Course planning is essential for academic success and the achievement of personal goals. Although universities provide course syllabi and curriculum maps for course planning, integrating and understanding these resources by the learners themselves for effective course planning is time-consuming and difficult. To address this issue, this study proposes a method that uses generative AI to classify relationships between subjects and generate explanatory texts describing the connections of subjects and positions of subjects within the curriculum based on subject and curriculum information. An evaluation experiment involving learners demonstrated a classification accuracy of approximately 70% for inter-subject relationships. Furthermore, our experimental results confirm that that the generated explanatory texts significantly enhance the understanding of relationships between subjects, and are thus effective for course planning. [For the full proceedings, see ED665357.]