Artificial Intelligence in Practice：Conversation-Based Intelligent Tutoring System Conducts Research on Japanese Remedial Teaching

• Main Authors: Chih-Ling Chia (Author), Cheng-Hsuan Li (Author)
• Format: Book
• Published: National Taipei University of Education, 2020-12-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

Summary

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.

Item Description

1993-5633
1993-5633