How much will it cost to (frugally) universalize digital learning?

• In Event: Financial Aspects of Education

Proposal

With the onset of the COVID-19 pandemic, digital learning became essential for many governments, schools and families. The digital learning strategies developed during this time have also built preparedness and resilience for future COVID-like shocks. However, the global cost of universalizing quality digital learning remains a puzzle, making it difficult to decide on a reasonable ask or to monitor funding and spending. This is further complicated by the expected tightened spending on education due to economic downturn and increases in spending on health and social protection.

In light of these concerns, this study explains a fast-track costing for frugal universalization of digital learning by 2030, specifically the digital learning solutions (DLS), plus devices to enable those DLS. Connectivity and data usage are equally critical for digital learning and can be much more costly than DLS and devices, but here we focus on what the education sector can lead on. It costs the gaps between the present situation and the ideal state of universal access, i.e., what the market has not done yet.

The cost estimate for DLS and devices is made under the assumption that (a) connectivity and power supply will be improved in parallel, (b) a global prototype will be developed for lowering the cost of devices for the most marginalized, (c) a zero or subsidized rating for digital learning- related data usage, and (d) out-of-school children and youth will also be allowed access digital learning. Apart from the above assumptions, it is important to note that an investment in DLS and devices does not replace other ongoing or planned education investments, such as back-to-learning, citizenship education, etc.

For each country, the cost for DLS is comprised by the costs for (a) content identification, curation and scaling-up, (b) upskilling teachers/facilitators in digital learning and pedagogies, (c) building policy and institutional capacity, (d) mobilization of users and teachers/facilitator and (e) data and analytics. This is aligned to the UNICEF Initiative of Reimagine Education, which aims at ending the learning crisis by enabling every child and young person to access to world-class digital learning solutions.

Compared with the costing for DLS, the costing for devices is more straightforward. Costed at US$200 on average as default, a digital learning device can be a phone, tablet or laptop. Since it is financially unrealistic to provide everyone with a device, the proposal aims for at least one device for every ten unconnected children and young people, and at least one device for every four teachers or facilitators serving them.

It is easily understood that costing for digital learning will need to take into consideration demographics, the economy and the education system. For example, a larger population will mean a greater degree of complexity in content deployment and thus an increased cost. In addition to these conventional factors, three more specific and relevant factors are reflected in the costing model. They are (a) learning poverty, proxied by World Bank’s learning poverty index; (b) digital divide, proxied by ITU’s internet user Indicator, and (c) engagement of young people that are both beneficiaries and facilitators-- young people will be instrumental in bringing the digital learning to scale, make it relevant for users, and ensure that it reaches the most marginalized.

In light of the rationale outlined above, we estimate a minimum of US$46.4 billion will be needed by 2030 to provide DLS and necessary devices to additional 1.8 billion children and young people for the universalization of digital learning. Of which, US$31.7 billion needs to be spent on reaching additional 1.4 billion children and young people in the 79 LI&LM countries. Three out of each five dollars are supposed to be spent in either South Asia or Sub-Sahara Africa, where host a large young population yet to be connected.

Of the US$46.4 billion, US$8.4 billion is to be spent on DLS. of which US$4.3 billion for LI&LM countries. Without empowering and mobilizing young people, the cost for digital learning solutions could be high at US$36.7 billion or four times of the current estimate. The cost for devices is US$38 billion, with almost three fourth (US$27.5 billion) of which to be spent in LI&LM countries. Under different scenarios, the cost to reach an additional child or young person by 2030 ranges from US$22 to US$31, with the potential for lower costs if implementation is at scale. When saying spending US$46.4 billion to reach additional 1.8 billion children young people, that is US$25 for every additional beneficiary globally.

US$46.4 billion, approximately the GDP of Eswatini, is not a small investment, but certainly achievable, and quite profitable. To universalize digital learning by 2030, the cost of US$46.4 billion means an annual spending of 4.6 billion. It accounts for less than one third of global education development assistance in 2018, or a tiny share of the estimated US$346 billion (2012 US$) post-COVID domestic education financing resources in LI&LM countries. Even if we boldly expand the cost estimate, say 15 times, to cover connectivity and data usage that are not assumed to be mostly paid by non-education budget, the annual ask is still lower than the expenditure on education by the government of India.

More importantly, compared with the estimated US$10 trillion economic loss (present value in 2017 PPP) over the coming generation as a result of pandemic-related school closures, the return to investment can be tremendous even if digital learning only mitigates a fraction of the economic loss.

The costing model and figures proposed by this study can be used to suggest financial input for global digital learning initiatives, such as the Reimagine Education. The same model is also capable of automating country-level ‘guide price’ as a starting point for more localized and precise costing, provided that the assumptions set for this model (e.g. concurrent improvement in connectivity) are valid for the country.

(Citations omitted)

Author

• Haogen Yao, UNICEF