Where

• KIAS-KU International Workshop
  Theoretical Challenges in Network Science

When

• Nov 4th to 8th

Where

• Korea Institute for Advanced Study

• P15

What

• Science and Technology related Undergraduate Curriculum Data

Who

• Gahyoun GIM 1, Jinhyuk YUN 2, Sang Hoon LEE 1,*

  • (1Department of Physics, Gyeongsang National University, 2School of AI Convergence, Soongsil University)

How(Abstract)

• • Most of the current research topics on “science of science” are centered around journal-based research activities, while those research activities are based on knowledge acquisition during formal education and training in science, technology, engineering, and mathematics (STEM) from undergraduate years. Therefore, it is essential to map the structure of STEM education in universities for a comprehensive understanding of contemporary scientific progress. As a first step toward that goal, we assess the raw data composed of 126,347 undergraduate courses from 2,841 STEM departments across 161 institutions for the 2024 spring semester, publicly provided by the Ministry of Education in Korea. To remove the effectively duplicated entries and errors in the raw course data, we process the raw data by considering higher-order interactions following the data preprocessing conducted via a large language model (LLM) and establish 24,467 standardized courses as nodes used in the following network analysis. This yields the bipartite network of standardized courses and institution departments conducting the courses, weighted by the course credit. From the scale-dependent community analysis of its department-mode projection, we observe a semi-hierarchical reorganization of departments, starting from the division of “hard”, “soft”, and “technical” science/engineering in the lowest resolution. Another notable example is a nontrivial reorganization of interdisciplinary departments across different scales. From the standardized course data, we plan to extract mesoscale structures, e.g., local hubs forming the core courses for each discipline and interdisciplinary courses connecting different communities, and directional information, e.g., curriculum prerequisite and postrequisite courses. Based on the analysis, we expect a more systematic assessment of the current university-level STEM education structure in Korea and possibly provide a quantitative guideline to design a new curriculum for newly emerging or interdisciplinary academic units.