arXiv — NLP / Computation & Language · · 3 min read

Adesua: Development and Feasibility Study of an AI WhatsApp Bot for Science Learning in West Africa

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Computer Science > Computation and Language

arXiv:2605.15376 (cs)
[Submitted on 14 May 2026]

Title:Adesua: Development and Feasibility Study of an AI WhatsApp Bot for Science Learning in West Africa

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Abstract: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)
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