Using AI-Powered Chatbots to Bridge the Education Gap in Underserved Communities

In underserved regions globally, students face significant barriers to accessing quality education. This research explores the role of AI-powered chatbots in delivering academic support to such communities. Leveraging Natural Language Processing (NLP), low-bandwidth interfaces, and simplified user interaction, the proposed solution enables personalized learning, academic guidance, and resource access in low-infrastructure settings. This paper presents the architectural diagram, system flow, technical components, simulated evaluation metrics, anticipated challenges, and potential for real-world deployment. Comparative analysis and future enhancements are also addressed. Mathematical models and NLP algorithms used in processing queries are explained and evaluated. Though the chatbot has not yet been deployed publicly, we simulate results based on interviews with students and teachers from several secondary institutions in rural Bangladesh.