让非英语母语者用母语提问,生成代码解决编程难题
Breaking the Programming Language Barrier: Multilingual Prompting to Empower Non-Native English Learners
- 用阿拉伯语、中文、葡萄牙语等母语提问生成代码
- 学生能成功解题,但术语表达仍有困难
- 适合希望降低编程学习门槛的教育者和学习者
非英语母语者(NNES)在学习编程时面临多重障碍,包括编程语言语法和指令多为英文,以及在母语者众多的课堂中不敢求助等。尽管这些障碍令人沮丧,但许多学生其实掌握的编程知识远超其英语表达能力。生成式AI(GenAI)的发展为此提供了突破可能,因为当前先进模型支持多语言交互,并已在代码生成与解释方面表现出高准确性。本文首次探索了非英语母语学生使用阿拉伯语、中文和葡萄牙语等母语提问,以生成解决编程问题的代码。结果表明,学生能够成功利用母语完成编程任务,但在准确表述编程术语和概念时仍存在困难。我们讨论了所遇挑战、短期实践意义,以及对全球计算教育长远变革的潜在影响。
原文摘要 · Abstract (English)
Non-native English speakers (NNES) face multiple barriers to learning programming. These barriers can be obvious, such as the fact that programming language syntax and instruction are often in English, or more subtle, such as being afraid to ask for help in a classroom full of native English speakers. However, these barriers are frustrating because many NNES students know more about programming than they can articulate in English. Advances in generative AI (GenAI) have the potential to break down these barriers because state of the art models can support interactions in multiple languages. Moreover, recent work has shown that GenAI can be highly accurate at code generation and explanation. In this paper, we provide the first exploration of NNES students prompting in their native languages (Arabic, Chinese, and Portuguese) to generate code to solve programming problems. Our results show that students are able to successfully use their native language to solve programming problems, but not without some difficulty specifying programming terminology and concepts. We discuss the challenges they faced, the implications for practice in the short term, and how this might transform computing education globally in the long term.
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