Developing a question answering system for the Sri Lankan school education system
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Date
2025
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Department of Computer Science and Engineering
Abstract
The integration of Artificial Intelligence (AI) into education unlocks opportunities for personalized learning. However, low-resource languages such as Sinhala currently lack robust Natural Language Processing (NLP) tools. This paper proposes a question-answering system tailored for the Sri Lankan school curriculum, designed to retrieve curriculum-based answers from structured educational materials. To address the digital divide in rural areas, an offline-accessible version is planned. The study outlines a framework for development and a proposed evaluation using standard NLP metrics and user feedback, aiming to create a scalable, effective tool for Sinhala language learners.
