Prerequisite Relation Learning for Concepts in MOOCs
What prerequisite knowledge should students achieve a level of mastery before moving forward to learn subsequent coursewares? We study the extent to which the prerequisite relation between knowledge concepts in Massive Open Online Courses (MOOCs) can be inferred automatically. In particular, what kinds of information can be leverage to uncover the potential prerequisite relation between knowledge concepts. We first propose a representation learning-based method for learning latent representations of course concepts, and then investigate how different features capture the prerequisite relations between concepts. Our experiments on three datasets form Coursera show that the proposed method achieves significant improvements (+5.9-48.0{\%} by F1-score) comparing with existing methods.
Code (0)
등록된 구현이 없습니다.
Tasks
RelationRepresentation LearningSimilar Papers 제목 키워드 기반
MOOCCube: A Large-scale Data Repository for NLP Applications in MOOCs
The prosperity of Massive Open Online Courses (MOOCs) provides fodder for many NLP and AI research for education applications, e.g., course concept extraction, prerequisite relation discovery, etc. However, the publicly …
MAssistant: A Personal Knowledge Assistant for MOOC Learners
Massive Open Online Courses (MOOCs) have developed rapidly and attracted large number of learners. In this work, we present MAssistant system, a personal knowledge assistant for MOOC learners. MAssistant helps users to t…
ManagementLeveraging Graph Retrieval-Augmented Generation to Support Learners' Understanding of Knowledge Concepts in MOOCs
Massive Open Online Courses (MOOCs) lack direct interaction between learners and instructors, making it challenging for learners to understand new knowledge concepts. Recently, learners have increasingly used Large Langu…
Knowledge GraphsQuestion AnsweringQuestion GenerationQuestion-Generation+2CLLMRec: LLM-powered Cognitive-Aware Concept Recommendation via Semantic Alignment and Prerequisite Knowledge Distillation
The growth of Massive Open Online Courses (MOOCs) presents significant challenges for personalized learning, where concept recommendation is crucial. Existing approaches typically rely on heterogeneous information networ…
Knowledge DistillationKnowledge TracingKnowledge GraphsCourse Concept Extraction in MOOCs via Embedding-Based Graph Propagation
Massive Open Online Courses (MOOCs), offering a new way to study online, are revolutionizing education. One challenging issue in MOOCs is how to design effective and fine-grained course concepts such that students with d…