项目自动生成的评价:以弱理论方法为例

IF 2.7 4区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Educational Measurement-Issues and Practice Pub Date : 2022-10-06 DOI:10.1111/emip.12529
Yanyan Fu, Edison M. Choe, Hwanggyu Lim, Jaehwa Choi
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引用次数: 0

摘要

本案例研究应用弱自动项目生成理论(AIG)为大规模评估生成同构项目实例(即唯一但心理测量等效的项目)。从每个项目模板(即模型)中选择三个具有代表性的实例进行试点测试。此外,在现有差异项目功能统计的基础上,应用一个新的分析框架——差异儿童项目功能分析(DCIF)来评估每个模板中项目实例的心理等效性。结果表明,在23个模板中,9个成功地生成了同构实例,5个需要进行小的修改以使它们同构,其余的模板需要进行大的修改。从AIG模板开发过程中获得的结果和见解可以帮助项目编写者和心理测量学家有效地开发和管理生成同构实例的模板。
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An Evaluation of Automatic Item Generation: A Case Study of Weak Theory Approach

This case study applied the weak theory of Automatic Item Generation (AIG) to generate isomorphic item instances (i.e., unique but psychometrically equivalent items) for a large-scale assessment. Three representative instances were selected from each item template (i.e., model) and pilot-tested. In addition, a new analytical framework, differential child item functioning (DCIF) analysis, based on the existing differential item functioning statistics, was applied to evaluate the psychometric equivalency of item instances within each template. The results showed that, out of 23 templates, nine successfully generated isomorphic instances, five required minor revisions to make them isomorphic, and the remaining templates required major modifications. The results and insights obtained from the AIG template development procedure may help item writers and psychometricians effectively develop and manage the templates that generate isomorphic instances.

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来源期刊
CiteScore
3.90
自引率
15.00%
发文量
47
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