CLCYHCIRFeb 21, 2023

Real-World Deployment and Evaluation of Kwame for Science, An AI Teaching Assistant for Science Education in West Africa

arXiv:2302.10786v312 citationsh-index: 11
Originality Incremental advance
AI Analysis

This work addresses scalable and cost-effective remote education for students in Africa, particularly in science, though it is incremental as it adapts an existing tool to a new domain.

The authors tackled the problem of limited teacher access in African science education by deploying Kwame for Science, an AI teaching assistant that achieved 87.2% top-3 accuracy in answering student questions based on real-world usage over 8 months with 750 users and 1.5K questions.

Africa has a high student-to-teacher ratio which limits students' access to teachers for learning support such as educational question answering. In this work, we extended Kwame, a bilingual AI teaching assistant for coding education, adapted it for science education, and deployed it as a web app. Kwame for Science provides passages from well-curated knowledge sources and related past national exam questions as answers to questions from students based on the Integrated Science subject of the West African Senior Secondary Certificate Examination (WASSCE). Furthermore, students can view past national exam questions along with their answers and filter by year, question type, and topics that were automatically categorized by a topic detection model which we developed (91% unweighted average recall). We deployed Kwame for Science in the real world over 8 months and had 750 users across 32 countries (15 in Africa) and 1.5K questions asked. Our evaluation showed an 87.2% top 3 accuracy (n=109 questions) implying that Kwame for Science has a high chance of giving at least one useful answer among the 3 displayed. We categorized the reasons the model incorrectly answered questions to provide insights for future improvements. We also share challenges and lessons with the development, deployment, and human-computer interaction component of such a tool to enable other researchers to deploy similar tools. With a first-of-its-kind tool within the African context, Kwame for Science has the potential to enable the delivery of scalable, cost-effective, and quality remote education to millions of people across Africa.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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