【摘要】 针对生成式人工智能在高职教育中存在技术接受与学习能力脱节的现实问题，结合技术接受模型，探究技术接受度与高职学生学习能力的关联及情境异质性。以江苏3所高职院校的245名学生为研究对象，采用问卷调查法，通过结构方程模型等分析技术接受度与学习能力的关系。研究发现：感知有用性、感知易用性均与学习能力显著正相关，感知有用性是更关键的驱动因素；技术接受度对学习能力有综合促进效应，且与高年级、理工专业学生的关联更强。基于上述分析，提出三方面建议：首先，重视对学生技术接受度的引导，强化对感知有用性的认知；其次，针对不同年级、不同专业学生实施差异化赋能策略；最后，加大对教师生成式人工智能应用能力的培训，推动技术与教学深度融合。更多还原

【Abstract】 Aiming at the practical problem of the disconnection between technology acceptance and learning ability of generative artificial intelligence in higher vocational education, based on the technology acceptance model, this paper explores the correlation and situational heterogeneity between technology acceptance and learning ability. Taking 245 students from three higher vocational colleges in Jiangsu as the research objects, the study analyzes the relationship between technology acceptance and learning ability by means of questionnaire survey and structural equation model. The results show that perceived usefulness and perceived ease of use are both significantly positively correlated with learning ability, and perceived usefulness is a more critical driving factor. Technology acceptance has a comprehensive promoting effect on learning ability, and has a stronger correlation with senior students and students majoring in science and engineering. Based on the above analysis, three suggestions are put forward: first, pay attention to the guidance of students′ technology acceptance and strengthening the cognition of perceived usefulness; second, implement differentiated empowerment strategies for students of different grades and majors; finally, increase the training of teachers′ application ability of generative artificial intelligence, and promote the deep integration of technology and teaching.更多还原