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

TL;DR

This paper presents a redesigned Moodledata module to facilitate sharing linkable learning objects with metadata and taxonomy assistance, enhancing interoperability and automated classification across e-learning platforms.

Contribution

It introduces a new approach for sharing and classifying learning objects using metadata and an enhanced taxonomy assistant within an AI-enabled environment.

Findings

Successful integration of linkable learning objects between Moodle and G-Lorep.

Improved automated classification using semantic and structural similarity measures.

Enhanced reuse and contextual classification of e-learning content.

Abstract

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.