Abdul Rahim Jalloh

Sensebod (from local Krio, meaning ?a smart student?) is an offline-first, local-language AI tutor with a built-in examination toolkit. It delivers personalised tutoring, mentorship, gamified engagement, and exam preparation for secondary school students, fully aligned with BECE/WASSCE curricula. Unlike global platforms such as UNICEF?s Learning Passport, Sensebod is built for African realities: it runs offline on EasySTEM Servers, supports learning in local language and adapts to the exam systems students face. Piloted with 400 students across 25 schools, Sensebod was co-developed with students, teachers, and parents to ensure cultural relevance and curriculum alignment. Ministries of Education and Communication anchor policy alignment, UNICEF supported deployment through the DLH in a Bag, and Africell is enabling zero-rating and offline data syncing to guarantee nationwide access. Early indicators are promising: 65% of students are weekly active users averaging one hour per session, and parents report 32% more study time. These trends suggest potential gains of 0.20?0.35 standard deviations in comprehension and exam readiness within one academic year equivalent to several additional months of learning. Teachers benefit from dashboards that flag at-risk learners early, while policymakers gain real-time, disaggregated data to guide equity-focused resource allocation. The societal and economic impact is twofold: improved exam performance and equity for marginalised learners, and reduced remediation costs while building a prepared workforce. By 2027, Sensebod will be open-sourced as a certified Digital Public Good, and by 2035 it will reach six million learners across Africa a replicable, ethical AI model for inclusive, exam-ready education.