At the same time, many care management programs and diabetes education centers struggle with staffing shortages, limited funding, and competitive time demands. As a result, 50 to 80% of individuals with diabetes experience significant knowledge and skill deficits. Health Information Technology (HIT) can make successful interventions available to more diverse populations. At present, however, many HIT interventions target improved patient-clinician communication and logging and monitoring, rather than focusing more specifically on fostering problem-solving skills. Moreover, few HIT interventions have been rigorously evaluated in controlled trials. The main contribution of this research is a theoretically-grounded HIT intervention, Mobile Diabetes Detective (MoDD), that incorporates best practices and current guidelines for supporting and fostering individuals' problem-solving skills in context of diabetes self-management. In our prior work we developed and evaluated a mobile application for reflection and discovery in diabetes management, MAHI (Mobile Access to Health Information). MAHI helped individuals with diabetes capture diabetes-related experiences and reflect on them under a supervision of a diabetes educator. The proposed intervention, MoDD will further extend this prior work, specifically focusing on guided problem-solving through experimentation. The intervention will utilize an open source platform for disease self-management developed by the research team.