Methods for Detecting and Representing the Item-Position Effect and the Exploration of its Cognitive Sources

物品-位置效应的检测和表征方法及其认知来源的探索

基本信息

项目摘要

The major aim of the proposed research is the advancement of psychological assessment by researching the item-position effect that is biasing measurement in the area of ability testing. For achieving this aim the research proposal suggests the construction of a methodology for the reliable detection and identification of the item-position effect in ability data, the optimization of the representation of the item-position effect in considering disturbances due to ceiling and similarity effects, the extension of the available method for data obtained in non-speeded testing to data obtained in speeded testing. Furthermore, the proposed research shall contribute to the further clarification of the sources of the item-position effect. Accordingly it is to be clarified whether the item-position effect is due to learning and whether there is an interaction with the difficulty-guided arrangement of items. A major part of the research work has to be conducted by means of simulated data. Simulated data enable the control over the general characteristics of data and, therefore, are especially well suited for finding out about the detectability of the item-position effect and about the specificities of the arrangement of items. The investigation of the impact of speeded testing on the item-position effect requires empirical data and also the investigation of the sources of the item-position effect. The investigation of the sources concentrates on the learning hypothesis. Therefore, the data collection must include the application of measures of learning besides ability measures. In the end there should be a revised method that enables the control of the item-position effect and eventually its exploitation as another source of valuable information.
本研究的主要目的是通过对能力测验中偏置测量的项目位置效应的研究,推动心理测评的发展。为了实现这一目标的研究建议,建议建设一个可靠的检测和识别的能力数据中的项目位置效应的方法,优化的项目位置效应的表示,考虑干扰由于天花板和相似性的影响,扩展的可用方法获得的数据在非加速测试中获得的数据在加速测试。此外,本文的研究将有助于进一步阐明项目位置效应的来源。因此,它是要澄清的项目位置效应是否是由于学习和是否有一个相互作用的项目的困难导向的安排。研究工作的主要部分必须通过模拟数据进行。模拟数据能够控制数据的一般特性,因此,特别适合于发现项目位置效应的可检测性和项目排列的特殊性。研究快速测试对项目位置效应的影响需要实证数据,也需要研究项目位置效应的来源。对来源的考察主要集中在学习假设上。因此,数据收集除了能力测量外,还必须包括学习测量的应用。最后,应该有一个修正的方法,使项目位置效应的控制,并最终开发其作为另一个有价值的信息来源。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Professor Dr. Karl Schweizer其他文献

Professor Dr. Karl Schweizer的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Professor Dr. Karl Schweizer', 18)}}的其他基金

Strukturgleichungsmodelle mit Sequenzmustern für die Analyse kognitiver Prozesse im Bereich von Aufmerksamkeit und Gedächtnis
具有序列模式的结构方程模型,用于分析注意力和记忆领域的认知过程
  • 批准号:
    101475775
  • 财政年份:
    2008
  • 资助金额:
    --
  • 项目类别:
    Research Grants
Individuelle Unterschiede in Intelligenz und Lernen aufgrund von Unterschieden in Kapazität und Geschwindigkeit
由于能力和速度的差异而导致智力和学习的个体差异
  • 批准号:
    5217840
  • 财政年份:
    1999
  • 资助金额:
    --
  • 项目类别:
    Research Grants

相似海外基金

Statistical Foundations for Detecting Anomalous Structure in Stream Settings (DASS)
检测流设置中的异常结构的统计基础 (DASS)
  • 批准号:
    EP/Z531327/1
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    Research Grant
Collaborative Research: NSF-BSF: SaTC: CORE: Small: Detecting malware with machine learning models efficiently and reliably
协作研究:NSF-BSF:SaTC:核心:小型:利用机器学习模型高效可靠地检测恶意软件
  • 批准号:
    2338301
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    Continuing Grant
In-situ Imaging and Detecting Electron Transfer for Single Site Reaction
单位点反应的原位成像和电子转移检测
  • 批准号:
    DE240100497
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    Discovery Early Career Researcher Award
CAREER: Detecting warming impacts on carbon accumulation across a climate transect of Michigan peatlands
职业:检测变暖对密歇根泥炭地气候断面碳积累的影响
  • 批准号:
    2338357
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    Continuing Grant
Collaborative Research: NSF-BSF: SaTC: CORE: Small: Detecting malware with machine learning models efficiently and reliably
协作研究:NSF-BSF:SaTC:核心:小型:利用机器学习模型高效可靠地检测恶意软件
  • 批准号:
    2338302
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    Continuing Grant
Development of Efficient Black Hole Spectroscopy and a Desktop Cluster for Detecting Compact Binary Mergers
开发高效黑洞光谱和用于检测紧凑二元合并的桌面集群
  • 批准号:
    2412341
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    Continuing Grant
Detecting and deciphering extinction dynamics under environmental change
检测和破译环境变化下的灭绝动态
  • 批准号:
    DP240102019
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    Discovery Projects
CAREER: Detecting Quantum Signatures in Nonadiabatic Molecular Dynamics
职业:检测非绝热分子动力学中的量子特征
  • 批准号:
    2340180
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    Continuing Grant
Open-world computer vision by detecting and tracking hierarchical objects
通过检测和跟踪分层对象来实现开放世界计算机视觉
  • 批准号:
    DE240100967
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    Discovery Early Career Researcher Award
Strategies for Detecting Fibrin Interference
检测纤维蛋白干扰的策略
  • 批准号:
    23K06851
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了