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Building More Equitable Education Systems With The Help Of AI

In the aftermath of Covid-19 - the philanthropic sector has an outsized opportunity, as well as responsibility, to help make up for the losses sustained by the educational sector. AI is already supporting education non-profits in their efforts to provide students with the skills they need for success in college and beyond, and might be the key to enabling lasting change in educational systems worldwide.

In a recent report on the impact of the pandemic on schools and learning, titled ‘Education Giving in the Midst of COVID-19’, the Organization for Economic Co-operation and Development Centre for Philanthropy outlined in harrowing detail the full effects of ‘The Great Lockdown’ on learners, households and teachers alike, concluding with the sobering statement that “Covid-19 and school closures is a tale of growing inequality.”

The report describes how the pandemic has been by far the largest disruption witnessed by education systems in the 21st century. At the peak of the first wave, school closures affected over 90% of all learners worldwide. This placed educators in a challenging teaching environment, and put millions of households under economic stress. The learning loss and the heightened risk of student disengagement, particularly for the most vulnerable, can have long-lasting effects on their life outcomes and future economic growth as well as physical and mental well-being.

Governments have committed funds and announced new programs in an attempt to mitigate these trends, but according to the OECD the most notable contributors to what will be a generational effort to claw back the losses sustained over the course of the multiple lockdowns have been and will continue to be philanthropic foundations, especially those who are utilizing technology effectively.

A recent study by the Centre for Disaster Philanthropy (CDP) also revealed that at least $20.2bn in global Covid-19 giving was made by grant-makers and wealthy donors during 2020. Corporate foundations and corporate giving programs accounted for $9.4bn (44 percent) of total Covid-19 funding. On the educational front, many philanthropic donors have been making quick disbursements of funds, redirecting committed resources to new issues, and in some cases, redefining their mid- and long-term strategies.

Much of these funds are being distributed to AI-enabled learning, in order to decrease inequality caused by the pandemic. AI can be a powerful tool for enhancing the educational experiences of people with disabilities or other special needs. We'll take a look at some examples of what is going on in the world of AI and Education Non Profits. For example, one teacher found that by pairing an interactive math app with her instruction she was able to better engage her students and reduce classroom anxiety for struggling learners who might otherwise have been left.

Some newly established foundations have committed themselves to confronting educational challenges with a technologically forward-thinking approach. One striking example of this is the Nick Maughan Foundation, established in 2020 “to further a range of philanthropic initiatives in education, the environment and civic support schemes for disenfranchised communities.” The Foundation – or ‘NMF’ as it is known – was founded by its namesake Nick Maughan, a British investor and philanthropist who made his fortune in algorithmic modelling companies (he is also the founder of Maughan Capital, an impact investment vehicle).


Over the course of the past year Maughan has been a persistent voice in the British press decrying the educational attainment gap - the differences in educational outcomes experienced by students from rich and poor backgrounds respectively. The problem is particularly acute in Britain, where the age-old class divide has produced a school system of such wildly disparate resources and opportunities that its harshest critics term it ‘educational apartheid’ that also makes the “digital divide” all the more apparent.

Earlier this year Maughan phrased the problem starkly on the UK’s influential Conservative Home website, writing that “all young people have been dealt a bad hand by the indirect effects of the pandemic – school closures, disrupted social lives, stifled educations, scuppered paths to university, the looming prospect of insurmountable debt, and diminished prospects for gainful employment. However, some young people are more equal than others.”

The disproportionate burden borne by the disadvantaged is the raison d'etre of his foundation. Maughan brings his years of algorithmic modelling expertise to the problem of education inequality by studying and implementing techniques using AI to create a more inclusive and equitable education system.

In his research, Maughan found that algorithms can be implemented within a classroom environment to provide students with personalized learning plans that meet their individual needs. Personalized learning is an educational approach that aims to provide students with unique, tailored education plans that meet their individual needs. Personalized learning has been shown to improve academic achievement by considering each student's strengths and weaknesses, interests, requirements and motivation.

Although personalized learning sounds like the ultimate solution to improving education worldwide it only works if every student receives the same high quality personalized instruction as other students. This means that teachers need access to large amounts of data on how well students are learning at all times. One example that has been successfully implemented is adaptive tutoring systems (ATSs). This idea has already netted tremendous results, especially in the areas of math and science education where concepts are very easy to quantify.

Another interesting area where algorithmic models have truly thrived is in the area of data mining and retrieval. Computer scientists have developed algorithms that can be sent into a database to find specific patterns or students with certain types of negative behavior and return this data to help teachers decide what activities or learning styles could best benefit the student.

It is against this backdrop that the NMF has announced it will be devoting its considerable resources to nurturing out-of-school clubs, designed to help young people make successful transitions to adulthood. The NMF is a major donor to the Berkshire Youth Trust, a youth support charity that aims to fill the gap left by sustained government cuts to youth support services across the UK, and earlier this year launched its own flagship youth organization called BOXWISE, a non-profit social enterprise centered around boxing classes that teaches its young participants life values such as purpose and teamwork while helping them to gain educational qualifications and seek out gainful employment.

The NMF’s emphasis on physical and mental health informed by data and algorithmic models is a key component to bridging the chasm between rich and poor young people falls in line with many of the OECD’s recommendations, which recognize the need for support from the philanthropic sector to be holistic instead of simply focusing on academic attainment.

Its other recommendations state the opportunity for foundations to build bridges between the public, private and technological sectors, to work with governments and Official Development Assistance (ODA) providers to deliver back-to-school campaigns, raising awareness on the value and importance of technologically informed educational programs among governments, other donors and local communities.

The report’s introduction is headed by Winston Churchill’s famous adage to “never let a good crisis go to waste.” Maybe foundations needed this crisis in order to find a renewed purpose in the world, better informed by data, research, and technological advancements. Efficiency is key when providing desperately needed educational resources which governments have been unable to fund, and AI is already bringing that efficiency to the table.

Published on, Sep 22, 2021


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