-SD)] + [1 x SD]

LP = Learning poverty

LD = Learning deprivation, defined as share of children at the end of primary who read at below the minimum proficiency level, as defined by the Global Alliance to Monitor Learning (GAML) in the context of the SDG 4.1.1 monitoring

SD = Schooling deprivation, defined as the share of primary aged children who are out-of-school. All out-of-school children are assumed to be below the minimum proficiency level in reading.

By construction, learning poverty can be affected by changes in its two dimensions: (i) learning deprivation as the share of students below the minimum proficiency threshold improves or worsens, or (ii) schooling deprivation as access or age-grade distortion changes due to shocks or policies.

While schooling deprivation can be directly observed depending on whether the child is enrolled or not enrolled in school, learning deprivation cannot be directly observed, and is measured through standardized learning assessments using SDG’s definition of minimum proficiency level, where reading proficiency is defined as:

“Students independently and fluently read simple, short narrative and expository texts. They locate explicitly stated information. They interpret and give some explanations about the key ideas in these texts. They provide simple, personal opinions or judgements about the information, events and characters in a text.” (UIS and GAML 2019)

 SDG 4.1.1, learning poverty and COVID-19

The SDG 4.1.1 framework and the learning poverty measure can help monitor and guide national conversations on the impacts and education policy response to COVID-19 by:

Reaching agreement and clarity on a minimum proficiency level: The GAML process, through the Global Proficiency Framework, has produced detailed documentation about the competences expected to be mastered at the minimum proficiency level (MPL). All this material can be used to inform a national conversation on what elements of the curriculum could be prioritized as the system reopens.

Focus on children falling behind: SDG 4.1.1 uses the MPL to measure the share of students above this threshold reflecting the aspiration that all children must be performing above the MPL. However, during a time of crisis and shock, such as COVID-19, countries might want to pay special attention to those students left behind. The latter is precisely what the measure of learning deprivation used in the learning poverty measure does.

Monitoring multiple dimensions of education:  As schools close, students will lose learning. However, for certain sub-populations, COVID-19 might push students out of the educational system, increasing drop-out rates; and in certain countries, due to a choice of policies and practices, might increase repetition and age-grade distortion. Moreover, if school deprivation increases, through an increase of drop-out or of the age-grade distortion of previously low-performing students, it is statistically possible that average learning scores might increase or at least not fall as much after COVID-19. This misleading result can be avoided if effects are monitored using a measure which is simultaneously sensitive to changes in learning and access to schooling.

COVID-19 has led to an unprecedented crisis within an already existing global crisis of the education system in the developing world. The ability to use it as an opportunity to build back better will depend on the quality of our understanding of its effects. For that, both data and our choice of measures will be equally critical.

[1] World Bank 2019.

[2] SDG 4 makes this commitment: by 2030, signatories will “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all.” The goal’s target 4.1 is to “ensure that all girls and boys complete free, equitable, and quality primary and secondary education leading to relevant and effective learning outcomes.”

Bridging CESA 16-25 and SDG 4: Using Regional Benchmarks to Meet Education Objectives

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By Silvia Montoya, Director of the UNESCO Institute for Statistics (UIS) and Daniel Capistrano, University College Dublin

This International Day of Education, the impact of COVID-19 on education is top of mind and finding solutions to revitalize learning is a priority, now more than ever. The UNESCO Institute for Statistics (UIS) is working with regional organizations and education partners to expand the global focus on benchmarking for the Sustainable Development Goals for education (SDG 4) so that regions and countries have more manageable, annual objectives.

With just a decade remaining to achieve SDG 4, it is imperative that all countries have the means to monitor progress and to plan necessary changes for the future. As the custodian of SDG 4 data and the lead agency providing internationally comparable and quality education data, the UIS has been working to help countries deal with this challenge.

One of the most effective ways of achieving the Agenda 2030 is by connecting existing efforts. The Africa Regional Report is a product of this collaborative strategy. Worldwide, there are several regional or sub-regional organizations that produce data and follow the progress of education policies based on common goals. Their transnational commitments require national and regional coordination and monitoring mechanisms to identify progress and obstacles. At the same time, they have articulated – or begun to articulate – their regional objectives with the Education 2030 Agenda.

