Artificial Intelligence-Powered Chatbot for Student Enquiries in Nigerian Tertiary Education

Abstract

Student enquiry management in Nigerian polytechnic institutions is largely manual, leading to delayed responses, administrative overload, and inefficient communication. Although artificial intelligence–based chatbots have been applied in educational environments globally, their adoption and contextual evaluation within Nigerian polytechnics remain limited. This study therefore aims to design and implement an AI-powered chatbot to improve the efficiency of handling student enquiries in a Nigerian polytechnic setting. The proposed system employs Natural Language Processing (NLP) techniques combined with a rule-based response model to interpret user queries and provide accurate, context-aware responses. The chatbot was developed using Python and supported by a lightweight database to enable offline functionality. A functional evaluation conducted at Osun State Polytechnic, Iree, demonstrated an accuracy rate of 90% and an average response time of 1.5 seconds. Benchmarking against related chatbot-based academic enquiry systems shows comparable or improved performance in response accuracy and speed. Despite its effectiveness, the system is limited by its reliance on predefined rules and institutional data, which may restrict scalability across multiple institutions. Overall, the results indicate that AI-driven conversational systems can significantly enhance administrative efficiency, service delivery, and digital transformation within Nigerian polytechnic education.