Research on the Application of Shortest Path Algorithm in the Optimization of Higher Education Curriculum System

Traditional higher education course recommendation methods mostly rely on static rules or simple associations, making it difficult to dynamically generate optimal learning paths that match learners' characteristics. In this study, we propose a framework for optimizing higher education course system that integrates knowledge graph and shortest path algorithm. The framework first constructs a knowledge map of higher education courses oriented to knowledge points, which formally represents the complex logical relationships of the courses. The learning path planning problem is then converted into a problem of finding the optimal path on the knowledge graph, and an ant colony algorithm is introduced to solve the problem, which describes pheromones, heuristic functions, and other major objects, and dynamically plans the shortest learning path for the learners. The superiority of the algorithm in learning path planning rationality and personalization is verified through parameter optimization experiments and algorithm simulation experiments. The system can effectively help learners to carry out informative and high-quality learning, which provides important help to the Ministry of Education to cultivate high-quality talents.