Developments in Psychometric Population Models for Technology-Based Large-Scale Assessments: An Overview of Challenges and Opportunities
Developments in Psychometric Population Models for Technology-Based Large-Scale Assessments: An Overview of Challenges and Opportunities
复制标题
DOI：
10.3102/1076998619881789
复制
发表时间：
2019-10
影响因子：
2.4
通讯作者：
Matthias von Davier;Lale Khorramdel;Qiwei He;H. Shin;Haiwen Chen
中科院分区：
文献类型：
--
作者：
Matthias von Davier;Lale Khorramdel;Qiwei He;H. Shin;Haiwen Chen
国际大规模评估从纸面评估过渡到计算机评估，促进了新项目类型和更有效的数据收集工具的使用。这允许实现更复杂的测试设计，并收集过程和响应时间（RT）数据。这些新的数据类型可用于提高数据质量和通过潜在回归（群体）模型获得的测试分数的准确性。然而，转向成本效益分析也对可比性和趋势衡量提出了挑战，而可比性和趋势衡量是独立的地方当局协定的主要目标之一。我们提供了一个ILSA中使用的当前方法的概述，以检查和确保不同评估模式和方法之间的数据的可比性，通过利用CBA提供的新数据类型来提高考试成绩的准确性。
International large-scale assessments (ILSAs) transitioned from paper-based assessments to computer-based assessments (CBAs) facilitating the use of new item types and more effective data collection tools. This allows implementation of more complex test designs and to collect process and response time (RT) data. These new data types can be used to improve data quality and the accuracy of test scores obtained through latent regression (population) models. However, the move to a CBA also poses challenges for comparability and trend measurement, one of the major goals in ISLAs. We provide an overview of current methods used in ILSAs to examine and assure the comparability of data across different assessment modes and methods that improve the accuracy of test scores by making use of new data types provided by a CBA.