分析编程教育中ChatGPT研究的讨论，揭示其教学潜力与风险
Pedagogical Promise and Peril of AI: A Text Mining Analysis of ChatGPT Research Discussions in Programming Education
- 用文本挖掘分析编程教育领域对ChatGPT的学术讨论
- 发现四大主题：教学实施、学生参与、人机协作与评估设计
- 强调需加强评估与制度治理，避免过度依赖与学术诚信风险
生成式AI系统如ChatGPT在编程教育领域的讨论日益增多，但其在学术文献中的概念化与框架仍不清晰。本研究对主流学术数据库中的相关出版物进行文本挖掘，通过词频分析、短语模式提取和主题建模，识别出四个主导主题：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、提示设计与模型评价。研究发现，现有文献更关注课堂实践与学习者互动，对评估设计与机构治理的关注相对不足。多数研究将ChatGPT视为辅助学习工具，可提供解释、反馈与效率提升，但也视其为潜在教学风险，涉及过度依赖、输出不可靠及学术诚信问题。研究结果支持负责任地整合该技术，并强调亟需强化评估机制与治理体系。
原文摘要 · Abstract (English)
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.
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