Knowledge Graphs-Based Learner Profiles: Construction, Implementation, and Use Case

This study proposes a learner profile model based on knowledge graphs to enhance personalized learning in network marketing education. By integrating curriculum and individual learner knowledge graphs, the model enables the tracking of students' knowledge mastery, ability development, and cognitive progress. Compared to traditional methods, the model significantly improves learners' comprehension and knowledge structure by dynamically mapping individual knowledge gaps to curriculum graphs and providing real-time adaptive feedback, as demonstrated by data from the network learning platform. Furthermore, it provides personalized learning paths and targeted support, thereby optimizing teaching and learning outcomes. Future research will expand the model's application across other courses and refine its precision for better learning outcomes.