Language is an important resource for physicists and learners of physics to construe physical phenomena and processes, and communicate ideas. Moreover, any physics-related instructional setting is inherently language-bound, and physics literacy is fundamentally related to comprehending and producing both physics-specific and general language. Consequently, characterizing physics language and understanding language use in physics are important goals for research on physics learning and instructional design. Qualitative physics education research offers a variety of insights into the characteristics of language and language use in physics such as the differences between everyday language and scientific language, or metaphors used to convey concepts. However, qualitative language analysis fails to capture distributional (i.e. quantitative) aspects of language use and is resource-intensive to apply in practice. Integrating quantitative and qualitative language analysis in physics education research might be enhanced by recently advanced artificial intelligence-based technologies such as large language models, as these models were found to be capable to systematically process and analyse language data. Large language models offer new potentials in some language-related tasks in physics education research and instruction, yet they are constrained in various ways. In this scoping review, we seek to demonstrate the multifaceted nature of language and language use in physics and answer the question what potentials and limitations artificial intelligence-based methods such as large language models can have in physics education research and instruction on language and language use.

中文翻译：

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物理语言和物理中的语言使用——我们知道什么以及人工智能如何加强与语言相关的研究和教学

语言是物理学家和物理学学习者解释物理现象和过程、交流思想的重要资源。此外，任何与物理相关的教学环境本质上都是受语言限制的，而物理素养从根本上与理解和产生物理专用语言和通用语言有关。因此，表征物理语言和理解物理中的语言使用是物理学习和教学设计研究的重要目标。定性物理教育研究提供了对物理中语言和语言使用特征的各种见解，例如日常语言和科学语言之间的差异，或用于传达概念的隐喻。然而，定性语言分析无法捕捉语言使用的分布（即定量）方面，并且在实践中应用需要大量资源。最近先进的基于人工智能的技术（例如大型语言模型）可能会增强物理教育研究中定量和定性语言分析的结合，因为这些模型被发现能够系统地处理和分析语言数据。大型语言模型为物理教育研究和教学中一些与语言相关的任务提供了新的潜力，但它们受到各种限制。在本次范围界定审查中，我们试图证明物理中语言和语言使用的多方面性质，并回答基于人工智能的方法（例如大语言模型）在物理教育研究和语言和语言使用教学中具有哪些潜力和局限性的问题。