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Experience of distance education for project-based learning in data science.
Sakamaki, Kentaro; Taguri, Masataka; Nishiuchi, Hiromu; Akimoto, Yoshitomo; Koizumi, Kazuyuki.
Afiliação
  • Sakamaki K; Center for Data Science, Yokohama City University, 22-2 Seto, Kanazawa-ku, Yokohama, 236-0027 Japan.
  • Taguri M; Department of Data Science, Graduate School of Data Science, Yokohama City University, Yokohama, Japan.
  • Nishiuchi H; Department of Data Science, Graduate School of Data Science, Yokohama City University, Yokohama, Japan.
  • Akimoto Y; Center for Data Science, Yokohama City University, 22-2 Seto, Kanazawa-ku, Yokohama, 236-0027 Japan.
  • Koizumi K; Department of Data Science, Graduate School of Data Science, Yokohama City University, Yokohama, Japan.
Jpn J Stat Data Sci ; 5(2): 757-767, 2022.
Article em En | MEDLINE | ID: mdl-35434522
ABSTRACT
Data science plays an important role in many fields. Project-based learning is an effective teaching approach because students can learn data science practices based on real-world problems and real-world data. Because of a pandemic of COVID-19, we provided project-based learning as distance education (synchronic distance education). In this study, we explain how we developed and conducted it and provide survey results from students. The survey showed about 30% of the students found it difficult to communicate with each other and with teachers. However, it suggested that they could communicate to some extent even by remote group work. We found that, in remote communication, it is important to see the faces of all the students (and teachers) on the Zoom screen when they discuss using screen sharing. There remain some challenges such as timing to start talking and casual questions to teachers. Although some issues should be improved, distance education for project-based learning in data science can be implemented effectively. Supplementary Information The online version contains supplementary material available at 10.1007/s42081-022-00154-2.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Jpn J Stat Data Sci Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Jpn J Stat Data Sci Ano de publicação: 2022 Tipo de documento: Article
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