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Using Household Surveys to Achieve the SDG 4 Objectives of Inclusivity and Equity

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By Friedrich Huebler, Head of Education Standards and Methodology at the UNESCO Institute for Statistics (UIS)

It is not enough to simply collect data. Data that are useful for monitoring progress towards Sustainable Development Goal 4 on education must be of high quality and comparable across countries. But collecting the data across a wide range of indicators has strained the data collection capacity of many Member States. At the same time, additional reporting needs brought on by COVID-19 have added further pressure to produce data as evidence for remedial action once schools fully re-open.

As the custodian agency for SDG 4, the UNESCO Institute for Statistics (UIS) works with countries to build their capacity to collect, produce and disseminate the data for monitoring progress towards international goals and for designing appropriate interventions, all while trying to mitigate the demands that this entails.

With this in mind, today the UIS is launching the 2020 SDG 4 Data Digest. This year, the Data Digest focuses on using household surveys to improve the scope of data collection while filling some of the gaps in administrative data.

To do this, the Data Digest explains the need for more and better data, serving as a “how-to” manual for ministries of education, national statistical offices and other education sector stakeholders. Readers will find information on everything from planning and design considerations for a household survey, to tips for writing compelling and effective questions, an interviewer’s check list of do’s and don’ts, the pros and cons of various modes of survey administration, along with implementation details like the most appropriate kind of field materials. The Data Digest also makes suggestions on how to communicate data findings.

In short, the 2020 SDG 4 Data Digest is the go-to source for a succinct overview of creating and implementing a household survey.

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Prepared for the Future: A New Indicator That Combines Completion with Learning

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By Silvia Montoya, Director, UNESCO Institute for Statistics (UIS) and Manos Antoninis, Director, Global Education Monitoring Report

New global indicator will provide a simple, comprehensive measure of progress towards the education goal, SDG4.

The Sustainable Development Goal (SDG 4) for education recognizes that all children deserve, and have the right to, a quality education. Over the last three decades, enrollment has risen to historic highs, though school disruptions and the economic implications of COVID-19 will offset some of these gains. But enrollment is only a part of what children need. For children to be fully prepared for the future, they need to complete their education, and emerge having learnt at least the basics. The new global indicator will combine all these critical factors to provide a snapshot of progress towards SDG 4.

Completing and learning are critical elements of a quality education

Unfortunately, in some of the poorest regions where children are most in need of a high-quality education to get ahead, poor learning outcomes often result in higher drop-out rates with large numbers of children not completing school at all – or completing it when more than five years older than the intended graduation age for that level. In sub-Saharan Africa, for example, where 82% of primary aged children are enrolled in school at the right grade for their age, just 62% graduate from this level on time. When children don’t finish school, it is hard, if not impossible, for any more learning to happen.

Even where education is free, poor families still pay for books and uniforms, and there is the perceived “opportunity cost” of lost income or help with household chores, while children are in school. If parents don’t see a pay-off from their investment in education, children can be pulled out of school before completing a level, or when transitioning between levels, from say, primary school, to lower secondary.

Introducing the new indicator: Prepared for the Future

To underline the need for countries to prioritize school completion, the UNESCO Institute for Statistics (UIS), working through the Global Alliance to Monitor Learning (GAML), is proposing a new, holistic, indicator that will track both completion and learning combined. The aim is to ensure that global leaders and education policy makers have the evidence they need to zero in on where they stand on their SDG 4 commitments. With ten targets and 42 indicators in the monitoring framework for SDG 4, some might argue that it is hard to quickly grasp where countries stand in their progress towards the goal. With so many touch-points, it risks calls for change being watered down. This new indicator will hopefully answer these concerns, providing a simple rallying reference point for all education actors to lobby for improvement, ensuring all children are prepared for the future.

