We describe an experiment that examines observational learning of either rules or instances. Subjects were asked to learn a dynamic computer control task and were given either a specific goal, to make the computer produce a specific response, or a non-specific goal, to find the pattern underlying the computer’s behavour. Subjects either interacted directly with the computer (the ‘models’) or observed a model’s learning trials (the ‘observers’). Both the goal of the models and the goal of the observers were varied so that specific goal and non-specific goal models were crossed with specific goal and non-specific goal observers. We predicted that the goal of the observer and not the goal of the model would determine whether observers learned rules or instances and that learning through observation would hinder instance learning. These predictions were confirmed. Non-specific goal models learned rules whereas specific goal models learned instances. Non-specific goal observers also learned rules, irrespective of the goal of the model, but specific goal observers failed to learn at all. A subsequent test confirmed that the failure of the specific goal observers to learn was due to the lack of feedback about correct responses. When such feedback was provided, specific goal observers learned instances. However, the presence of feedback was detrimental to rule learning. When non-specific goal observers received feedback, they learned only instances. These results support the view that both goal specificity and the presence or absence of feedback guide learning by directing attention to either instance space or both instance space and rule space.