论证理论
下一代科学标准
拉什模型
心理学
考试(生物学)
科学教育
构造(python库)
数学教育
项目反应理论
结构效度
认识论
计算机科学
人工智能
心理测量学
发展心理学
古生物学
哲学
生物
程序设计语言
作者
Jonathan Osborne,J. Bryan Henderson,Anna MacPherson,Evan Szu,Andrew Wild,Shi‐Ying Yao
摘要
Abstract Given the centrality of argumentation in the Next Generation Science Standards, there is an urgent need for an empirically validated learning progression of this core practice and the development of high‐quality assessment items. Here, we introduce a hypothesized three‐tiered learning progression for scientific argumentation. The learning progression accounts for the intrinsic cognitive load associated with orchestrating arguments of increasingly complex structure. Our proposed learning progression for argumentation in science also makes an important distinction between construction and critique. We present validity evidence for this learning progression based on item response theory, and discuss the development of items used to test this learning progression. By analyzing data from cognitive think‐aloud interviews of students, written responses on pilot test administrations, and large‐scale test administrations using a Rasch analysis, we discuss the refinement both of our items and our learning progression to improve construct validity and scoring reliability. Limitations to this research as well as implications for future work on assessment of scientific argumentation are discussed. © 2016 Wiley Periodicals, Inc. J Res Sci Teach 53: 821–846, 2016
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