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.

翻译：生成式人工智能在学术写作中的日益普及引发了高等教育领域对透明度和学术诚信的持续担忧。本研究探讨了影响学术英语学生披露人工智能工具使用意愿的心理因素。基于认知-情感-意动框架，本研究构建了一个整合促进与抑制因素以塑造披露意愿的理论模型，并采用了序贯解释性混合研究方法。通过对中国某英语教学高校324名学术英语学生的定量数据进行结构方程模型分析，并结合对15名学生的半结构化访谈以进一步阐释研究结果，定量结果表明：心理安全感正向预测人工智能披露意愿，而负面评价恐惧则负向预测该意愿。质性研究进一步揭示：教师支持性实践与明确指导能增强心理安全感，而政策模糊性与声誉担忧则会加剧负面评价恐惧并抑制披露行为。这些发现凸显了明确机构政策与支持性教学环境在促进透明化人工智能使用中的关键作用。