敬语效应：探索日语语言形式对AI生成的物理解释的影响
The Honorific Effect: Exploring the Impact of Japanese Linguistic Formalities on AI-Generated Physics Explanations
AI总结：
本研究探讨了日语敬语对大型语言模型解释动量守恒定律的影响，发现敬语显著影响AI回答的质量、一致性和正式程度，为AI辅助教育中的文化适应和个性化学习提供了新途径。
摘要：
本研究调查了日语敬语对大型语言模型（LLM）在解释动量守恒定律时回答的影响。我们分析了六种最先进的AI模型的输出，包括ChatGPT、Coral和Gemini的变体，使用了14种不同的敬语形式。研究结果表明，敬语显著影响AI生成回答的质量、一致性和正式程度，展示了LLM解释和适应嵌入语言中的社会语境线索的能力。不同模型之间观察到显著差异，有些强调历史背景和推导，而另一些则侧重于直观解释。本研究突出了在教育背景下使用敬语调整AI生成解释的深度和复杂性的潜力。此外，AI模型对文化语言元素的响应能力强调了在教育应用的AI开发中考虑文化因素的重要性。这些结果为AI辅助教育和AI系统中的文化适应研究开辟了新途径，对个性化学习体验和开发面向全球教育的文化敏感型AI工具具有重要意义。
英文摘要：
This study investigates the influence of Japanese honorifics on the responses of large language models (LLMs) when explaining the law of conservation of momentum. We analyzed the outputs of six state-of-the-art AI models, including variations of ChatGPT, Coral, and Gemini, using 14 different honorific forms. Our findings reveal that honorifics significantly affect the quality, consistency, and formality of AI-generated responses, demonstrating LLMs' ability to interpret and adapt to social context cues embedded in language. Notable variations were observed across different models, with some emphasizing historical context and derivations, while others focused on intuitive explanations. The study highlights the potential for using honorifics to adjust the depth and complexity of AI-generated explanations in educational contexts. Furthermore, the responsiveness of AI models to cultural linguistic elements underscores the importance of considering cultural factors in AI development for educational applications. These results open new avenues for research in AI-assisted education and cultural adaptation in AI systems, with significant implications for personalizing learning experiences and developing culturally sensitive AI tools for global education.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
