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Advanced quantitative measurement methodology in physics education research.

机译：物理教育研究中的高级定量测量方法。

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摘要

The ultimate goal of physics education research (PER) is to develop a theoretical framework to understand and improve the learning process. In this journey of discovery, assessment serves as our headlamp and alpenstock. It sometimes detects signals in student mental structures, and sometimes presents the difference between expert understanding and novice understanding. Quantitative assessment is an important area in PER. Developing research-based effective assessment instruments and making meaningful inferences based on these instruments have always been important goals of the PER community. Quantitative studies are often conducted to provide bases for test development and result interpretation.;Statistics are frequently used in quantitative studies. The selection of statistical methods and interpretation of the results obtained by these methods shall be connected to the education background. In this connecting process, the issues of educational models are often raised. Many widely used statistical methods do not make assumptions on the mental structure of subjects, nor do they provide explanations tailored to the educational audience. There are also other methods that consider the mental structure and are tailored to provide strong connections between statistics and education. These methods often involve model assumption and parameter estimation, and are complicated mathematically.;The dissertation provides a practical view of some advanced quantitative assessment methods. The common feature of these methods is that they all make educational/psychological model assumptions beyond the minimum mathematical model. The purpose of the study is to provide a comparison between these advanced methods and the pure mathematical methods. The comparison is based on the performance of the two types of methods under physics education settings. In particular, the comparison uses both physics content assessments and scientific ability assessments.;The dissertation includes three parts. The first part involves the comparison between item response theory (IRT) and classical test theory (CTT). The two theories both provide test item statistics for educational inferences and decisions. The two theories are both applied to Force Concept Inventory data obtained from students enrolled in The Ohio State University. Effort was made to examine the similarity and difference between the two theories, and the possible explanation to the difference. The study suggests that item response theory is more sensitive to the context and conceptual features of the test items than classical test theory. The IRT parameters provide a better measure than CTT parameters for the educational audience to investigate item features.;The second part of the dissertation is on the measure of association for binary data. In quantitative assessment, binary data is often encountered because of its simplicity. The current popular measures of association fail under some extremely unbalanced conditions. However, the occurrence of these conditions is not rare in educational data. Two popular association measures, the Pearson's correlation and the tetrachoric correlation are examined. A new method, model based association is introduced, and an educational testing constraint is discussed. The existing popular methods are compared with the model based association measure with and without the constraint. Connections between the value of association and the context and conceptual features of questions are discussed in detail. Results show that all the methods have their advantages and disadvantages. Special attention to the test and data conditions is necessary.;The last part of the dissertation is focused on exploratory factor analysis (EFA). The theoretical advantages of EFA are discussed. Typical misunderstanding and misusage of EFA are explored. The EFA is performed on Lawson's Classroom Test of Scientific Reasoning (LCTSR), a widely used assessment on scientific reasoning skills. The reasoning ability structures for U. S. and Chinese students at different educational levels are given by the analysis. A final discussion on the advanced quantitative assessment methodology and the pure mathematical methodology is presented at the end.
机译：物理教育研究（PER）的最终目标是建立一个理论框架，以理解和改善学习过程。在这一发现旅程中，评估是我们的头灯和登山杖。它有时会检测学生心理结构中的信号，有时会呈现专家理解和新手理解之间的差异。定量评估是PER中的重要领域。开发基于研究的有效评估工具并基于这些工具做出有意义的推断一直是PER社区的重要目标。经常进行定量研究，以便为测试开发和结果解释提供基础。;统计经常用于定量研究中。统计方法的选择和对通过这些方法获得的结果的解释应与教育背景有关。在这种联系过程中，常常提出教育模式的问题。许多广泛使用的统计方法没有对受试者的心理结构做出假设，也没有提供针对教育受众的量身定制的解释。还有其他考虑心理结构的方法，这些方法经过专门设计以在统计和教育之间建立牢固的联系。这些方法通常涉及模型假设和参数估计，并且在数学上较为复杂。;论文为一些先进的定量评估方法提供了实用的见解。这些方法的共同特点是，它们都对教育/心理模型进行了超越最小数学模型的假设。本研究的目的是提供这些高级方法与纯数学方法之间的比较。比较是基于在物理教学环境下两种方法的性能。特别是在比较中既采用了物理含量评估，又采用了科学能力评估。本文分为三个部分。第一部分涉及项目响应理论（IRT）和经典测试理论（CTT）之间的比较。两种理论均提供了用于教育推理和决策的测试项目统计信息。这两种理论都适用于从俄亥俄州立大学就读的学生获得的“部队概念清单”数据。努力检查这两种理论之间的相似性和差异，以及对差异的可能解释。研究表明，项目响应理论比经典的测试理论对测试项目的上下文和概念特征更敏感。 IRT参数提供了比CTT参数更好的度量，用于教育受众调查项目特征。;论文的第二部分是二进制数据的关联度量。在定量评估中，由于其简单性，经常会遇到二进制数据。当前流行的结社措施在某些极端不平衡的条件下会失败。但是，这些情况的发生在教育数据中并不罕见。研究了两种流行的关联度量，即皮尔森相关和四色相关。介绍了一种基于模型的关联的新方法，并讨论了教育测试的约束条件。将现有的流行方法与带有和不带有约束的基于模型的关联度量进行比较。详细讨论了关联的价值与上下文和问题的概念特征之间的联系。结果表明，所有方法都有其优缺点。必须特别注意测试和数据条件。论文的最后一部分集中在探索性因素分析（EFA）上。讨论了全民教育的理论优势。探索了EFA的典型误解和误用。全民教育是在劳森的科学推理课堂测试（LCTSR）上进行的，这是对科学推理技能的广泛使用的评估。通过分析给出了中美两国不同教育水平学生的推理能力结构。最后介绍了高级定量评估方法和纯数学方法。

著录项

  • 作者

    Wang, Jing.;

  • 作者单位

    The Ohio State University.;

  • 授予单位 The Ohio State University.;
  • 学科 Education Tests and Measurements.;Physics General.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 259 p.
  • 总页数 259
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 教育;物理学;
  • 关键词

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