Psychometrician The American Board of Anesthesiology, United States
Most medical licensure and certification examinations rely on large pools of high-quality multiple-choice items, and the item writing process to continually develop new items for these exams is demanding and expensive. In order to utilize tools, such as automated item generation, or streamline the item writing process, it may be beneficial to better understand whether there are predictable features of items that make them more or less difficult.
This e-poster will highlight the possibilities and challenges of using the Linear Logistic Test Model (LLTM). The item features explored include information about the item’s structure (i.e., number of options, inclusion of tables or pictures), wording (i.e., number of words, complexity of words), content (i.e., blueprint category, type of task), or context (i.e., application, patient age).
Thank you Excelsoft for sponsoring the Test Development and Administration track.
Learning Objectives:
Upon completion, participant will be able to describe the importance of learning about their examinations’ item features, as well as list potential uses of these features to better control item difficulty.
Upon completion, participant will be able to describe the general purpose of the LLTM model and how it is applied to examination data to learn about item features.
Upon completion, participant will be able to generate their own ideas of applying LLTM to analyze items and improve item writing in their own settings
