Learning Analytics for Investigating the Mind Map-Guided AI Chatbot Approach in an EFL Flipped Speaking Classroom

Abstract

One of the biggest challenges for EFL (English as Foreign Language) students to learn English is the lack of practicing environments. Although language researchers have attempted to conduct flipped classrooms to increase the practicing time in class, EFL students generally have difficulties interacting with peers and teachers in English in class. The advancement of Artificial Intelligence (AI) provides an opportunity to address this problem. With AI technologies, computer systems, in particular in the form of AI chatbots, are able to identify the meanings of users’ statements and make responses accordingly. In the research design, AI-based chatbots were employed in the in-class and out-of-class activities for facilitating the students’ speaking performance and interactions during the learning process in a university flipped English speaking classroom. The experimental results show that the mind map-guided AI chatbot approach (MM-AI) promoted the students’ English speaking performances more than did the conventional AI chatbot approach (C-AI). Moreover, the MM-AI also promoted the students’ learning performance and organized the interaction between the robots and humans more than the C-AI did. The findings could be a valuable reference for language educators and researchers who intend to conduct AI-supported flipped classrooms in language learning.

Keywords

• ai chatbot
• mind-map strategy
• english speaking flipped learning
• learning analytics