An evaluation of rehabilitation students’ learning goals in their first year: a text mining approach

IntroductionQualitative information in the form of written reflection reports is vital for evaluating students’ progress in education. As a pilot study, we used text mining, which analyzes qualitative information with quantitative features, to investigate how rehabilitation students’ goals change du...

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出版年:Frontiers in Medicine
主要な著者: Shin Kitamura, Kotaro Takeda, Shintaro Uehara, Taiki Yoshida, Hirofumi Ota, Shigeo Tanabe, Kazuya Takeda, Soichiro Koyama, Hiroaki Sakurai, Yoshikiyo Kanada
フォーマット: 論文
言語:英語
出版事項: Frontiers Media S.A. 2024-03-01
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オンライン・アクセス:https://www.frontiersin.org/articles/10.3389/fmed.2024.1239916/full
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author Shin Kitamura
Kotaro Takeda
Shintaro Uehara
Taiki Yoshida
Hirofumi Ota
Shigeo Tanabe
Kazuya Takeda
Soichiro Koyama
Hiroaki Sakurai
Yoshikiyo Kanada
author_facet Shin Kitamura
Kotaro Takeda
Shintaro Uehara
Taiki Yoshida
Hirofumi Ota
Shigeo Tanabe
Kazuya Takeda
Soichiro Koyama
Hiroaki Sakurai
Yoshikiyo Kanada
author_sort Shin Kitamura
collection DOAJ
container_title Frontiers in Medicine
description IntroductionQualitative information in the form of written reflection reports is vital for evaluating students’ progress in education. As a pilot study, we used text mining, which analyzes qualitative information with quantitative features, to investigate how rehabilitation students’ goals change during their first year at university.MethodsWe recruited 109 first-year students (66 physical therapy and 43 occupational therapy students) enrolled in a university rehabilitation course. These students completed an open-ended questionnaire about their learning goals at the time of admission and at 6 and 12 months after admission to the university. Text mining was used to objectively interpret the descriptive text data from all three-time points to extract frequently occurring nouns at once. Then, hierarchical cluster analysis was performed to generate clusters. The number of students who mentioned at least one noun in each cluster was counted and the percentages of students in each cluster were compared for the three periods using Cochran’s Q test.ResultsThe 31 nouns that appeared 10 or more times in the 427 sentences were classified into three clusters: “Socializing,” “Practical Training,” and “Classroom Learning.” The percentage of students in all three clusters showed significant differences across the time periods (p < 0.001 for “Socializing”; p < 0.01 for “Practical Training” and “Classroom Learning”).ConclusionThese findings suggest that the students’ learning goals changed during their first year of education. This objective analytical method will enable researchers to examine transitional trends in students’ reflections and capture their psychological changes, making it a useful tool in educational research.
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spelling doaj-art-8dcfdf7ff3354f68a6eacbfa63dfb5382025-08-20T00:52:50ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2024-03-011110.3389/fmed.2024.12399161239916An evaluation of rehabilitation students’ learning goals in their first year: a text mining approachShin KitamuraKotaro TakedaShintaro UeharaTaiki YoshidaHirofumi OtaShigeo TanabeKazuya TakedaSoichiro KoyamaHiroaki SakuraiYoshikiyo KanadaIntroductionQualitative information in the form of written reflection reports is vital for evaluating students’ progress in education. As a pilot study, we used text mining, which analyzes qualitative information with quantitative features, to investigate how rehabilitation students’ goals change during their first year at university.MethodsWe recruited 109 first-year students (66 physical therapy and 43 occupational therapy students) enrolled in a university rehabilitation course. These students completed an open-ended questionnaire about their learning goals at the time of admission and at 6 and 12 months after admission to the university. Text mining was used to objectively interpret the descriptive text data from all three-time points to extract frequently occurring nouns at once. Then, hierarchical cluster analysis was performed to generate clusters. The number of students who mentioned at least one noun in each cluster was counted and the percentages of students in each cluster were compared for the three periods using Cochran’s Q test.ResultsThe 31 nouns that appeared 10 or more times in the 427 sentences were classified into three clusters: “Socializing,” “Practical Training,” and “Classroom Learning.” The percentage of students in all three clusters showed significant differences across the time periods (p < 0.001 for “Socializing”; p < 0.01 for “Practical Training” and “Classroom Learning”).ConclusionThese findings suggest that the students’ learning goals changed during their first year of education. This objective analytical method will enable researchers to examine transitional trends in students’ reflections and capture their psychological changes, making it a useful tool in educational research.https://www.frontiersin.org/articles/10.3389/fmed.2024.1239916/fullcluster analysisprofessional educationrehabilitationstudentstext mining
spellingShingle Shin Kitamura
Kotaro Takeda
Shintaro Uehara
Taiki Yoshida
Hirofumi Ota
Shigeo Tanabe
Kazuya Takeda
Soichiro Koyama
Hiroaki Sakurai
Yoshikiyo Kanada
An evaluation of rehabilitation students’ learning goals in their first year: a text mining approach
cluster analysis
professional education
rehabilitation
students
text mining
title An evaluation of rehabilitation students’ learning goals in their first year: a text mining approach
title_full An evaluation of rehabilitation students’ learning goals in their first year: a text mining approach
title_fullStr An evaluation of rehabilitation students’ learning goals in their first year: a text mining approach
title_full_unstemmed An evaluation of rehabilitation students’ learning goals in their first year: a text mining approach
title_short An evaluation of rehabilitation students’ learning goals in their first year: a text mining approach
title_sort evaluation of rehabilitation students learning goals in their first year a text mining approach
topic cluster analysis
professional education
rehabilitation
students
text mining
url https://www.frontiersin.org/articles/10.3389/fmed.2024.1239916/full
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