Learning to Make Selection and Detection Decisions: The Roles of Base Rate and Feedback


Stewart, Thomas, Center for Policy Research, University at Albany, State University of New York, NY 12222, USA.

E-mail: t.stewart@albany.edu


The effects of type of feedback and base rate on threshold learning in a multiple-cue decision task were examined. In most such decision experiments, participants receive feedback after every trial (full feedback), and a single base rate (usually 0.5) is used. Our experiment explored conditional feedback (feedback only after positive decisions) representing common selection and detection tasks (such as hiring), where the decision maker receives no feedback unless the decision is positive (e.g., hire the applicant). We used three base rates (0.2, 0.5, and 0.8). As expected, performance was best in full feedback, but after 300 learning trials, the difference was small. Conditional feedback generally resulted in fewer positive decisions than full feedback, but this difference was not found in the low (0.2) base rate condition. There were interactions between base rates and types of feedback. Results provide partial support for the constructivist encoding hypothesis of Elwin and colleagues. Simulation results suggest that our results may reflect overconfidence when feedback is not given. With respect to rate of learning, when the base rate was 0.2, conditional feedback participants reached approximately the same selection rate but did so more slowly than the full feedback participants. Partial feedback participants learned slower and appeared to be still learning after 500 trials. When the base rate was 0.5 or 0.8, partial feedback was nearly as good as full feedback, but conditional feedback resulted in a systematically lower rate of positive decisions. Copyright © 2011 John Wiley & Sons, Ltd.