In the context of cognitive competencies, we are defined by our memories. As such, experiential data in various forms of Electronic Competency Records (ECRs), including the Learning Record Store (LRS), can be used as the basis for an Intelligent Tutoring System (ITS), scheduling medical recertification preparation and other forms of educational intervention. However, the experiential data infrastructure provided by an ECR is necessary but insufficient for realizing the full potential of competency tracking and prediction technology. To this end, we are exploring competency degradation models based on time and interference, using retrospective data from our ECR-based work in ITS.