ItemSight: Development of a Shiny Application for Simplified Item Analysis of Type A Multiple-Choice Questions

Item analysis is a vital step in educational assessment to check the quality of multiple-choice questions (items). Traditional item analysis methods using spreadsheets or statistical software are often time-consuming, error-prone, and challenging for educators with limited programming expertise. To address these issues, ItemSight, an intuitive software for item analysis, was developed to automate and simplify the psychometric evaluation of test items. The software was developed using the R-Shiny framework. It computes item difficulty, discrimination index, distractor efficiency, internal consistency (if an item is deleted), and point-biserial correlation. To run the software, users need R and RStudio with installed packages and the code we provide. After analysis, the report can be easily exported in comma-separated values (CSV) format for further analysis. All data remains stored locally on the user's computer, ensuring privacy. Currently, the software supports only type A multiple-choice questions (four options with a single best answer). It can be accessed and used through RStudio without any cost. The tool serves as a valuable resource for educators and researchers in medical and allied health sciences, promoting evidence-based improvement of assessment quality.