Adesua: Development and Feasibility Study of an AI WhatsApp Bot for Science Learning in West Africa
arXiv cs.CL·George Boateng, Evans Atompoya, Philemon Badu, Samuel John, Samuel Ansah, Patrick Agyeman-Budu, Victor Wumbor-Apin Kumbol
4d agoQuick Take
Adesua is an AI WhatsApp bot designed to enhance science learning in West Africa.
Key Points
- Addresses high student-teacher ratios in Sub-Saharan Africa.
- Offers personalized learning support via WhatsApp.
- Preliminary results show high perceived usefulness among users.
📖 Reader Mode
~2 min readAbstract:Sub-Saharan Africa faces persistently high student-teacher ratios and shortages of qualified teachers, limiting students' access to personalized learning support and formative assessment. To address this challenge, we present Adesua, a WhatsApp-based AI Teaching Assistant for science education that extends the Kwame for Science platform. Adesua leverages WhatsApp's widespread adoption in Africa to provide accessible, curriculum-aligned learning support for Junior High School (JHS) and Senior High School (SHS) students across West Africa. The system integrates curated textbooks and 33 years of national examination questions with generative AI to enable conversational question answering and automated assessment with feedback via a WhatsApp bot. Students can ask science questions, take timed or untimed multiple-choice tests by topic or exam year, and receive instant grading and detailed explanations of correct and incorrect responses. A 6-month feasibility deployment in 2025 had 56 active users in Ghana, including students and parents. Quantitative evaluation showed a high perceived usefulness, with a helpfulness score of 93.75\% for AI-generated answers, albeit with a small number of ratings (n=16). These preliminary results provide a basis for more extensive future evaluation of a WhatsApp-based AI assistant to assess its potential to offer scalable, low-cost personalized learning support and formative assessment in resource-constrained educational contexts.
| Comments: | 11 pages. Accepted at the 27th International Conference on Artificial Intelligence in Education (AIED 2026) |
| Subjects: | Computation and Language (cs.CL); Computers and Society (cs.CY) |
| Cite as: | arXiv:2605.15376 [cs.CL] |
| (or arXiv:2605.15376v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2605.15376 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: George Boateng [view email]
[v1]
Thu, 14 May 2026 20:04:39 UTC (4,606 KB)
— Originally published at arxiv.org
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