외국어학습을 위한 대화형 챗봇의 담화 분석을 통한 개선 방안 연구

초록

The present study investigated the potential of voice-based conversation AI chatbot for foreign language learning. Among commercially available AI chatbot products, Naver’s Clova was selected, and its English speaking mode was utilized. The dialogs between this chatbot and one of the authors were recorded, and used as the primary data in this study. In analyzing these dialogs, the widely used frameworks in foreign language learning research were adopted, including “Initiate-response-feedback,” “teacher’s question type,” and “negotiation of meaning strategies” frameworks. The results showed the selected chatbot appeared to take the role of a teacher (tutor) in conversation with the user, in that on most occasions it started a conversation (new topic) by asking questions to the user. Furthermore, the chatbot primarily used relatively simple types of questions to guide the user conversations. In terms of the uses of negotiation of meaning strategies, which are considered one of the most important aspects in conversation-driven foreign language learning, the chatbot was found to be rarely using this type of strategies, and the absence of such strategies resulted in communication breakdown with the user. The present study also proposes considerations for the future development of the chatbot for foreign language learning.

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