A LEARNING MODEL FOR FORCED‐CHOICE DETECTION EXPERIMENTS 1
R. C. Atkinson, R. A. Kanchla · British Journal of Mathematical and Statistical Psychology · 1965
Several signal detection experiments employing a forced‐choice procedure are analysed in terms of a model that incorporates two distinct processes: a sensory process and a decision process. The sensory process specifies the relation between external signal events and hypothesized sensory states of the subject. The decision process specifies the relation between the sensory states and the observable responses of the subject. The sensory process is assumed to be fixed throughout an experiment, whereas the decision process is viewed as varying from trial to trial as a function of the particular sequence of preceding events. The changes in the decision process are assumed to be governed by a simple stochastic learning model. There are several ways of formulating the learning model and the experiments reported here were designed to select among these alternative approaches. The empirical results favour a linear‐operator process with trial‐to‐trial changes in response probabilities that are a function not only of the signal and information events, but also of the particular sequence of sensory states activated.