Development of a Class Materials Search System using LINE Chatbot

Abstract

Self-learning enables students to learn at their own pace. The process itself has changed significantly from reading textbooks to viewing ebooks on electronic devices, asking questions on online discussion boards or watching video clips from other parts of the world. The change has come with a massive increase in the amount of information available. It is time-consuming for a student to obtain the exact item of class material wanted. We developed a search system that can store relevant class materials in its own database and give suggestions when a student needs them. The system is built as a chatbot in the LINE application, using the NLP algorithm, to interact between users and the system via Artificial Intelligence technology. The system was developed for two subjects in Electrical Engineering: Signals and Systems and Control Systems. It was able to correctly interpret the users’ requests with up to 80% accuracy. It can give suggestions of class materials based on rankings given by users’ scores. This search system makes self-learning less time consuming and may provide more encouragement to students.