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The EEG-Based Attention Analysis in Multimedia m-Learning
In recent years, research on brain-computer interfaces has been increasing in the field of education, and mobile learning has become a very important way of learning. In this study, EEG experiment of a group of iPad-based mobile learners was conducted through algorithm optimization on the TGAM chip....
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303747/ https://www.ncbi.nlm.nih.gov/pubmed/32587629 http://dx.doi.org/10.1155/2020/4837291 |
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author | Ni, Dan Wang, Shuo Liu, Guocheng |
author_facet | Ni, Dan Wang, Shuo Liu, Guocheng |
author_sort | Ni, Dan |
collection | PubMed |
description | In recent years, research on brain-computer interfaces has been increasing in the field of education, and mobile learning has become a very important way of learning. In this study, EEG experiment of a group of iPad-based mobile learners was conducted through algorithm optimization on the TGAM chip. Under the three learning media (text, text + graphic, and video), the researchers analyzed the difference in learners' attention. The study found no significant difference in attention in different media, but learners using text media had the highest attention value. Later, the researchers studied the attention of learners with different learning styles and found that active and reflective learners' attention exhibited significant differences when using video media to learn. |
format | Online Article Text |
id | pubmed-7303747 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-73037472020-06-24 The EEG-Based Attention Analysis in Multimedia m-Learning Ni, Dan Wang, Shuo Liu, Guocheng Comput Math Methods Med Research Article In recent years, research on brain-computer interfaces has been increasing in the field of education, and mobile learning has become a very important way of learning. In this study, EEG experiment of a group of iPad-based mobile learners was conducted through algorithm optimization on the TGAM chip. Under the three learning media (text, text + graphic, and video), the researchers analyzed the difference in learners' attention. The study found no significant difference in attention in different media, but learners using text media had the highest attention value. Later, the researchers studied the attention of learners with different learning styles and found that active and reflective learners' attention exhibited significant differences when using video media to learn. Hindawi 2020-06-10 /pmc/articles/PMC7303747/ /pubmed/32587629 http://dx.doi.org/10.1155/2020/4837291 Text en Copyright © 2020 Dan Ni et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ni, Dan Wang, Shuo Liu, Guocheng The EEG-Based Attention Analysis in Multimedia m-Learning |
title | The EEG-Based Attention Analysis in Multimedia m-Learning |
title_full | The EEG-Based Attention Analysis in Multimedia m-Learning |
title_fullStr | The EEG-Based Attention Analysis in Multimedia m-Learning |
title_full_unstemmed | The EEG-Based Attention Analysis in Multimedia m-Learning |
title_short | The EEG-Based Attention Analysis in Multimedia m-Learning |
title_sort | eeg-based attention analysis in multimedia m-learning |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303747/ https://www.ncbi.nlm.nih.gov/pubmed/32587629 http://dx.doi.org/10.1155/2020/4837291 |
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