工作流程
计算机科学
开发(拓扑)
软件工程
数据挖掘
人工智能
数据库
数学
数学分析
摘要
Abstract The template‐based automated item‐generation (TAIG) approach that involves template creation, item generation, item selection, field‐testing, and evaluation has more steps than the traditional item development method. Consequentially, there is more margin for error in this process, and any template errors can be cascaded to the generated items. Therefore, it is essential to eliminate the source of errors and ensure the quality of the template so items can be problem‐free. The article introduces a process to reduce template errors at the early stage of template development, minimize the impact of template errors on generated items, and increase the survival rates of generated items. The article also discusses a statistical method to establish confidence in the quality of the template by systematically examining the quality of the generated items. The proposed method can reduce the review process for some items generated from a template.
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