Africa has a high student-to-teacher ratio which limits students' access to teachers. Consequently, students struggle to get answers to their questions. In this work, we extended Kwame, our previous AI teaching assistant, adapted it for science education, and deployed it as a web app. Kwame for Science answers questions of students based on the Integrated Science subject of the West African Senior Secondary Certificate Examination (WASSCE). Kwame for Science is a Sentence-BERT-based question-answering web app that displays 3 paragraphs as answers along with a confidence score in response to science questions. Additionally, it displays the top 5 related past exam questions and their answers in addition to the 3 paragraphs. Our preliminary evaluation of the Kwame for Science with a 2.5-week real-world deployment showed a top 3 accuracy of 87.5% (n=56) with 190 users across 11 countries. Kwame for Science will enable the delivery of scalable, cost-effective, and quality remote education to millions of people across Africa.

本研究致力于通过IT技术实现对于非洲高中生科学教育的帮助，设计并推出了科学AI教学助手Kwame，利用语义模型回答学生问题并能够提供相关的历届考试题和答案。Kwame的部署和测试表明，其能够大幅提高学生的科学教育效益和学习体验，可以成为一种高效且具有可伸缩性的远程教育方案。

基于Sentence-BERT的Kwame科学教学助手：用于西非的科学教育