The effects of cognitive feedback and task complexity in multiple-cue probability learning

Subjects learned three multiple-cue probability learning (MCPL) tasks of varying complexity under conditions of feedforward and cognitive feedback. Statistical information about the task was presented in the feedforward condition; in the cognitive feedback condition, subjects were given statistical information about their own performance in addition to information about the task. Task complexity was manipulated by varying the function forms relating the values of the cues to the values of the criterion: The least complex task contained three positive linear function forms, the intermediate task contained three inverted U-shaped function forms, and there was one negative linear function form, one inverted U-shaped function form, and one U-shaped function form in the most complex task. The hypothesis that cognitive feedback is more effective than feedforward for the more complex task used here was not confirmed: There were no differences between the two groups with regard to r_a (achievement), G (knowledge), or R_s,² (cognitive control). The level of performance on all tasks, including the complex nonlinear tasks, was very high under both conditions, however, an unexpected and important finding.