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Recalculating Proficiency in Schools: COVID-19 Related Learning Losses and Dropping Out

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Traditional ways of measuring educational proficiency, based on assessment results and the percentage of children enrolled in schooling, may not be as effective a measurement while COVID-19 impacts upon attendance rates.

Analysts working with SDG indicators on learning proficiency, in particular Indicator 4.1.1, would in many cases be familiar with a formula such as the following:

The percentage of enrolled learners who are proficient, S, is typically known from assessment results. The percentage of children of the age of the grade in question who are not enrolled, N, is typically known from household data. P is what planners are ultimately interested in: the percentage of the relevant age cohort in the population who are proficient. While there is some ambiguity over whether Indicator 4.1.1 refers to S or P, P is clearly important and must be monitored.

The above formula assumes that non-enrolled children do not reach minimum proficiency levels, following the approach taken in UIS (2020) and UIS (2017). The relationships can be illustrated as in the following graph, which is based loosely on levels of learning proficiency and the out-of-school problem in developing countries. Here P is a function of S and N, according to the above formula. 

In the context of COVID-19, sudden declines in enrolment, meaning N rises, and declines in proficiency in the population due to disruptions in schools, meaning P drops, are possible. In examining the effects on the three statistics P, N and S, it is important to remember that N and S influence each other. Assuming that children who drop out of the schooling system are the academically weakest learners, an assumption that is likely to hold for a number of reasons, one can expect S either to rise or decline, depending on the magnitudes of the two effects: dropping out of school and learning losses. If one has estimates of P and N, then the new S is calculated according to the following transformation of the previous formula:

To illustrate the ambiguity, we can imagine learning losses resulting in a drop in P from the 35% seen in the graph to 33%. If out-of-school N increases from 5% to 9%, S declines from 37% to 36%. However, if N displays a larger increase, from 5% to 13%, then S displays an increase from 37% to 38%. Even with learning losses in the population of a specific age, if enough learners drop out, and we assume that these learners are those who struggled most academically, then assessment systems may in fact detect an increase in the percentage of proficient learners.

Clearly, planners need to be fully aware of these relationships. Above all, the first formula above should not be used to conclude that more out-of-school children on its own produces a decline in P. If S was 37% (as in the graph) and then out-of-school N increases from 5% to 13%, one cannot conclude that P drops to 32%. This would ignore the fact that if N changes, S automatically changes too. 

Projections For Learning Proficiency Can Inform Post COVID-19 Educational Strategies

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The UIS will soon be releasing its projections of the impact of COVID-19 on the learning proficiency of children and youth, building upon previous UIS projections published in early 2020, before the pandemic. Projections of this kind are vital and inform the planning conducted by national governments, global bodies, and development assistance organizations. 

The data suggest that the impact of the pandemic on learning occurs through two distinct channels:

  1. Disruption in schooling has denied learners their usual classroom experience with teachers and other children. Disruptions have been particularly serious for younger children, who are most in need of contact teaching, and often receive meals through the school. These needs are felt especially in developing countries.
  2. The economic shock of the pandemic has put education budgets under pressure, and worsened household poverty. These factors also impact negatively on learning. 

The findings suggest that the effects of school disruptions on learning proficiency could be felt for many years, even after the pandemic is declared over. In future years, however, as children who did not directly experience the disruptions enter the education system, the longer-term budgetary and poverty effects will be of greatest significance. It is important for planners both to mitigate the effects of the disruptions, and to plan for the educational well-being of future age cohorts of children not affected directly by the disruptions. 

Current focus

The following diagram outlines the variety of factors influencing any schooling system’s ability to minimize learning losses: 

This illustrates how future priorities depend to a large degree on the strengths and weaknesses of the schooling system that existed before the pandemic. Systems with effective support and accountability structures, and which had been experiencing improvements in learning proficiency before 2020, are likely to be the most resilient to the shock of the pandemic. 

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The Importance of Monitoring and Improving ICT Use in Education Post-Confinement

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By Silvia Montoya, Director, UNESCO Institute for Statistics; and Alexandre Barbosa, Head of the Regional Center for Studies on the Development of the Information Society, under the auspices of UNESCO, Brazil (Cetic.br).

