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.
Sharing Linkable Learning Objects with the Use of Metadata and a Taxonomy Assistant for Categorization / Franzoni, V.; Tasso, S.; Pallottelli, S.; Perri, D.. - ELETTRONICO. - 11620 LNCS:(2019), pp. 336-348. (Intervento presentato al convegno International Conference on Computational Science and Its Applications tenutosi a Saint Petersburg, Russia nel July 1-4 2019) [10.1007/978-3-030-24296-1_28].
Sharing Linkable Learning Objects with the Use of Metadata and a Taxonomy Assistant for Categorization
Perri, D.
2019
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.File | Dimensione | Formato | |
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