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An intelligent tutoring system for supporting active learning: A case study on predictive parsing learning
The way in which people learn and institutions teach is changing due to the ever-increasing impact of technology. People access the Internet anywhere, anytime and request online training. This has brought about the creation of numerous online learning platforms which offer comprehensive and effectiv...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7495305/ https://www.ncbi.nlm.nih.gov/pubmed/32958966 http://dx.doi.org/10.1016/j.ins.2020.08.079 |
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author | Castro-Schez, J.J. Glez-Morcillo, C. Albusac, J. Vallejo, D. |
author_facet | Castro-Schez, J.J. Glez-Morcillo, C. Albusac, J. Vallejo, D. |
author_sort | Castro-Schez, J.J. |
collection | PubMed |
description | The way in which people learn and institutions teach is changing due to the ever-increasing impact of technology. People access the Internet anywhere, anytime and request online training. This has brought about the creation of numerous online learning platforms which offer comprehensive and effective educational solutions which are 100% online. These platforms benefit from intelligent tutoring systems that help and guide students through the learning process, emulating the behavior of a human tutor. However, these systems give the student little freedom to experiment with the knowledge of the subject, that is, they do not allow him/her to propose and carry out tasks on his/her own initiative. They are very restricted systems in term of what the student can do, as the tasks are defined in advance. An intelligent tutoring system is proposed in this paper to encourage students to learn through experimentation, proposing tasks on their own initiative, which involves putting into use all the skills, abilities tools and knowledge needed to successfully solve them. This system has been designed developed and applied for learning predictive parsing techniques and has been used by Computer Science students during four academic courses to evaluate its suitability for improving the student’s learning process. |
format | Online Article Text |
id | pubmed-7495305 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74953052020-09-17 An intelligent tutoring system for supporting active learning: A case study on predictive parsing learning Castro-Schez, J.J. Glez-Morcillo, C. Albusac, J. Vallejo, D. Inf Sci (N Y) Article The way in which people learn and institutions teach is changing due to the ever-increasing impact of technology. People access the Internet anywhere, anytime and request online training. This has brought about the creation of numerous online learning platforms which offer comprehensive and effective educational solutions which are 100% online. These platforms benefit from intelligent tutoring systems that help and guide students through the learning process, emulating the behavior of a human tutor. However, these systems give the student little freedom to experiment with the knowledge of the subject, that is, they do not allow him/her to propose and carry out tasks on his/her own initiative. They are very restricted systems in term of what the student can do, as the tasks are defined in advance. An intelligent tutoring system is proposed in this paper to encourage students to learn through experimentation, proposing tasks on their own initiative, which involves putting into use all the skills, abilities tools and knowledge needed to successfully solve them. This system has been designed developed and applied for learning predictive parsing techniques and has been used by Computer Science students during four academic courses to evaluate its suitability for improving the student’s learning process. Elsevier Inc. 2021-01-12 2020-09-17 /pmc/articles/PMC7495305/ /pubmed/32958966 http://dx.doi.org/10.1016/j.ins.2020.08.079 Text en © 2020 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Castro-Schez, J.J. Glez-Morcillo, C. Albusac, J. Vallejo, D. An intelligent tutoring system for supporting active learning: A case study on predictive parsing learning |
title | An intelligent tutoring system for supporting active learning: A case study on predictive parsing learning |
title_full | An intelligent tutoring system for supporting active learning: A case study on predictive parsing learning |
title_fullStr | An intelligent tutoring system for supporting active learning: A case study on predictive parsing learning |
title_full_unstemmed | An intelligent tutoring system for supporting active learning: A case study on predictive parsing learning |
title_short | An intelligent tutoring system for supporting active learning: A case study on predictive parsing learning |
title_sort | intelligent tutoring system for supporting active learning: a case study on predictive parsing learning |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7495305/ https://www.ncbi.nlm.nih.gov/pubmed/32958966 http://dx.doi.org/10.1016/j.ins.2020.08.079 |
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