特殊教育中的认知诊断研究

认知诊断主要将认知心理学与现代教育测量方法相结合,通过获得受试个体在测试中的作答反应来推测其不可观察的知识状态,以测量该个体特定的知识结构和加工技能。本文将研究利用建立 Q矩阵对特殊人群的学力结构进行认知诊断的方法,从而实现因材施教,实现个性化教育。     

英语测试中的认知诊断研究

认知诊断测试可以反映受试的知识结构和分项技能掌握情况,为受试提供详细的反馈信息.本文简要介绍了认知诊断的原理和步骤,总结了国内外英语测试领域的认知诊断研究已取得的进展,并指出目前该领域尚存的问题远大于已取得的成就,在未来的研究中需要设计严格意义上的认知诊断测试,探索检验Q矩阵效度的多种方法并开展诊断结果促学的实证研究.     

认知诊断测验Q矩阵估计方法比较

认知诊断以微观认知角度对被试做出准确评估与反馈的优势在心理与教育测量领域展现出巨大发展潜力,但要利用这种优势就必须确保Q矩阵的合理性。研究表明错误界定的Q矩阵会严重影响模型参数估计和被试分类准确性。本文从参数化与否出发介绍6种基于被试作答反应的Q矩阵估计方法的基本思想、实现步骤及应用情况,总结这些方法的特点并展望未来研究方向,为认知诊断研究及应用提供借鉴和基础。     

认知诊断理论述评

心理与教育测量经历了经典测量理论、项目反应理论、概化理论的发展过程,为了更好地应用于心理与教育测验,认知诊断理论作为新一代测量理论的核心,成为国内外学者关注和研究的热点。本文从背景、概述、评价等方面对该理论进行一个简要述评。     

认知诊断理论在数学教育评价中的应用

质性地比较论证了基于认知诊断理论的数学教育评价工具开发的可行性。通过分析实际测试数据,比较几种不同认知诊断模型中的参数估计方法实际应用于分析数学评价测验的可能性。研究发现,认知属性概念可以帮助研究者和实践者分析影响学生解答数学题目背后的认知结构。人工神经网络模型能够充分利用理论设计的认知模型,克服测验题目有限、题型多样、认知属性差异大等不易分析的困难,较好评价学生的数学学业成就,为后续教学提供诊断性信息,达到了诊断性测验的目的。     

教育考试中的认知诊断评估

认知诊断评估是教育和心理测量学界新兴起的一项技术,主要是在传统考试基础上,为学生提供诊断信息,即提供关于学生对知识/技能掌握情况的信息,对教育教学具有重要的实际价值。本文以认知诊断评估为研究对象,着重分析开展认知诊断评估工作的基本流程,以期为我国教育工作开展认知诊断评估提供参考。     

认知诊断测评的研究述评及展望

通过回顾文献的方法,从认知诊断模型的开发及认知诊断的应用研究两个方面,对认知诊断测评的研究现状进行梳理,帮助读者更好地应用认知诊断技术对学生进行准确的测评,并在现有研究的基础上对未来的研究方向提出建议。     

认知诊断与大规模统一考试的改革

论文介绍了什么是测验的认知诊断及其重要性、测验认知诊断的理论基础与常用的认知诊断心理计量模型,并对我国开展测验诊断、推进大规模统一考试改革提出了具体建议。     

基于教育测评数据的个性化认知诊断研究

教育测评是教学中的一个重要环节,对教育测评数据进行深入挖掘可对学生学习状况开展多角度、多层面的教学诊断.以教育测评数据为基础,以教学目标达成情况和知识点掌握情况为研究目标,以布鲁姆教学目标分类学和Q矩阵理论为理论支撑,通过计算面向教学目标和知识点的属性掌握概率,建立个性化认知诊断模型.以西安邮电大学65名学生教育测评数...     

认知诊断技术在学科学业评价中的应用——以初中一年级“有理数及其运算”为例

当前,中小学学业评价中以考试总分为结果报告的主要方式,这虽然可以判断学生在特定团体中所处的位置以及学生总体上的学习情况,但是却不能明确地指出学生的认知优势或劣势,不能有效地提供“学生掌握了或未掌握什么知识、技能”等信息,也不能有效地让教师因材施教、实现针对性教学。基于这一情况,本研究将教育测量中的前沿技术——认知诊断应用于学业成就评价,以初中一年级数学“有理数及其运算”为例,介绍了认知诊断技术在数学学业评价中的应用过程,为教师改进教学、促进学生发展提供有效支持。     

