This study investigated two feedback types to see if there was a relationship between level of elaborative feedback and participant’s ability to learn a task while also looking at their use of automation. The task was a rule-based problem solving task where participants needed to learn the rules of selecting one pair (Ranger and Hiker) on a gridded map. Ten trials were randomly presented to participants who were asked to make pair selections based on rules (two stated and one unknown to the participant when starting) of correct matches. Results indicated that feedback type significantly influenced accuracy, while trial difficulty influenced use of automation. Results from this study can be applied in education and training of declarative knowledge tasks when rules must be inferred.