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Designing an Evidence-based Assessment of Conceptual Understanding and Misunderstandings in Statistics

机译：设计基于证据的统计概念理解和误解评估

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摘要

This study investigates the extent to which an assessment can diagnose learner misconceptions in the domain of statistics. A Statistics Concept Inventory (StatCI) was created using an evidence-centered design framework (Mislevy, Steinberg, & Almond, 2003). This assessment draws from a comprehensive literature review of student thinking in statistics, in which clusters of items correspond to a major concept, and each distractor maps onto a misconception. Professors and graduate students with expertise in statistics checked the assessment for face validity. Four studies were run to validate aspects of this assessment. First, a student protocol study was conducted to examine how students interpreted the items. Second, a 30-item pilot version was administered to 100 participants on Amazon Mechanical Turk. Preliminary psychometric tests were run on these data to identify items to modify and delete. A beta version was administered to another 100 participants. Finally, an updated was administered to 750 participants. Participant performance data was analyzed for response patterns demonstrating conceptual and errorful thinking. In particular, data was analyzed by items, conceptual structure, distractors, and demographic groups. These results provided evidence that the assessment is measuring the targeted constructs and is able to identify learner misconceptions and errors. The outcomes of this program of research included: (1) a design pattern template that can be broadly applied to create other assessments in statistics; (2) a final assessment instrument that can be used in undergraduate first-year statistics courses; (3) a methodology for applying ECD to concept inventory design.
机译：这项研究调查了评估可以诊断统计领域中的学习者误解的程度。使用以证据为中心的设计框架创建了统计概念清单（StatCI）（Mislevy，Steinberg和Almond，2003年）。该评估来自对学生的统计学思维的全面文献综述，其中项目的集合对应于一个主要概念，并且每个干扰因素都映射到一个误解上。具有统计学专业知识的教授和研究生检查了脸部有效性的评估。进行了四项研究以验证该评估的各个方面。首先，进行了学生协议研究，以检查学生如何解释项目。其次，向Amazon Mechanical Turk的100名参与者管理了30个项目的试用版。对这些数据进行了初步的心理测验，以识别要修改和删除的项目。测试版还对另外100名参与者进行了管理。最终，对750名参与者进行了更新。分析了参与者的表现数据的响应模式，表明了概念和错误的思维。特别是，数据是按项目，概念结构，干扰因素和人口统计数据组进行分析的。这些结果提供了证据，表明评估正在衡量目标结构，并且能够识别学习者的误解和错误。该研究计划的结果包括：（1）设计模式模板，可以广泛地用于创建统计方面的其他评估； （2）可用于本科一年级统计学课程的最终评估工具； （3）将ECD应用于概念清单设计的方法。

著录项

  • 作者

    Jorion, Natalie.;

  • 作者单位

    University of Illinois at Chicago.;

  • 授予单位 University of Illinois at Chicago.;
  • 学科 Educational tests measurements.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 235 p.
  • 总页数 235
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 遥感技术;
  • 关键词

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