Judgement Frequency, Belief Revision, and Serial processing of Causal Information

Abstract

The main aim of this research was to study the cognitive architecture underlying causal/covariation learning by investigating the frequency of judgement effect. Previous research has shown that decreasing the number of trials between opportunities to make a judgement in a covariation learning task led to a higher score after an a or d type of trial (positive cases) than after b and c trials (negative cases). Experiment 1 replicated this effect using a trial-by-trial procedure and examined the conditions under which it occurs. Experiment 2 demonstrated a similar frequency of judgement effect when the information was presented in the form of contingency tables. Associative or statistical single-mechanism accounts of causal and covariation learning do not provide a satisfactory explanation for these findings. An alternative belief revision model is presented.