Content-Based Learning Object Recommendation System Using a User Profile Ontology for High School Students

Bruna Morillo-Palacios, Juan Gutiérrez-Cárdenas

Research output: Chapter in Book/Report/Conference proceedingPaper (Conference contribution)peer-review

Abstract

The lack of quality of education in Peruvian schools has caused young people to look for other ways to obtain information, of which the web stands out. However, this tool is made up of billions of web pages, which affects the time each student takes to search. To address this situation, we propose the development of a content-based recommendation system that uses ontologies for data storage. Our recommender system allows the user profile data to be integrated into the model to consider its characteristics as part of the recommendation. We carried out two sets of validations for the evaluation of our proposal, one with expert judgment and the other by gathering the opinion of the end-users. As a result of the first evaluation, we found that 76.25% of the items were highly related to the search. For the second evaluation, we found that our system obtained a usability of 78.67%, considering the opinion of the students tested.

Original languageEnglish
Title of host publicationProceedings of the Future Technologies Conference, FTC 2020, Volume 1
EditorsKohei Arai, Supriya Kapoor, Rahul Bhatia
PublisherSpringer Science and Business Media Deutschland GmbH
Pages838-858
Number of pages21
ISBN (Print)9783030631277
DOIs
StatePublished - 2021
EventFuture Technologies Conference, FTC 2020 - San Francisco, United States
Duration: 5 Nov 20206 Nov 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1288
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

ConferenceFuture Technologies Conference, FTC 2020
CountryUnited States
CitySan Francisco
Period5/11/206/11/20

Keywords

  • Content based
  • Education
  • Learning objects
  • Ontologies
  • Recommender system

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