The global provision of schooling is facing unprecedented challenges as a result of the COVID-19 crisis. Within the span of a few months, 191 countries had closed their schools to deploy social distancing measures in accordance with the World Health Organisation (WHO) recommendations. More than 1.5 billion students from pre-primary to university-level have been affected by these closures, with classroom-based learning interrupted for indefinite periods of time. While some education systems, teachers, students and parents were somewhat prepared to adapt to existing distance learning programmes and platforms, millions were not.

In the context of COVID-19 school closures, paper-based and digital distance education platforms have become essential to the continued provision of education for all. After more than a month of school closures across the world, many students are still struggling with remote learning. Global estimates suggest that 826 million students are without a household computer, 706 million lack internet access at home and another 56 million lack coverage by mobile 3G/4G networks. To better gauge the scope of the impact of school closures and of the ensuing national education responses, a survey of ministries of education developed jointly by UNESCO, UNICEF and the World Bank was recently launched to more accurately inform a collaborative global education response.

Without adequate information and communication technology (ICT) devices, internet/mobile network access, educational resources and teachers’ training, students simply cannot partake in distance education to continue on their learning trajectories. At most risk of being left behind are students from resource-poor areas, remote rural areas and low-income households. In addition, learners with disabilities or those who use a different language in the home than in school will require more individualised support.

Multiple delivery channels are an essential component to reach all children and youth during this pandemic. A recent UNICEF survey found that 68% of the 127 countries were using a combination of digital and non-digital delivery of remote education (i.e. TV, radio and take-home packages). Even before the COVID-19 related school closures, the use of radio, video and television for remote learning has proven to be strong components of well-designed numeracy, literacy and financial education programmes for children, youth and adults living in remote and rural communities. However, the implementation and reach of such programmes require the monitoring and support of trained educators.

Distance learning also requires that school systems consider the needs of parents and guardians who have to step in to facilitate learning to ensure the pedagogical continuity of their children, especially for the children in earlier grades (Grades 1-3) who need more one-on-one support. The ability for parents and guardians to effectively facilitate home-based learning depends on a variety of interacting factors, including their education level, native language and time availability. Understanding parental digital literacy – which could be estimated from SDG 4 Indicator 4.4.1 that assesses ICT skills among youth and adults – is essential for targeting skill support and development for parents. Without ICT skills support for the adults in the home, children from families with poor digital literacy are likely to fall even further behind.

Developing ICT skills to ensure education weathers the storm of future crises

Reports of parents, teachers, communities and networks that have developed innovative and makeshift interventions, such as mobile-based Wi-Fi networks as well as on-demand content and textbooks available in clouds — to broaden digital capacities have certainly sparked optimism. However, these grassroots efforts largely serve as a short-term band-aid solution. Although they are inspiring, more fundamental developments to bolster access to and use of ICT are required – both at home and in schools, and especially for younger learners at the primary and secondary levels where gaps are largest. Hastily put-together remote teaching approaches have not proven to be optimal learning experiences and could be off-putting to some students.

School closures such as those currently experienced by the more than 1.5 billion students worldwide are commonplace in some countries due to natural emergencies, conflict as well as budgetary or labour negotiations. Once schools reopen, building skills and support for distance education in schools so learners can continue learning in the home can help minimise learning interruptions as well as deter learners from leaving school early or dropping out in the event of future crises. In addition, there remains a possibility that the COVID-19 crisis and its ensuing confinement measures may not be short-lived as flare-ups of cases may spark future school closures in certain countries. As some countries begin to reopen their schools, they will need to select innovative remote teaching modalities that blend with face-to-face teaching to ensure that learners are better prepared for future school closures. Thus, given the importance of distance education in the current context and in anticipation of future crises, countries need to take responsibility for monitoring, facilitating and enabling access to ICT in schools as well as in the homes of all learners.

