The Woodspring Intell Hub
Grounded Intelligence
Automatic speech recognition promises to transform foundational literacy assessment in African classrooms — faster feedback, less burden on teachers, and real scale. But most ASR tools have been trained on adult voices, tested in quiet rooms, and built without the children they're meant to serve. Idris examines what the early evidence shows, where the gaps are, and what every decision-maker should ask before deploying.
Automatic speech recognition promises to transform foundational literacy assessment in African classrooms — faster feedback, less burden on teachers, and real scale. But most ASR tools have been trained on adult voices, tested in quiet rooms, and built without the children they're meant to serve. Idris examines what the early evidence shows, where the gaps are, and what every decision-maker should ask before deploying.
Speech and language AI is reshaping how children learn worldwide. But in Africa, where an estimated 85–90% of languages rely on tone to distinguish meaning, most of these tools fail in basic and predictable ways — not from lack of effort, but from a fundamental mismatch between system design and linguistic reality. Godfred Agyapong examines what tone-blindness costs in African classrooms and what it will take to build tools that actually work.
Learning Futures Briefing
Latest
AI is already in African and Indian classrooms — not replacing teachers, but giving them something they've rarely had: fast, actionable feedback. From phone-based handwriting scanners in Rajasthan to ASR reading tools in Ghana and AI chatbots in Sierra Leone, this issue of the Learning Futures Briefing maps what Teacher–AI tandems look like in practice, and why the shift from concept to classroom is already underway.
AI is moving fast in education — but how do we know what actually works? This issue of the Learning Futures Briefing makes the case for benchmarks and evaluations as the field's essential guardrails: tools that separate genuine classroom impact from well-marketed hype, and that help funders, developers, and decision-makers build confidence before they scale.
When education data systems don't talk to each other, teachers juggle disconnected dashboards, ministries can't link spending to outcomes, and AI tools accelerate the fragmentation rather than solving it. This issue of the Learning Futures Briefing makes the case for interoperability as the invisible foundation of effective EdTech — and examines what it looks like when governments actually get it right.
AI tools are starting to remember — storing learner progress, preferences, and patterns across sessions. But who owns that data, and what happens when it's locked inside a proprietary system a school can't access or transfer? This issue of the Learning Futures Briefing explores how persistent memory works, what it could mean for teaching and learning, and why the governance choices being made right now will shape the future of every child's educational record.
Most AI tools assume a stable internet connection — but the classrooms that need them most often have none. This issue of the Learning Features Briefing explores Edge AI: small language models that run directly on phones, tablets, and school servers, no cloud required. From reading tutors in Tanzania to coaching tools in East Africa, the technology is already arriving in LMIC classrooms. The question is whether builders and deployers can keep it light, local, and built to last.
AI agents — systems that can perceive, reason, and act toward specific goals — are no longer just for engineers. They're becoming practical tools for education, capable of automating assessments, grouping learners by skill level, personalising lesson materials, and delivering coaching feedback at scale. This inaugural issue of the Learning Futures Briefing breaks down how agents work, what they can realistically do in classrooms today, and where the hype still outpaces the evidence.