RESUMEN

Categorical learning is important and often challenging in both specialized domains, such as medical image interpretation, and commonplace ones, such as face recognition. Research has shown that comparing items from different categories can enhance the learning of perceptual classifications, particularly when those categories appear highly similar. Here, we developed and tested novel adaptively triggered comparisons (ATCs), in which errors produced during interactive learning dynamically prompted the presentation of active comparison trials. In a facial identity paradigm, undergraduate participants learned to recognize and name varying views of 22 unknown people. In Experiment 1, single-item classification trials were compared to a condition in which ATC trials were generated whenever a participant repeatedly confused two faces. Comparison trials required discrimination between simultaneously presented exemplars from the confused categories. In Experiment 2, an ATC condition was compared to a non-adaptive comparison condition. Participants learned to accuracy and speed criteria, and completed immediate and delayed posttests. ATCs substantially enhanced learning efficiency in both experiments. These studies, using a novel adaptive procedure guided by each learner's performance, show that adaptively triggered comparisons improve category learning.

Asunto(s)

Reconocimiento Facial , Aprendizaje , Humanos , Femenino , Masculino , Aprendizaje/fisiología , Adulto Joven , Adulto , Cara , Adolescente

RESUMEN

Recent work suggests that learning perceptual classifications can be enhanced by combining single item classifications with adaptive comparisons triggered by each learner's confusions. Here, we asked whether learning might work equally well using all comparison trials. In a face identification paradigm, we tested single item classifications, paired comparisons, and dual instance classifications that resembled comparisons but required two identification responses. In initial results, the comparisons condition showed evidence of greater efficiency (learning gain divided by trials or time invested). We suspected that this effect may have been driven by easier attainment of mastery criteria in the comparisons condition, and a negatively accelerated learning curve. To test this idea, we fit learning curves and found data consistent with the same underlying learning rate in all conditions. These results suggest that paired comparison trials may be as effective in driving learning of multiple perceptual classifications as more demanding single item classifications.