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A featured contribution from Leadership Perspectives: a curated forum reserved for leaders nominated by our subscribers and vetted by the Education Technology Insights APAC Advisory Board.

Dr. Lamiae Benhayoun, Business Analytics and Data Science Program Manager, Associate Professor of Information Systems

A Screen, a Dream and No Classroom in Sight
Dr. Lamiae Benhayoun
AI Skills Architect
It is past eleven o'clock at night in Lagos. Amara, nineteen, sits on a shared bed, earphones in, completing a software engineering certification on her smartphone. The course was designed by a Nigerian startup, recorded in English and Yoruba, built to run on two bars of mobile data. There is no campus she can afford, no teacher she can call. There is only the screen and the stubborn arithmetic of ambition. Amara's story is not exceptional. It is, increasingly, the norm.
The Scale of the Problem
The eLearning market in Africa alone was valued at $3.4 billion in 2024, expected to climb to $19.7 billion by 2034, driven by over 500 million smartphone users across the continent. Yet behind the figures lies a grimmer reality: hundreds of millions of children in Sub-Saharan Africa, South Asia, and Latin America attend under-resourced schools or none at all. Teacher shortages are chronic. Curricula are often delivered in colonial languages students do not speak at home.
These are not temporary deficits. They are structural realities that the Western EdTech industry built for broadband-connected, English-speaking, middle-class households, was never designed to address. While developed economies focus on introducing innovative EdTech offerings to reduce teacher workload and engage students, emerging economies face the more fundamental challenge of ensuring easy and convenient access to educational opportunities for their citizens at all. The ambition is different. The constraints are different. And, increasingly, the solutions are different too.
The Leapfrog Moment
There is a concept in development economics called leapfrogging: countries with weak legacy infrastructures sometimes skip entire technological generations. M-Pesa, the Kenyan mobile payment platform, is the textbook case. A country with limited banking infrastructure became a global leader in financial technology by bypassing the old model entirely.
Education is now living through its own leapfrog moment. The smartphone has arrived in places where the school building has not. Increasing smartphone adoption, a growing young population seeking quality education and government initiatives aimed at bridging educational gaps through technology are the primary drivers reshaping EdTech across emerging markets. Where infrastructure is absent, the phone becomes the classroom, the library and the examination hall.
This shift has profound design implications. A platform built for a North American university student with a reliable Wi-Fi, a laptop, and a quiet room is simply unusable in rural Bangladesh or peri-urban Nairobi. The real innovation in global EdTech is not happening in San Francisco incubators. It is happening in the constraints.
Who Is Actually Building This
Across Lagos, Nairobi, and Cairo, founders are building products serving hundreds of thousands of learners without ever pitching at a Western tech conference.
eLimu in Kenya delivers digital tools designed to improve literacy among children who have never opened a printed textbook. uLesson in Lagos offers video courses and assessments tailored to local curricula, not the Cambridge syllabus, but the West African Examinations Council. Klas, also Nigerian, connects 5,000 teachers with 300,000 learners across 30 countries, functioning as a mobile-first platform for educators to build and monetize their own digital classrooms.
"What unites these platforms is a design philosophy born of necessity: offline-first architecture, low-bandwidth optimization, local language content and pricing calibrated to local incomes."
Nigeria accounted for 34 percent of Africa's top EdTech startups in 2024, while Rwanda, Kenya and Egypt are rapidly expanding their own ecosystems.
What unites these platforms is a design philosophy born of necessity: offline-first architecture, low-bandwidth optimization, local language content, and pricing calibrated to local incomes. These are not compromises. They are innovations and they have produced learning tools more adaptive, more resilient and more contextually intelligent than many of their Western counterparts.
The Hard Questions
The EdTech revolution in emerging economies carries its own fault lines that deserve honest examination
• Access is not the same as quality: reaching more students does not automatically mean teaching them better.
• The credential gap remains acute: only 2 percent of Africa's workforce currently holds recognized digital skills, and certificates from emerging market platforms still carry limited weight with global employers.
• Data governance is largely unresolved with millions of students generating behavioral data on commercial platforms in countries with weak privacy regulation.
• Investor agendas shape outcomes: as global EdTech venture capital fell to $1.8 billion in 2024, its lowest level since 2014, the startups best positioned to survive are those that can demonstrate revenue, which does not always align with serving the most marginalized learners.
She Built Her Own Path. Can the System Catch Up?
The argument that policymakers have been slow to make is this: the Global South is not a recipient of EdTech innovation, it is a laboratory for it. The offline-first, multilingual, mobile-native models being built in Lagos and Nairobi will matter far beyond their original context. The case for South-South knowledge transfer is more compelling than any North-South aid program premised on the assumption that innovation flows in one direction only.
For international organizations: fund what is already working locally. For global EdTech companies: the fastestgrowing youth populations on earth are in Africa, South Asia, and Latin America. Adapt or watch the homegrown alternatives lead.
It is past midnight. Amara has finished her module. She sets her alarm and sleeps. She did not wait for the system to include her. She built her own path through it, on a $90 smartphone, with borrowed data, in a city that never built her a school. The question now is whether the system is ready to learn from her.