The United Nations’ Sustainable Development Goal (SDG) for education calls for learning for all. This includes ensuring that, by 2030, all students achieve relevant learning outcomes by the end of their primary and lower-secondary schooling. An important way to measure the attainment of this target will be to look at the percentage of children in each country achieving- at the very least- “minimum proficiency” on standardized math and reading tests.
"Digitale Teilhabe für alle" (digital participation for everyone) was the theme of last week's Volkshochschultag 2016, an international conference convened in Berlin by the German Adult Education Association (DVV) to explore the impact and consequences of the increasing use of digital technologies in education around the world, especially as they relate to equity and inclusion. "Does digitisation provide an opportunity for educational justice or does it strengthen the unequal access to education even more?" This question (which admittedly flows off the tongue a little better in German than it does in English) animated a related debate (in which I participated) on the last day of the conference.
In support of my pithy, one word response to this question (an enthusiastic and deliberately argumentative ja!), I drew heavily on the 2016 World Development Report, which the World Bank released earlier this year. This widely read, 'flagship' annual World Bank publication explores a topic of broad relevance in the fields of international development and development economics. The 2016 report, Digital Dividends [pdf, 10.8mb), examines the impact that the Internet and mobile networks are having (and not having) around the world.
As a primer on the uses of ‘informational and communication technologies for development’ (what’s known as ‘ICT4D’ by those in related fields who like acronyms), the 2016 World Development Report is quite comprehensive. Surveying and exploring how ICTs are impacting fields such as agriculture, finance, government services, education, energy, the environment and healthcare (and many others), ‘Digital Dividends’ is a World Bank report written for people who don’t normally read (or perhaps even care about) World Bank reports.
It is relatively catholic in its worldview, although not surprisingly there is a decided focus on things the Bank cares about (e.g. economic growth, jobs), but thankfully in language a bit more accessible than what one often finds in publications put out by an institution which employs over 1,000 PhD economists. Happily, there’s not a single mention of a ‘production function’, for example; and I really like the cover!
But I don’t mean to ‘bury the lede’, as journalists say. Here, quickly, are the main messages from the 2016 World Development Report:
With almost half of its population living in urban areas, Senegal is ahead of Sub-Saharan Africa’s average urbanization rate of 40%. Senegal’s urban population has almost doubled in the last few decades, rising from 23% in 1960 to 43% in 2013, and is projected to reach 60% by 2030. This growth comes with immense challenges, but also constitutes an opportunity for Senegalese policymakers to structurally transform the Senegalese economy.
Around the world, 30 percent of the world’s burden of disease is estimated to be caused by conditions requiring the care of a surgeon. Such conditions are estimated to cost low- and middle-income countries up to USD 12.3 trillion in lost economic output by 2030. Moreover, 81 million individuals face financial ruin due to expenses incurred while receiving surgical care each year.when they need it. The impact of surgical disease is not trivial;
The delivery of surgery is critical for the realization of many of the Sustainable Development Goals: Good health and well-being (Goal 3); No poverty (Goal 1); Gender equality (Goal 5), and Reducing inequalities (Goal 10).
Describing access to surgery as a treatment modality or platform of care, with relevant country-level data requires a rigorous deconstruction of the components of access upon which national governments can intervene. To this end, Dr. Jim Kim challenged the surgical community in 2014 to develop surgical indicators, along with “time-bound targets” to which the world can aspire.
A couple of months ago, I visited a few tertiary colleges affiliated with the National University in Bangladesh while preparing the College Education Development Project which aims to strengthen the strategic planning and management capacity of the college subsector and improve the teaching and learning environment of colleges. Almost two-thirds of all tertiary students in Bangladesh are enrolled in these colleges, making them the largest provider of higher education in the country.
World Bank report on education in Bangladesh
A recent World Bank report estimates that around 1.6 million tertiary students in Bangladesh are enrolled in around 1,700 government and non-government colleges affiliated under the National University. This piece of information underpins a huge economic opportunity in context with Bangladesh’s quest to become a middle-income country over the next few years. There is a strong demand for graduates with higher cognitive and non-cognitive skills and job-specific technical skills in the country. This requires an improvement in the quality and relevance of tertiary education to ensure graduates have more market relevant skills. The National University student enrolment size combined with its sheer number of colleges network all over the country make it the critical subsector for making a qualitative dent in the higher education system.
This is at the geeky, number-crunching end of my spectrum, but I think it’s worth a look (and anyway, they asked nicely). The 2016 Multi-Dimensional Poverty Index was published yesterday. It now covers 102 countries in total, including 75 per cent of the world’s population, or 5.2 billion people. Of this proportion, 30 per cent of people (1.6 billion) are identified as multidimensionally poor.
The Global MPI has 3 dimensions and 10 indicators (for details see here and the graphic, right). A person is identified as multidimensionally poor (or ‘MPI poor’) if they are deprived in at least one third of the dimensions. The MPI is calculated by multiplying the incidence of poverty (the percentage of people identified as MPI poor) by the average intensity of poverty across the poor. So it reflects both the share of people in poverty and the degree to which they are deprived.
The MPI increasingly digs down below national level, giving separate results for 962 sub-national regions, which range from having 0% to 100% of people poor (see African map, below). It is also disaggregated by rural-urban areas for nearly all countries as well as by age.