AI-supported Authentic Communication with Native Speakers: Exploring EFL Learners' Willingness to Communicate and Emotional Changes

This is the authors' abstract. We don't add key points for this paper.

EFL students’ willingness to communicate (WTC) is a major contributor to speaking in authentic situations. This case study examined the influence of artificial intelligence (AI) on the WTC among Chinese university students engaged in face-to-face (F2F) interactions with a native English speaker. Employing a mixed-method approach, including a WTC questionnaire and two open-ended questions, the study involved fourteen students who engaged in AI chatbot-assisted communication practice simulating human-like dialogues prior to F2F interactions with a native English-speaking teacher outside the traditional classroom setting. The results of the WTC survey indicated positive outcomes and content analysis findings reported students exhibiting shifts from negative emotional states to positive ones. AI's role in pre-talk preparation significantly contributed to the success of students' interactions, emphasizing the value of AI chatbots in the absence of authentic communication opportunities. The study concludes that strategically integrating AI chatbot aligns with the active filter hypothesis, reducing anxiety and promoting positive WTC, thus enhancing language learning experiences.