Breaking the Programming Language Barrier: Multilingual Prompting to Empower Non-Native English Learners

TL;DR

This study tackles the barrier that English poses for non-native English speakers learning programming by exploring multilingual prompting using GenAI. It introduces Prompt Problems in Arabic, Chinese, and Portuguese across three universities, combining quantitative prompt analyses with qualitative user surveys to gauge success and experience. The findings reveal that Chinese and Portuguese participants generally succeed more than Arabic participants, with clear expressivity advantages in native languages but English-based coding terms still driving higher accuracy. The work highlights both the transformative potential and the challenges of multilingual GenAI-assisted programming education, underscoring the need for more inclusive, culturally relevant prompt design and broader language coverage to truly democratize computing education.

Abstract

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.