本研究探讨了基于图形组织器的自然语言聊天机器人方法对翻转课堂中 EFL 学生的口语表现、计算思维倾向和文化兴趣的影响。本研究采用准实验设计，其中ELF（英语作为外语）两个班的48名学生。实验组（n=27）被分配到基于图形组织的自然语言聊天机器人方法（GO-NLC），而对照组（n=21）被分配到传统的自然语言聊天机器人方法（C-NLC）翻转课堂。数据通过混合设计方差分析、顺序分析和 Voyant 工具进行分析。本研究结果表明，实验组不仅显着提高了学生的口头表达能力，而且还提高了学生的计算思维倾向。然而，文化兴趣在实验组和对照组之间没有显着差异。此外，GO-NLC 策略提高了学生组织信息与机器人对话的技能，比 C-NLC 策略更自信、更具互动性和创造性。

The present study explored the impacts of a graphic organizer-based natural language chatbot approach on EFL students’ oral presentation performances, computational thinking tendency, and cultural interest in a flipped classroom. This study adopted a quasi-experimental design, in which 48 students from two classes of ELF (English as a Foreign Language). The experimental group (n=27) was assigned with a graphic organizer-based natural language chatbot approach (GO-NLC), while the control group (n=21) was assigned with a conventional natural language chatbot approach (C-NLC) in the flipped classroom. The data were analyzed by mixed-design ANOVA, sequential analysis, and Voyant tools. The results of this study reveal that the experimental group had not only significantly improved students’ oral presentation performance, but also improve students’ computational thinking tendency. However, the cultural interest has not a significant difference between the experimental and control groups. Moreover, the GO-NLC strategy had improved the students’ skills in organizing information to dialogue with robots, more confident, interactive, and creative than the C-NLC strategy.

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