Using Learning Analytics to Explore the Performance of Chinese Mathematical Intelligent Tutoring System

Abstract

This study introduced the Chinese dialogue-based mathematical intelligent tutoring system that developed to help students to learn mathematics without teachers. Student interactions with the Chinese dialogue-based mathematical intelligent tutoring system produce a wide range of learning sequences. The present study explored students’ learning performance and the effectiveness of knowledge components by using additive factors model and Bayesian knowledge tracing model. The model fit and the learning patterns of students were discussed.