Improving Course Registration Efficiency Through LINE Chatbot with LLM Integration

Abstract

This study addresses inefficiencies in course registration at a private training center that used Google Forms. The process resulted in redundant data entry, a 25% error rate, and no real-time status tracking. The study pursued three objectives 1) developing an Automated Question Answering System (AQAS) using LLM technology 2) implementing an Automated Course Registration System (ACRS) via LINE Messaging API and 3) minimizing data entry errors to enhance data management efficiency. System development followed the Software Development Life Cycle (SDLC) waterfall model, the system was developed through structured phases of analysis, design, implementation, testing, deployment, and maintenance. Data management utilizes MySQL database with administrator validation conducted directly through LINE. System evaluation presented improvements in all three objectives. The LLMintegrated question-answering system achieved 86% accuracy across 50 structured queries. Comparative testing with 80 participants across three courses showed that the LINE-based registration system improved registration data entry accuracy by a 26.7% relative increase and reduced processing time by 50-66 %. These improvements enhanced user interaction quality, reduced staff workload, and demonstrated the effectiveness of AI-enabled chatbots for educational administration.