基于大语言模型的职业院校区域间发展差异比较研究——以北京市和甘肃省为研究样本

Comparative Study on Regional Development Differences of Vocational Colleges Based on Large Language Models——Taking Beijing and Gansu as Samples

鉴于中国地域辽阔、经济发展不均衡的国情,识别职业教育在各地表现的差异性对于科学统筹全国职业教育的高质量发展意义重大。利用大语言模型ChatGPT,通过Python程序调用API,对北京市和甘肃省职业院校发布的质量年度报告进行本体关系构建,深入对比分析两地区在人才培养与产教融合方面发展的相似性与差异性。结果显示,北京市凭借其丰富的教育资源,更加注重教师团队、课程设置等关键资源的投入,以增强职业院校的建设水平和创新能力;而甘肃省则更加侧重于学生在校的学习质量保障,就业所需的实际技能,致力于培养适应当地社会经济发展需求的实践性人才。

Given China’s vast territory and unbalanced economic development,identifying the differences in the performance of vocational education across regions is of great significance for scientifically coordinating the high-quality development of vocational education nationwide.In this paper,we use the large language model ChatGPT,and invoke its API through the program Python to construct the ontology relationship of the annual quality reports issued by vocational colleges in Beijing and Gansu Province.The similarities and differences between the two regions in personnel training and the industry-education integration are analyzed.The results showed that Beijing,with its abundant educational resources,places more emphasis on the investment in key resources such as teaching teams and curriculum settings to enhance the construction level and innovation capability of vocational colleges.In contrast,Gansu focuses more on ensuring the quality of students’learning and the practical skills needed for employment,aiming to cultivate practical talents that meet the local socio-economic development needs.