Objectives Learning retention after the deliberate practice of radiograph interpretation may be challenging for image types which are common enough to be clinically relevant but not so common that proficiency can be sustained through clinical practice. This is especially relevant for radiographs such as paediatric elbow films (EXR) that carry high risks for the patient if pathology is missed. Building on our prior research in this area, this study will develop an innovative computer learning application for paediatric EXR interpretation. After an initial learning period, this study will quantitatively determine the rate of skill decay and the optimal timing for refresher-education.