Linear Quantity Models in US and Chinese Elementary Mathematics Classrooms

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  • Author(s): Ding, Meixia (ORCID Ding, Meixia (ORCID 0000-0002-5820-0684); Chen, Wei; Hassler, Ryan Scott
  • Language:
    English
  • Source:
    Mathematical Thinking and Learning: An International Journal. 2019 21(2):105-130.
  • Publication Date:
    2019
  • Document Type:
    Journal Articles
    Reports - Research
  • Additional Information
    • Availability:
      Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
    • Peer Reviewed:
      Y
    • Source:
      26
    • Sponsoring Agency:
      National Science Foundation (NSF)
    • Contract Number:
      1350068
    • Education Level:
      Elementary Education
    • Subject Terms:
    • Subject Terms:
    • Accession Number:
      10.1080/10986065.2019.1570834
    • ISSN:
      1098-6065
    • Abstract:
      Linear quantity models such as pre-tapes, tape diagrams, and number line diagrams have drawn increasing attention in mathematics education around the world. However, we still know relatively little about how teachers actually use these models in the classroom. This study explores how exemplary US and Chinese elementary teachers use linear quantity models during mathematics instruction. Based on an examination of 64 videotaped lessons on inverse relations, we identified 110 "diagram episodes." An analysis of these episodes reveals that linear quantity models, especially tape diagrams, were used more frequently in US classrooms than in Chinese classrooms. However, Chinese lessons used these models for the sole purpose of modeling the underlying quantitative relationships, whereas US lessons mainly used them to aid in computation. In addition, while US teachers rarely involved students in discussion of linear quantity models, Chinese teachers spent significant time engaging students in co-constructing, comparing, and explaining these models.
    • Abstract:
      As Provided
    • Publication Date:
      2019
    • Accession Number:
      EJ1210794