Publication | Closed Access
Investigating Learning Resources Precedence Relations via Concept Prerequisite Learning
14
Citations
12
References
2018
Year
Unknown Venue
Concept FormationEngineeringKnowledge ExtractionConceptual Knowledge AcquisitionSemanticsLanguage LearningNatural Language ProcessingInformation RetrievalData ScienceComputational LinguisticsAutomatic IdentificationLanguage StudiesCognitive ScienceKnowledge AcquisitionLearning SciencesKnowledge DiscoveryEducational Data MiningConcept Prerequisite LearningLearning AnalyticsComputer ScienceSymbolic Machine LearningAutomated Knowledge AcquisitionAutomated ReasoningPrecedence RelationshipsPrerequisite RelationshipsLinguistics
The identification of prerequisite relationships among concepts is a fundamental step toward the organization of knowledge for educational purposes. In the context of a learning process, simplest concepts that are requirements to understand and address more complex concepts should be presented first. Therefore, the identification of prerequisite relationships is a fundamental step for effective course design and automatic learning path generation systems. Although there have been recent advances in machine learning methods for the automatic identification of prerequisite relationships between concepts, little research has been done on whether these automatic strategies can be extended to establish precedence relationships among learning resources. The precedence relation between two learning resources establishes which of the resources must be presented first. In this paper, we approach this problem and propose a strategy to identify the precedence relation. Given two learning resources our strategy analyzes prerequisites among the concepts addressed by the learning resources to estimate the precedence relation. A set of 1588 pairs of learning resources extracted from MOOCs refined by human experts is used to evaluate the strategy. The experimental results show that it is possible to identify the precedence relation between learning resources through the automatic identification of prerequisite relationships between concepts.
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