研究留学生用AI写作时为何不愿坦白，发现安全环境是关键。
Examining EAP Students' AI Disclosure Intention: A Cognition-Affect-Conation Perspective
- 从认知-情感-行为三层面分析学生是否披露用AI
- 心理安全感强则更愿坦白，怕被评价则选择隐瞒
- 适合教育政策制定者和教师参考
生成式人工智能在学术写作中的广泛应用引发了高等教育中透明度与学术诚信的担忧。本研究基于认知-情感-行为框架，探究英语学术用途（EAP）学生披露使用AI工具意愿的心理因素。采用分步解释型混合方法设计：对中国某英文授课高校的324名EAP学生进行定量调查，使用结构方程模型分析，随后对15名学生开展半结构化访谈以深化理解。量化结果显示，心理安全感正向预测披露意愿，而对负面评价的恐惧则负向影响。质性分析进一步表明，教师支持性实践与明确指导能增强心理安全感，而政策模糊与声誉顾虑则加剧恐惧感，抑制披露行为。研究强调清晰的机构政策与支持性教学环境对促进透明使用AI的重要性。
原文摘要 · Abstract (English)
The growing use of generative artificial intelligence (AI) in academic writing has raised increasing concerns regarding transparency and academic integrity in higher education. This study examines the psychological factors influencing English for Academic Purposes (EAP) students' intention to disclose their use of AI tools. Drawing on the cognition-affect-conation framework, the study proposes a model integrating both enabling and inhibiting factors shaping disclosure intention. A sequential explanatory mixed-methods design was employed. Quantitative data from 324 EAP students at an English-medium instruction university in China were analysed using structural equation modelling, followed by semi-structured interviews with 15 students to further interpret the findings. The quantitative results indicate that psychological safety positively predicts AI disclosure intention, whereas fear of negative evaluation negatively predicts it. The qualitative findings further reveal that supportive teacher practices and clear guidance foster psychological safety, while policy ambiguity and reputational concerns intensify fear of negative evaluation and discourage disclosure. These findings highlight the importance of clear institutional policies and supportive pedagogical environments in promoting transparent AI use.
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