Intelligent Voice Instructor-Assistant System for Collaborative and Interactive Classes

Abstract

College classes are becoming increasingly large. A critical component in scaling class size is the collaboration and interactions among instructors, teaching assistants, and students. We develop a prototype of an intelligent voice instructor-assistant system for supporting large classes, in which Amazon Web Services, Alexa Voice Services, and self-developed services are used. It uses a scraping service for reading the questions and answers from the past and current course discussion boards, organizes the questions in JavaScript object notation format, and stores them in the database, which can be accessed by Amazon web services Alexa skills. When a voice question from a student comes, Alexa is used for translating the voice sentence into texts. Then, Siamese deep long short-term memory model is introduced to calculate the similarity between the question asked and the questions in the database to find the best-matched answer. Questions with no match will be sent to the instructor, and instructor’s answer will be added into the database. Experiments show that the implemented model achieves promising results that can lead to a practical system. Intelligent voice instructor-assistant system starts with a small set of questions. It can grow through learning and improving when more and more questions are asked and answered.