Abstract:Scientific education serves as a crucial foundation for enhancing the scientific literacy of the entire population and cultivating innovative talents. Relevant policies play a pivotal role in ensuring the high-quality development of the scientific education sector. In order to facilitate the continuous and in-depth advancement of science and education in our country, this study, based on the texts of scientific education policies at both the central and local levels, utilizes Natural Language Processing (NLP) technology to construct a "Space-Time-Subject-Content-Theme" model for quantitative research and comparative analysis of the internal structure and external attributes of these policies.The research findings indicate that there is a high degree of consistency in the temporal dimension of scientific education policies between the central and local levels. However, significant disparities exist in terms of issuing authorities, content, and themes, reflecting diverse perspectives and expressions regarding the key components and distinctive features of scientific education at different levels of governance. Concurrently, there are certain similarities in the texts of policies at both levels, illustrating common concerns and policy coordination regarding the philosophical underpinnings, roles, and subjects of scientific education.Based on these observations, the study proposes recommendations, including optimizing the balanced allocation of scientific education resources, deepening the collaborative efforts between the central and local authorities in policy formulation, strengthening policy implementation, and establishing an evaluation mechanism for the effectiveness of scientific education policies. These suggestions aim to provide guidance for optimizing China"s scientific education policies, promoting the balanced development and quality improvement of scientific education.
