The Impact of Complete and Selective Feedback in Static and Dynamic Multiple-Cue Judgment Tasks

Abstract

It is widely accepted that feedback is critical to guide the learning process and to make effective decisions. However, ideal feedback is relatively rare in our daily environments. Two multiple-cue judgment experiments examined whether biased and incomplete feedback leads to less accurate learning than comprehensive feedback. Experiment 1 found that participants given selective feedback produce equivalently accurate predictions, learned equally rapidly, and exhibited equivalent task structure knowledge to those given full feedback. Experiment 2 showed that selective feedback led to more accurate outcome predictions and task structure knowledge in a dynamic task environment. These results are problematic for error-based models of learning.


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