List Volume 33Number 2 publication date:Dec. 2020 Back Artificial Intelligence in Practice： Conversation-Based Intelligent Tutoring System Conducts Research on Japanese Remedial Teaching     Author:Chih-Ling Chia＊ & Cheng-Hsuan Li Research Article Download The objective of this study is to construct a conversation-based intelligent tutoring system for Japanese learning (CITS-JL), and it is expected to improve students’  Japanese learning effects. Based on the Japanese learning standards in the Japanese Foundation Standard, this study proposes a knowledge map for primary Japanese learning; students can learn Japanese step-by-step by following 22 learning scenarios and 86 designed learning units. CITS-JL first diagnosed students’ error patterns and then used appropriate cognitive conflict teaching strategies to design corresponding problems and conversations to clarify possible misuse of words in learning. In addition, CITS-JL considers the learning system, research objectives, research status of three orientation content, so that the intelligent tutoring system develop a richer level, but also to more complete to assist students to learn. The results show that CITS-JL can immediately clarify the misuse of students’ words, cultivate self-study habits, and improve learning efficiency through repeated exercises. In addition, CITS-JL can be applied to personalized learning. Students can learn Japanese anywhere outside the classroom, saving more time and money. This study contributes to research by building a learning tool for Japanese learners,  providing teachers with appropriate guidelines for remedial teaching. Keywords: Computer-Assisted Teaching, ITS, Knowledge Map, JF Standard A Transnational Study on the Contribution of the Education, Land, Physical Capital, Labor, and Unemployment Ratio to Economic Development