An Image-Based Vocabulary Learning System Based on Multi-Agent System

• Main Authors: Preecha Tangworakitthaworn, Preeyapol Owatsuwan, Nutsima Nongyai, Nongnapas Arayapong
• Other Authors: Mahidol University
• Format: Conference or Workshop Item
• Published: 2020
• Subjects: Computer Science; Decision Sciences
• Online Access: https://repository.li.mahidol.ac.th/handle/123456789/50627

© 2019 IEEE. Promoting and developing English language skills are essential for second language learners. This paper presents the design and development of a mobile application for promoting learners' experiences in learning the English vocabularies by formulating the compound words generated from images. The proposed system is based on the multi-Agent system (MAS) covering three main agents: matching learners agent, combination vocabulary agent, and feedback agent. The innovation of the proposed approach is that many learners (matching learners agent) can formulate the new vocabulary that is formed from the combination algorithm (combination vocabulary agent) and learners can experience new vocabulary represented by using the image results (feedback agent). The two experiments of the system performance evaluation are reported. The experimental results show that the performance of the vocabularies' detection and the sub processes execution were achieved the high accuracy.