Using psychometric tools as a window into students’ quantitative reasoning in introductory physics

Trevor I. Smith, Philip Eaton, S. Brahmia, Alexis Olsho, A. Boudreaux, C. DePalma, Victor Lasasso, Scott Straguzzi, Christopher Whitener
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引用次数: 4

Abstract

The Physics Inventory of Quantitative Literacy (PIQL), a reasoning inventory under development, aims to assess students' physics quantitative literacy at the introductory level. PIQL's design presents the challenge of isolating types of mathematical reasoning that are independent of each other in physics questions. In its current form, PIQL spans three principle reasoning subdomains previously identified in mathematics and physics education research: ratios and proportions, covariation, and signed (negative) quantities. An important psychometric objective is to test the orthogonality of these three reasoning subdomains. We present results from exploratory factor analysis, confirmatory factor analysis, and module analysis that inform interpretations of the underlying structure of PIQL from a student viewpoint, emphasizing ways in which these results agree and disagree with expert categorization. In addition to informing the development of existing and new PIQL assessment items, these results are also providing exciting insights into students' quantitative reasoning at the introductory level.
在物理导论中,使用心理测量工具作为学生定量推理的窗口
物理定量素养量表(PIQL)是一个正在开发的推理量表,旨在评估学生在入门水平的物理定量素养。PIQL的设计提出了在物理问题中隔离彼此独立的数学推理类型的挑战。在目前的形式中,PIQL跨越了先前在数学和物理教育研究中确定的三个原则推理子领域:比率和比例、协变和有符号(负)量。一个重要的心理测量目标是测试这三个推理子域的正交性。我们提出了探索性因素分析、验证性因素分析和模块分析的结果,这些结果从学生的角度解释了PIQL的底层结构,强调了这些结果与专家分类的一致和不一致的方式。除了为现有和新的PIQL评估项目的开发提供信息外,这些结果还为学生在入门级的定量推理提供了令人兴奋的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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