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.

Citation Key: fu2022 <标题>: 自动题目生成评估：弱理论方法的案例研究