Does Contrast or Comparison Help More? The Role of Learning Mode and Category Type

Recent work suggests that classification training and observational learning may differ with regard to the benefits of different types of item presentation. In particular, there is evidence that between-category contrast is most helpful for traditional classification learning of feature-based categories, while a supervised observational mode promotes learning of relational categories via within-category comparison. The purpose of this study is to begin to tease apart the role of the learning mode versus the type of category in producing this pattern of results by replicating an earlier study that used classification training and feature-based categories, and adding in observational learning conditions. If under these conditions, contrast is beneficial for both learning modes, it will suggest that the type of category being learned is the key to the previously observed difference. If, on the other hand, that same difference is observed, it will suggest that the cause is the learning mode itself.