Personalized Learning Resource Recommendation Framework Based on Knowledge Map

Abstract

The knowledge space theory can better understand the knowledge concept and its internal connection by analyzing and understanding the connection and combination of knowledge concepts. A personalized learning resource recommendation framework based on knowledge space theory is designed to help students better understand and master subject knowledge in this paper. The framework mainly includes the following three steps: firstly, analyze the students' learning behavior, and establish the student knowledge space model; secondly, establish the subject knowledge space model by analyzing the structure and relationship of subject knowledge; finally, according to the student's The knowledge space model and subject knowledge space model design personalized learning resource recommendation algorithms to provide students with the most suitable learning resources. Experiments are conducted to verify the validity and feasibility of the framework, as well as its impact on student learning outcomes.