Current measures of ICT availability fall short of capturing the needs in certain countries and regions as they fail to report on factors, such as the availability of electricity (grid- or solar based) and access to computers for pedagogical purposes, which are primary necessities. At a global level, these indicators are needed to monitor ICT use and detect national trends. However, they are not sufficiently detailed or policy-oriented to provide governments with adequate information to improve access to and use of ICT in education as well as sufficient information on teacher training and digital skills. For instance, counting the number of computers per school or per student poorly reflects the use of computers, which may in fact be minimal if these devices are locked in computer labs.

Monitoring ICT use in schools to better inform education policies post-confinement

Reliable data from school-based surveys can provide the quality ICT use data required to better inform education policy and practices, especially in developing countries. Capturing the complex set of factors involved will paint a more accurate picture of what is available and used by both students and teachers. This includes information, such as availability of digital infrastructure; internet connection speed; school activities in which teachers use ICT; training received by teachers to empower them to integrate ICT into their practices; strategies implemented by schools to develop digital skills; and perceptions by principals and teachers on ICT use in education and its barriers. Furthermore, the presence of qualified technical staff (e.g. technicians, librarians) is required to support the use of ICT in schools, including ensuring digital access and ICT learning among teachers.

These indicators and more are proposed in the Practical Guide to Implement Surveys on ICT Use in Primary and Secondary Schools – a joint publication by the UIS and Cetic.br (Regional Center for Studies on the Development of the Information Society). The guide discusses the relevance of survey data on ICT use in schools to inform policymaking and underscores the need for robust data to understand factors that determine equal access to and use of technologies by the teachers, principals, students and their families.

The guide serves as an especially useful reference for government agencies, school authorities and other stakeholders looking to measure ICT access and use in education as it outlines the methodology and steps required to conduct a successful survey (i.e. planning, fieldwork, data processing, reporting and dissemination). This comprehensive document also examines the practical aspects of developing school-based surveys explicitly related to ICT and includes methodological datasheets for 26 core and optional indicators.

As some countries begin to reopen their schools, promoting equity in ICT access and use will continue to be an important factor to consider when addressing educational challenges for disadvantaged schools and learners from vulnerable households. In addition, the availability of computers, tablets, mobile phones and other potential learning devices, along with the provision of internet access in the home, will ultimately determine which children will be able to participate in distance learning and be more likely to complete their education in the event of future school closures.

Bridging the digital divide at home and in schools

Evidence indicates that there is a substantial ‘digital divide’ in access to ICT between countries. For example, according to estimates from the International Telecommunication Union (ITU), 21% of learners in Africa cannot be reached by 3G mobile networks. In terms of internet access, 82.2% of households in Africa lack access in the home (see Figure 1). To bridge the divide and encourage mobile-based education, and in addition to infrastructure investment, lowering the cost to consumers to gain access to online data needs to be considered as these are prohibitive in many countries.

Source: International Telecommunication Union (ITU) 

Under Sustainable Development Goal (SDG) 4 to ensure inclusive and equitable education and promote life-long learning opportunities for all, governments have committed both to increase digital skills and expand ICT infrastructure in schools. To support distance education, schools will need to better equip learners with the skills to migrate onto these online learning platforms. Moreover, closing the ‘digital divide’ will require governments to invest in supporting learners in the early grades of school. In this endeavour, the first step is to map within and between countries where investment is most needed. This requires better measures of access to and use of digital technologies in schools.

The latest UIS data for SDG Indicator 4.a.1 on the availability of electricity, computers and internet in schools for pedagogical purposes indicate that certain regions are behind in their capabilities to support learners. Although sub-Saharan Africa as well as Central and Southern Asia do not have sufficient data for this indicator in lower education levels, there is adequate data for upper-secondary schools. Only about one quarter of upper-secondary schools in sub-Saharan Africa and one-half in Central and Southern Asia are equipped with internet access (see Figure 2). Electricity – another necessity – is also not available equitably across regions and school levels. In sub-Saharan Africa, only 33.8% of primary schools have access to electricity while the same holds true for 57.2% of upper-secondary schools in the region. The situation is bleaker still in the Democratic Republic of the Congo where only 13.7% of upper-secondary schools have access to electricity.

