An Intelligent System of Oral English Assistant Teaching Based on Tag Matching

Abstract

This paper introduces an online oral English teaching aid system based on tag matching. Data is first collected by the multi-parameter objective scoring system of Reading Aloud in English. Feedback of students’ oral English learning and learning resource recommendation then are given to students based on formative assessment theory. This system serves both teachers and students. Students can learn autonomously, monitor their study and obtain personalized learning resource recommendation. Meanwhile, teachers can have a visual interface of students’ learning results, which helps them to track students’ individual learning process as well as obtain an overall view of the whole class through the visual data analysis chart function. The application of this system can improve students’ oral English learning efficiency and help teachers complete their predetermined teaching objectives.