Cross-modal adaptive reconstruction of open education resources.

ABSTRACT: Matching vast online resources to individual learners' needs remains a major challenge, especially for adults with diverse backgrounds. To address this challenge, we proposed a Dynamic Knowledge Graph-enhanced Cross-Modal Recommendation model (DKG-CMR) to solve the problem. This model utilizes a dynamic knowledge graph-a structure organizing information and relationships-that continuously updates based on learner actions and course objectives. DKG-CMR focuses on three key improvements: (1) Aligning meaning across different data types (e.g., text, video, user behavior logs). (2) Maintaining the knowledge graph's real-time relevance. (3) Reducing the cognitive demand of recommendations (optimizing cognitive efficiency). Our approach employs contrastive learning (a technique for similarity le

SUBMITTER: Shengju T 

PROVIDER: S-EPMC12373862 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature