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, our previous 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 (objectives, theory, and practicals), 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.

翻译：非洲师生比例较高，限制了学生获取教师学习支持（如教育问答）的机会。本研究将我们先前面向编程教育的AI助教Kwame进行扩展，适配至科学教育领域，并以Web应用形式部署。Kwame for Science基于西非高中毕业证书考试（WASSCE）的综合科学科目，从精心筛选的知识源中提取段落，并结合历年国家考试真题，为学生问题提供答案。此外，学生可按年份、题型（客观题、理论题、实验题）及我们自研的自动分类主题检测模型（未加权平均召回率91%）所划分的科目，查阅历年真题及其参考答案。我们在真实环境中部署Kwame for Science达8个月，累计服务来自32个国家（含15个非洲国家）的750名用户，解答1,500道问题。评估结果显示，前三准确率达87.2%（n=109道问题），表明Kwame for Science在三条展示答案中至少提供一条有效答案的成功率较高。我们系统分类了模型回答错误的成因，为后续改进提供依据，并分享了此类工具在开发、部署及人机交互环节中的挑战与经验，以助力其他研究者部署类似工具。作为非洲语境下首款此类工具，Kwame for Science有望为全非洲数百万用户提供可扩展、高性价比、高质量的远程教育服务。