核心素养的认知诊断测评体系建构

核心素养作为人的必备品质和关键能力,其测评成为了教育教学研究的主要议题。认知诊断理论与素养测评具有内在一致性,在分析认知诊断测评核心素养的合理性和可行性的基础上,借助认知诊断测评理论,文章从核心素养的基本属性关系构建、认知诊断测试的编制、认知诊断模型的选择与应用、测评结果解释与诊断报告的制定等方面建构起素养测评的完整体系,并以数感为例对测评体系的应用做了解析。结合当前核心素养测评的现状,文章针对认知诊断的核心素养测评给出了启示,为核心素养的测评提供了新的视角。     

Developing Score Reports for Cognitive Diagnostic Assessments

This paper presents a framework to provide a structured approach for developing score reports for cognitive diagnostic assessments (CDAs). Guidelines for reporting and presenting diagnostic scores are based on a review of current educational test score reporting practices and literature from the area of information design. A sample diagnostic report is presented to illustrate application of the reporting framework in the context of one CDA procedure called the Attribute Hierarchy Method. Integration and application of interdisciplinary techniques from education, information design, and technology are required for effective score reporting. While the AHM is used in this paper, this framework is applicable to any attribute-based diagnostic testing method.     

Reliably Assessing Growth with Longitudinal Diagnostic Classification Models

Recent advances have enabled diagnostic classification models (DCMs) to accommodate longitudinal data. These longitudinal DCMs were developed to study how examinees change, or transition, between different attribute mastery statuses over time. This study examines using longitudinal DCMs as an approach to assessing growth and serves three purposes: (1) to define and evaluate two reliability measures to be used in the application of longitudinal DCMs; (2) through simulation, demonstrate that longitudinal DCM growth estimates have increased reliability compared to longitudinal item response theory models; and (3) through an empirical analysis, illustrate the practical and interpretive benefits of longitudinal DCMs. A discussion describes how longitudinal DCMs can be used as practical and reliable psychometric models when categorical and criterion‐referenced interpretations of growth are desired.     

Interpreting Probabilistic Classifications From Diagnostic Psychometric Models

Although much research has been conducted on the psychometric properties of cognitive diagnostic models, they are only recently being used in operational settings to provide results to examinees and other stakeholders. Using this newer class of models in practice comes with a fresh challenge for diagnostic assessment developers: effectively reporting results and supporting end users to accurately interpret results. Achieving the goal of communicating results in a way that leads users of the assessment to make accurate interpretations requires a prerequisite step that cannot be taken for granted. The assessment developers must first accurately interpret results from a psychometric, or measurement, standpoint. Through this article, we seek to begin a discussion about reasonable interpretations of the results that classification‐based models provide about examinees. Interpretations from published research and ongoing practice show different—and sometimes conflicting—ways to interpret these results. This article seeks to formalize a comparison, critique, and discussion among the interpretations. Before beginning this discussion, we first present background on the results provided by classification‐based models regarding the examinees. We then structure our discussion around key questions an assessment development team needs to answer themselves prior to constructing reports and interpretative guides for end users of the assessment.     

Digital Module 05: Diagnostic Measurement—The G‐DINA Framework https://ncme.elevate.commpartners.com

In this ITEMS module, we introduce the generalized deterministic inputs, noisy “and” gate (G‐DINA) model, which is a general framework for specifying, estimating, and evaluating a wide variety of cognitive diagnosis models. The module contains a nontechnical introduction to diagnostic measurement, an introductory overview of the G‐DINA model, as well as common special cases, and a review of model‐data fit evaluation practices within this framework. We use the flexible GDINA R package, which is available for free within the R environment and provides a user‐friendly graphical interface in addition to the code‐driven layer. The digital module also contains videos of worked examples, solutions to data activity questions, curated resources, a glossary, and quizzes with diagnostic feedback.     

基于认知诊断的英语阅读研究述评

认知诊断是在现代认知心理学和心理测量学、现代统计数学以及计算机科学基础上发展起来的一种新的诊断技术。它能够科学地描述测试中所包含的认知属性,准确地诊断学习者的语言技能结构,促进个性化的语言教学,因而在英语教育领域,尤其是英语阅读测试中得到了广泛应用,并引起了国内外学者的关注。本文从认知诊断研究的发展、理论基础、在英语阅读测试中的应用、现有研究的难点和不足等方面对认知诊断进行了综述,以期促进认知诊断在英语教学中的应用。     

认知诊断理论的新进展

认知诊断理论是基于项目反应理论的新一代测量理论,在教育测量实践中具有广阔的应用前景。诊断理论的研究主要围绕诊断模型的提出、模型诊断性能的评估、模型诊断结果的报告三个方面展开。认知诊断研究在上述三个方面的进展促进了诊断模型理论建设的深入与应用范围的拓展,但是在模型的外在效度、模型的群体诊断结果、模型的选择与比较、多分项目的诊断模型以及不同诊断测验之间的等值方面仍需进一步研究探索。