The Effect for Category Learning on Recognition Memory: A Signal Detection Theory Analysis

AbstractPrevious studies have shown that category learning affects subsequent recognition memory. However, questions remain as to how category learning affects discriminability during recognition. In this three-stage study, we employed sets of simulated flowers with category- and non-category-inclusion features appearing with equal probabilities. In the learning stage, participants were asked to categorize flowers by identifying the category-inclusion feature. Next, in the studying stage, participants memorized a new set of flowers, half of which belonged to the learned category. Finally, in the testing stage, participants received a recognition test with old and new flowers, some from the learned, some from the not learned, and some from both categories. We applied hierarchical Bayesian signal detection theory models to recognition performance and found that prior category learning affected both discriminability as well as criterion bias. That is, people that learned the category well, exhibited improved discriminability and a shifted bias toward flowers from the learned relative to the not learned category.


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