工业技术与职业教育

为了有效推动生成式AI在船舶类人才培养中的应用，从价值意蕴、潜在风险和优化路径等3个维度，对生成式AI赋能船舶类人才培养进行了深入研究。研究结果表明，生成式AI在教学过程中展现出重塑教师角色和助力学生学习的双重潜力；然而，生成式AI在船舶类人才培养中的应用仍面临若干潜在风险。对教师而言，主要潜在风险包括教学能力退化、教学资源把控难度增加和学术诚信监管难度加大等风险。对学生而言，主要潜在风险则体现在知识理解浅层化、实践能力退化和学术诚信失范等方面。为应对上述的潜在风险，从“教育部门、高校、教师和学生”四位一体角度提出生成式AI赋能船舶类人才培养的优化路径。

To effectively promote the application of generative AI in the cultivation of shipbuilding professionals, an in-depth study on the empowerment of generative AI in shipbuilding-related talent development from three dimensions: value significance, potential risks, and optimization pathways, was conducted. The research findings indicate that generative AI exhibits dual potential in the teaching process, namely reshaping the role of teachers and facilitating students' learning. However, the application of generative AI in the cultivation of shipping-related talents still faces several potential risks. For educators, the primary risks include the degradation of teaching capabilities, increased difficulty in controlling teaching resources, and heightened challenges in academic integrity supervision. For students, the main risks manifest as superficial knowledge comprehension, the decline of practical skills, and academic misconduct. To address these potential risks, an optimized pathway for generative AI-enabled shipbuilding talent cultivation is proposed from a "four-in-one" perspective involving education departments, universities, teachers, and students.