論文

招待有り 筆頭著者
2016年3月

知識理解と資質能力育成を同時に実現するジグソー法の理論と実践

薬学雑誌. 乙号
  • 益川 弘如

136
3
開始ページ
369
終了ページ
379
記述言語
日本語
掲載種別
DOI
10.1248/yakushi.15-00231-2
出版者・発行元
公益社団法人 日本薬学会

  The Learning Sciences constitute a rapidly expanding discipline that focuses on the learning potential of humans. In this paper, I will discuss the particular learning mechanism involved in the concomitant advancement of domain knowledge and 21st century skills, as well as the Constructive Jigsaw Method of knowledge construction through collaboration—that is, collaborative problem solving. An especially important focus on knowledge construction separates routine experts from adaptive experts. While routine experts develop a core set of skills that they apply throughout their lives with increasing efficiency, adaptive experts are much more likely to change their core skills and continually expand the depth of their expertise. This restructuring of core ideas and skills may reduce their efficiency in the short run but make them more flexible in the long run. The Constructive Jigsaw Method employs a learning mechanism that encourages the development of adaptive experts. Under this method, students first study a piece of material in an expert group. One member from each of several expert groups then joins a new study group, a jigsaw group. The members of this new group then combine what they have learned, creating new knowledge and a deeper understanding of the concept through collaboration, communication, and innovation.<br>

リンク情報
DOI
https://doi.org/10.1248/yakushi.15-00231-2
J-GLOBAL
https://jglobal.jst.go.jp/detail?JGLOBAL_ID=201602219231877214
CiNii Articles
http://ci.nii.ac.jp/naid/130005131256
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000371196500003&DestApp=WOS_CPL
ID情報
  • DOI : 10.1248/yakushi.15-00231-2
  • ISSN : 0031-6903
  • J-Global ID : 201602219231877214
  • CiNii Articles ID : 130005131256
  • identifiers.cinii_nr_id : 9000002519804
  • Web of Science ID : WOS:000371196500003

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