Ayoung Choi  Jongwook Jeong

10.5626/JOK.2026.53.3.248

Mobile Application layout feature tappability graphical user interface

In mobile applications, a disconnect between how users perceive tappability and the designer's intent can lead to users tapping unintended elements or encountering no response (e.g., dead clicks), which negatively impacts the user experience. Previous research has primarily focused on visual features to predict tappability, but these methods can only be applied once the design is finalized. To address this limitation, this study introduces an AI-based approach that predicts tappability using only the layout features of UI elements. We defined layout features-such as element position, size, and spacing between neighboring elements-that can be directly extracted from layout files, and utilized them in a Support Vector Machine (SVM) model. The proposed model achieved an F1 score of 0.772, indicating strong performance. These findings suggest that tappability prediction can be effectively carried out using only layout information in the early design stages, offering a practical solution for proactively detecting usability issues throughout the development process.