Multi-label Search Model for Open Educational Resources Based on Learning Purpose

Klinge Villalba-Condori, Lushianna Tejada-Ortega, Julio Vera-Sancho, Jorge Mamani-Calcina, Cesar Vera-Vasquez, Héctor Cardona-Reyes

Research output: Chapter in Book/ReportConference contributionpeer-review

Abstract

The Open Educational Resources (OER) repositories store a large quantity and variety of data from multiple sources, and that present relevant and useful information for the student training process, improving student performance thanks to more up-to-date and didactic educational content, this generates the need for a more specialized Learning Objects (LO) search system. In this research work, a multi-label search platform is proposed based on the learning purpose that unifies the information from different OER in a single platform, using an information extraction process based on Web Scraping techniques and generating a selection of one of them. Or multiple tags, based on the SOLO taxonomy, using an MLP-based multi-tag classifier. As a result, we obtained the improvement of the most specialized search and content according to what teachers really need, up to 85% accuracy of the resources they needed and approval of the use of the platform up to 78.57%.

Original languageAmerican English
Title of host publicationHuman-Computer Interaction - 8th Iberoamerican Workshop, HCI-COLLAB 2022, Revised Selected Papers
EditorsVanessa Agredo-Delgado, Pablo H. Ruiz, Vanessa Agredo-Delgado, Pablo H. Ruiz, Omar Correa-Madrigal
PublisherSpringer Science and Business Media Deutschland GmbH
Pages130-145
Number of pages16
ISBN (Print)9783031247088
DOIs
StateIndexed - 2022
Event8th Ibero-American Workshop on Human-Computer Interaction, HCI-COLLAB 2022 - Havana, Cuba
Duration: 13 Oct 202215 Oct 2022

Publication series

NameCommunications in Computer and Information Science
Volume1707 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference8th Ibero-American Workshop on Human-Computer Interaction, HCI-COLLAB 2022
Country/TerritoryCuba
CityHavana
Period13/10/2215/10/22

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • Machine learning
  • Open educational resources
  • Scrapy

Fingerprint

Dive into the research topics of 'Multi-label Search Model for Open Educational Resources Based on Learning Purpose'. Together they form a unique fingerprint.

Cite this