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Sharing Linkable Learning Objects with the use of Metadata and a Taxonomy Assistant for Categorization

arXiv 2212.05947 ↗First posted 9 Dec 2022cs.OH cs.AIcited by 0

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Abstract (arXiv)

In this work, a re-design of the Moodledata module functionalities is presented to share learning objects between e-learning content platforms, e.g., Moodle and G-Lorep, in a linkable object format. The e-learning courses content of the Drupal-based Content Management System G-Lorep for academic learning is exchanged designing an object incorporating metadata to support the reuse and the classification in its context. In such an Artificial Intelligence environment, the exchange of Linkable Learning Objects can be used for dialogue between Learning Systems to obtain information, especially with the use of semantic or structural similarity measures to enhance the existent Taxonomy Assistant for advanced automated classification.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 40 references that are in the map. First posted on arXiv 9 Dec 2022.

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References · 2

  1. 2016Web-based Semantic Similarity for Emotion Recognition in Web Objectscited by 3
  2. 2017Semantic Evolutionary Concept Distances for Effective Information Retrieval in Query Expansioncited by 1

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