Differentiating the learning styles of college students in different disciplines in a college English blended learning setting.
Learning styles are critical to educational psychology, especially when investigating various contextual factors that interact with individual learning styles. Drawing upon Biglan's taxonomy of academic tribes, this study systematically analyzed the learning styles of 790 sophomores in a blende...
Guardado en:
Autores principales: | , , , |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Public Library of Science (PLoS)
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/e9af4009b8cc4fe79f053228f0e6342f |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
id |
oai:doaj.org-article:e9af4009b8cc4fe79f053228f0e6342f |
---|---|
record_format |
dspace |
spelling |
oai:doaj.org-article:e9af4009b8cc4fe79f053228f0e6342f2021-11-25T06:23:45ZDifferentiating the learning styles of college students in different disciplines in a college English blended learning setting.1932-620310.1371/journal.pone.0251545https://doaj.org/article/e9af4009b8cc4fe79f053228f0e6342f2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0251545https://doaj.org/toc/1932-6203Learning styles are critical to educational psychology, especially when investigating various contextual factors that interact with individual learning styles. Drawing upon Biglan's taxonomy of academic tribes, this study systematically analyzed the learning styles of 790 sophomores in a blended learning course with 46 specializations using a novel machine learning algorithm called the support vector machine (SVM). Moreover, an SVM-based recursive feature elimination (SVM-RFE) technique was integrated to identify the differential features among distinct disciplines. The findings of this study shed light on the optimal feature sets that collectively determined students' discipline-specific learning styles in a college blended learning setting.Jie HuYi PengXueliang ChenHangyan YuPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 5, p e0251545 (2021) |
institution |
DOAJ |
collection |
DOAJ |
language |
EN |
topic |
Medicine R Science Q |
spellingShingle |
Medicine R Science Q Jie Hu Yi Peng Xueliang Chen Hangyan Yu Differentiating the learning styles of college students in different disciplines in a college English blended learning setting. |
description |
Learning styles are critical to educational psychology, especially when investigating various contextual factors that interact with individual learning styles. Drawing upon Biglan's taxonomy of academic tribes, this study systematically analyzed the learning styles of 790 sophomores in a blended learning course with 46 specializations using a novel machine learning algorithm called the support vector machine (SVM). Moreover, an SVM-based recursive feature elimination (SVM-RFE) technique was integrated to identify the differential features among distinct disciplines. The findings of this study shed light on the optimal feature sets that collectively determined students' discipline-specific learning styles in a college blended learning setting. |
format |
article |
author |
Jie Hu Yi Peng Xueliang Chen Hangyan Yu |
author_facet |
Jie Hu Yi Peng Xueliang Chen Hangyan Yu |
author_sort |
Jie Hu |
title |
Differentiating the learning styles of college students in different disciplines in a college English blended learning setting. |
title_short |
Differentiating the learning styles of college students in different disciplines in a college English blended learning setting. |
title_full |
Differentiating the learning styles of college students in different disciplines in a college English blended learning setting. |
title_fullStr |
Differentiating the learning styles of college students in different disciplines in a college English blended learning setting. |
title_full_unstemmed |
Differentiating the learning styles of college students in different disciplines in a college English blended learning setting. |
title_sort |
differentiating the learning styles of college students in different disciplines in a college english blended learning setting. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2021 |
url |
https://doaj.org/article/e9af4009b8cc4fe79f053228f0e6342f |
work_keys_str_mv |
AT jiehu differentiatingthelearningstylesofcollegestudentsindifferentdisciplinesinacollegeenglishblendedlearningsetting AT yipeng differentiatingthelearningstylesofcollegestudentsindifferentdisciplinesinacollegeenglishblendedlearningsetting AT xueliangchen differentiatingthelearningstylesofcollegestudentsindifferentdisciplinesinacollegeenglishblendedlearningsetting AT hangyanyu differentiatingthelearningstylesofcollegestudentsindifferentdisciplinesinacollegeenglishblendedlearningsetting |
_version_ |
1718413776610394112 |