Informal learners of computational skills often fi nd it difficult to self-direct their learning pursuits, which may be spread across different mediums and study sessions. Inspired by self-monitoring interventions from domains such as health and productivity, we investigate key requirements for helping informal learners better self-reflect on their learning experiences. We carried out two elicitation studies with paper-based and interactive probes to explore a range of manual, automatic, and semi-automatic design approaches for capturing and presenting a learner's data. We found that although automatically generated visual overviews of learning histories are initially promising for increasing awareness, learners prefer having controls to manipulate overviews through personally relevant filtering options to better reflect on their past, plan for future sessions, and communicate with others for feedback. To validate our findings and expand our understanding of designing self-monitoring tools for use in real settings, we gathered further insights from experts, who shed light on factors to consider in terms of data collection techniques, designing for reflections, and carrying out field studies. Our findings have several implications for designing learner-centered self-monitoring interventions that can be both useful and engaging for informal learners.