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  • 标题:An analytic framework for understanding student thinking in STEM contexts
  • 本地全文:下载
  • 作者:David Slavit ; Kristin Lesseig ; Amber Simpson
  • 期刊名称:Journal of Pedagogical Research
  • 电子版ISSN:2602-3717
  • 出版年度:2022
  • 卷号:6
  • 期号:2
  • 页码:132-148
  • DOI:10.33902/JPR.202213536
  • 语种:English
  • 出版社:Journal of Pedagogical Research
  • 摘要:The goal of this paper is to share an analytic framework for understanding Students’ Ways of Thinking (SWoT) in STEM-rich learning environments. Before revealing our refined coding framework, we detail the nature of our collaborations and the various analytic decisions that led to its formation. These collaborations supported our collective ability to make sense of SWoT and produce a more coherent perspective that can be operationalized in STEM contexts. Our analytic framework foregrounds student claim-making and the related evidence and reasoning used in support. Specific commentary about the development and application of each coding category is provided, including examples of student data and rationale for related coding decisions. Our analytic framework, and discussion of its formation, can help educators, curriculum makers, and policymakers make use of SWoT in the development of meaningful and effective STEM education.
  • 关键词:STEM education;student thinking;integrated STEM;analytic methods;Coding
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