Cognitive science principles should have implications for the design of effective learning environments. The self-explanation principle was chosen for the current project because it has developed significantly over the past few years. Early formulations suggested that self-explanation facilitated inference generation to supply missing information about a concept or target skill, whereas later work suggested that self-explanation facilitated mental-model revision (Chi, 2000). To better understand the complex interaction between prior knowledge, cognitive processing, and changes to a learners representation, three different types of self-explanation prompts were designed and tested in the domain of physics problem solving. The results suggest that prompts designed to focus on problem-solving steps led to a sustained level of engagement with the examples and a reduction in the number of hints needed to solve the physics problems.