Source: UNESCO Institute for Statistics, SDG 4 Data Explorer (data for the latest available year used). 

Teacher training as part of the solution to closing the ICT skill gap

As noted, beyond the provision of internet access and ICT equipment in education, there is also a need to support learners by building their ICT skills. But what about teachers? During this period of school closures, teachers require training in the use of distance learning platforms to ensure teaching and learning can continue. While some of the 63 million primary and secondary school teachers who were displaced by COVID-19-related school closures have managed to reach students with their existing set of skills and equipment, many have not received basic teacher training. It is therefore disconcerting that most teacher training programmes do not include the use of ICT in education to develop appropriate learning and teaching strategies. In sub-Saharan Africa, only 64% of primary and 50% of secondary teachers have received minimum training. Indicators recommended in the Practical Guide to Implement Surveys on ICT Use in Primary and Secondary Schools can point to specific areas in which teacher training needs to be reinforced to improve ICT skills.

Use of ICTs for education during the COVID-19 crisis and beyond is a reality for which teachers and learners must be better prepared. This crisis marks the time for government-led initiatives for schools to test innovative methods to reach out to students, learn from other countries and incorporate effective approaches into the regular provision of education. Digital technologies need to be integrated within sound learning programmes to create effective student learning experiences. Countries need to make the necessary preparations to better map teaching and learning needs for future crises in education. As a necessary step, this requires collecting robust survey data on ICT use in schools to adequately guide policymaking.

Rethinking Education Post-Coronavirus: Lessons from Spain to Avoid Widening the Socioeconomic Achievement Gap

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By Ana Capilla, Organización de Estados Iberoamericanos (OEI) and UFV;
Jorge Sainz, Universidad Rey Juan Carlos (URJC), Madrid (Spain) and IPR (University of Bath, UK); and Ismael Sanz, URJC, Madrid (Spain)

In a recent post, UNESCO reminded us of the similarity between the learning challenges that fourteenth century societies confronted during the Black Death and the current COVID-19 pandemic. Back then, as William Courtenay remembers, the plague helped develop new ways of teaching and the beginning of the substitution of Latin with popular languages as vehicles to communicate science. Just as that global pandemic marked the beginning of a new world in education, so could the current one if policymakers respond thoughtfully to this education crisis.

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Nurturing Education at Home in the Midst of a Health Crisis: How SDG Indicator 4.2.3 can Help Guide Where More Support is Needed

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By Silvia Montoya, Director, UNESCO Institute for Statistics

In the midst of this global health crisis that threatens lives and containment measures that threaten our ways of living, we are faced with the stark reality that the world we return to will be forever altered. The far-reaching consequences of the COVID-19 pandemic may also jeopardize the hard won gains made in improving global education. 

The country statistics data collected and housed at the UIS has proved crucial in this time of crisis to help us estimate the global scope of the pandemic’s impact on education due to massive school closures. Given the importance of education as the foundation for all development, we must strive to safeguard learning at all ages. Thus, as a response, UNESCO has launched the Global Education Coalition in an attempt to support learning in the home as this becomes the new normal.

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Where Are All the Women in Science and Research?

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By Rohan Pathirage, R&D statistician for the UNESCO Institute for Statistics (UIS)

On the International Day of Women and Girls in Science, you could be forgiven for asking: just where are all these women and girls? They are there if you look but they remain the exception at the very highest echelons in science and research. Their rarity may even – on occasion – obscure the critical value of their work. From Marie Curie to Rosalind Franklin, women scientists have often been viewed in terms of their relationships to their male counterparts.

A simple web search on female scientists will yield lists of the ‘17 Famous Female Scientists Who Helped Change the World’ or ‘10 Women in Science and Tech Who Should be Household Names’. But search for ‘the most famous male scientists today and the lists talk about the most ‘influential’ scientists, ‘the top 10 greatest scientists’ – with no mention of the word ‘male’. It simply isn’t noteworthy. Continue reading →