一句话：首次实证调查拉美西语开发者使用 AI 编程工具时的语言障碍、不信任来源与改进需求。
AI 编程工具能提升开发效率，但其训练数据以英语为主，给非英语母语开发者带来困难。在厄瓜多尔的双语环境中，西班牙语主导日常工作流，而英语对 API 与文档不可或缺，这些工具无法解析西班牙语标识符等非英语代码元素，造成低效与不信任。本文用混合方法调查了 65 名母语为西班牙语的开发者（45 份西语问卷、20 份英语问卷，英语水平各异），考察工具使用、语言障碍与期望的改进。参与者用 AI 助手自动化日常任务，但当建议涉及多文件或忽略本地命名约定时出现问题；西语问卷受访者放弃建议的比例高于英语问卷受访者（25% 对 17.9%），说明这是语言不平等而非编程能力差异。定性分析指出三项需求：理解西英混合代码的多语言 NLP、适应当地 API 规范的上下文感知生成、以及暴露来源与置信度的透明反馈。作者主张平衡的西英语料与双语分词器是务实步骤。研究受限于便利样本较小与自报实践。
AI coding tools can boost software-development productivity, yet their English-dominated training data pose challenges for non-English-speaking developers. In Ecuador's bilingual context—Spanish drives workflows while English is essential for APIs and documentation—these tools fail to parse non-English code elements, including Spanish identifiers, causing inefficiency and mistrust. This study investigates perceptions and challenges among 65 developers—45 Spanish-survey (ES) and 20 English-survey (EN) respondents, all native Spanish speakers with varying English skills. Using mixed methods we surveyed tool usage, linguistic barriers, and desired enhancements. Participants use AI assistants to automate routine tasks but report issues when suggestions span multiple files or ignore local naming conventions. ES respondents abandon recommendations more often than EN peers (25% vs 17.9%), indicating linguistic inequities rather than programming expertise. Qualitative analyzes highlight three needs: (i) multilingual NLP that understands hybrid Spanish-English code, (ii) context-aware generation that adapts to regional API norms, and (iii) transparent feedback that exposes provenance and confidence for verification. We argue that balanced Spanish-English corpora and bilingual tokenisers are pragmatic steps toward these goals, enabling automation while preserving developers' reasoning skills. Though limited by a modest convenience sample and self-reported practices, this work provides the first empirical snapshot of AI coding-tool adoption in Latin America and underscores the need for inclusive, context-sensitive tools to foster equitable software-engineering advancement globally.
@inproceedings{paperbot9160,
title = {AI Coding Tools in Bilingual Software Development: A Survey of Spanish-Speaking Developers},
author = {Miguel Botto-Tobar and Alexander Serebrenik and M. G. J. van den Brand},
booktitle = {FSE},
year = {2025},
doi = {10.1145/3696630.3731670}
}