GenAI systems such as ChatGPT are increasingly discussed in programming education, but the ways in which the research literature conceptualizes and frames their role remain unclear. This chapter applies text mining to publications indexed in a leading academic database to map scholarly discourse on ChatGPT in programming education. Term frequency analysis, phrase pattern extraction, and topic modeling reveal four dominant themes: pedagogical implementation, student-centered learning and engagement, AI infrastructure and human-AI collaboration, and assessment, prompting, and model evaluation. The literature prioritizes classroom practice and learner interaction, with comparatively limited attention to assessment design and institutional governance. Across studies, ChatGPT is positioned both as a learning aid that supports explanation, feedback, and efficiency and as a pedagogical risk linked to overreliance, unreliable outputs, and academic integrity concerns. These findings support responsible integration and highlight the need for stronger assessment and governance mechanisms.

翻译：生成式人工智能系统（如ChatGPT）在编程教育中日益受到关注，但研究文献对其角色的概念化与框架定位仍不明确。本章对收录于权威学术数据库中的相关出版物进行文本挖掘，以描绘ChatGPT在编程教育领域中的学术话语。通过词频分析、短语模式提取及主题建模，研究揭示了四大主导主题：教学实施、以学生为中心的学习与参与、人工智能基础设施与人机协作、以及评估与提示及模型评测。现有文献优先关注课堂实践与学习者互动，对评估设计与制度治理的关注相对有限。在各研究中，ChatGPT既被定位为支持解释、反馈与效率的学习辅助工具，也被视为与过度依赖、不可靠输出及学术诚信问题相关的教学风险。这些发现为负责任的技术整合提供了支撑，并凸显了强化评估与治理机制的必要性。