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Knowledge Graphs as Context Sources for LLM-Based Explanations of Learning Recommendations
In the era of personalized education, the provision of comprehensible explanations for learning recommendations is of a great value to enhance the learner's understanding and engagement with the recommended learning content.
Building Contextual Knowledge Graphs for Personalized Learning Recommendations using Text Mining and Semantic Graph Completion
While hierarchical data models are commonly used in digital learning platforms, using graph-based models enables representing the context of LOs in those platforms.
Supporting Student Decisions on Learning Recommendations: An LLM-Based Chatbot with Knowledge Graph Contextualization for Conversational Explainability and Mentoring
Student commitment towards a learning recommendation is not separable from their understanding of the reasons it was recommended to them; and their ability to modify it based on that understanding.
Explainable Graph-based Search for Lessons-Learned Documents in the Semiconductor Industry
A key challenge of this sustainability is the intelligent management of the generated data, as well as the knowledge extracted from it, in order to utilize this knowledge for improving future procedures.
