Mapping Knowledge Points to OBE Goals in Financial Management Curriculum via Artificial Intelligence and Knowledge Graphs

It is crucial to align course design with measurable learning outcomes in light of the increasing emphasis on Outcome-Based Education (OBE) in contemporary pedagogical reforms. This study combines knowledge graph systems with OBE rules to establish a comprehensive framework for financial management knowledge. Key concepts and logical relationships were extracted from authoritative textbooks using natural language processing (NLP) techniques. A knowledge graph was constructed by Neo4j, which plainly reflects the hierarchical structure and relationships among these information items. Further, the study statistically assessed the impact of semantic similarity computations and network analysis techniques like PageRank on mapping information points to particular OBE objectives. Improved alignment between knowledge points and OBE objectives is demonstrated by experimental results that show a 6% increase in semantic similarity and a 30% decrease in mapping variance. In addition, utilizing the knowledge graph for teaching optimization resulted in a 7% decrease in overall course satisfaction and a 15% decrease in the core knowledge acquisition time. These results highlight the potential for using AI-driven systems and data analysis to improve lesson design in online education settings.