People's judgments and decisions often deviate from classical notions of rationality, incurring costs to both themselves and to society. Previous research has proposed that the cost of these biases can be reduced by redesigning decision problems based on theories of human decision making. These modifications, or nudges, can have dramatic results and have been successfully applied to a variety of domains. However, the formal underpinning of nudge theory is limited, and it is not always clear what the effect of a nudge will be before it is implemented. As a result, designing nudges can be time consuming and error-prone. We propose using resource-rational analysis as a formal framework for modeling and understanding nudges. In this experiment, we will test the predictions of this model on default nudges. In these nudges, decision makers are given the opportunity to skip a problem by selecting a recommended option that tends to be good for most people.