Learning analytics provide designers of educational materials with the ability to ask and answer questions about the effectiveness of those materials in supporting student learning. However, copyright typically prevents designers from engaging in continuous improvement activities.  Open educational resources provide designers of educational materials with copyright permission to revise and remix educational materials. However, they provide no insights into where designers might most productively spend their continuous improvement efforts. Combining learning analytics with open educational resources opens the door to data-driven continuous improvement of educational materials. However, no tools exist to support designers in this time-intensive process. RISE is an R package that implements the resource inspection, selection, and evaluation (RISE) technique described in Bodily, Nyland, and Wiley (2017). RISE combines information about course learning outcomes, student use of learning materials aligned with learning outcomes, and student performance on assessments aligned with learning outcomes in order to automatically places where learning materials are not effectively supporting student learning. Automating the process of identifying areas for improvement allows designers to spend less of their time determining which learning materials need to be improved and more time actually making improvements to learning materials.