Generation of reusable learning objects from digital medical collections: An analysis based on the MASMDOA framework

Fuente: Zenodo
Saved in:
Bibliographic Details
Main Authors: Buendia, Felix, Gayoso-Cabada, Joaquin, Sierra Rodríguez, José
Format: Recurso digital
Language:English
Published: Zenodo 2021
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866901251213492224
author Buendia, Felix
Gayoso-Cabada, Joaquin
Sierra Rodríguez, José
author_facet Buendia, Felix
Gayoso-Cabada, Joaquin
Sierra Rodríguez, José
contents <p>Learning Objects represent a widespread approach to structuring instructional materials in a large variety of educational contexts. The main aim of this work consists of analyzing from a qualitative point of view the process of generating reusable learning objects (RLOs) followed by Clavy, a tool that can be used to retrieve data from multiple medical knowledge sources and reconfigure such sources in diverse multimedia-based structures and organizations. From these organizations, Clavy is able to generate learning objects which can be adapted to various instructional healthcare scenarios with several types of user profiles and distinct learning requirements. Moreover, Clavy provides the capability of exporting these learning objects through educational standard specifications, which improves their reusability features. The analysis insights highlight the importance of having a tool able to transfer knowledge from the available digital medical collections to learning objects that can be easily accessed by medical students and healthcare practitioners through the most popular e-learning platforms.</p>
format Recurso digital
id zenodo_https___doi_org_10_1177_1460458220977586
institution Zenodo
language eng
publishDate 2021
publisher Zenodo
record_format zenodo
spellingShingle Generation of reusable learning objects from digital medical collections: An analysis based on the MASMDOA framework
Buendia, Felix
Gayoso-Cabada, Joaquin
Sierra Rodríguez, José
<p>Learning Objects represent a widespread approach to structuring instructional materials in a large variety of educational contexts. The main aim of this work consists of analyzing from a qualitative point of view the process of generating reusable learning objects (RLOs) followed by Clavy, a tool that can be used to retrieve data from multiple medical knowledge sources and reconfigure such sources in diverse multimedia-based structures and organizations. From these organizations, Clavy is able to generate learning objects which can be adapted to various instructional healthcare scenarios with several types of user profiles and distinct learning requirements. Moreover, Clavy provides the capability of exporting these learning objects through educational standard specifications, which improves their reusability features. The analysis insights highlight the importance of having a tool able to transfer knowledge from the available digital medical collections to learning objects that can be easily accessed by medical students and healthcare practitioners through the most popular e-learning platforms.</p>
title Generation of reusable learning objects from digital medical collections: An analysis based on the MASMDOA framework
url https://doi.org/10.1177/1460458220977586