This presents a comprehensive review of the empirical literature bearing on the effects of cognitive feedback (CFB) on multiple measures of performance. CEB refers to the process of presenting the person information about the relations in the environment (task information [TI]), relations perceived by the person (cognitive information [CIj), and relations between the environment and the person's perceptions of the environment (functional validity information [FVI]). Overall, CFB does improve performance on judgment tasks. Specifically, the research indicates that TI rather than CI is the aspect of CFB that influences performance. Factors influencing the effects of CFB on performance are discussed, and both current and potential applications of CFB are explored.A major theme emerging from extensive work in cognitive psychology is that people are limited in their ability to process information in uncertain environments (Nisbett & Ross, 1980), notably so with respect to human judgment and decision making (Kahneman, Slovic, & Tversky, 1982). Research has shown that people have difficulty inferring environmental relationships from unaided experience (Brehmer, 1980) and often lack sufficient insight into their judgment strategies to permit them to communicate those strategies (Balke, Hammond, & Meyer, 1973). More effective judgment and decision making would enhance the lives of individuals and the performance of organizations, and researchers have devoted considerable attention to investigating means of improving these cognitive activities

Numerous authors (e.g., Popper, 1959) argue that scientists should try to falsify rather than confirm theories. However, recent empirical work (Wason and Johnson-Laird, 1972) suggests the existence of a confirmation bias, at least on abstract problems. Using a more realistic, computer controlled environment modeled after a real research setting, subjects in this study first formulated hypotheses about the laws governing events occurring in the environment. They then chose between pairs of environments in which they could: (I) make observations which would probably confirm these hypotheses, or (2) test alternative hypotheses. Strong evidence for a confirmation bias involving failure to choose environments allowing tests of alternative hypotheses was found. However, when subjects did obtain explicit falsifying information, they used this information to reject incorrect hypotheses.

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People routinely focus on one hypothesis and avoid consideration of alternative hypotheses on problems requiring decisions between possible states of the world–-for example, on the “pseudodiagnosticity” task (Doherty, Mynatt, Tweney, & Schiavo, 1979). In order to account for behaviour on such “inference” problems, it is proposed that people can hold in working memory, and operate upon, but one alternative at a time, and that they have a bias to test the hypothesis they think true. In addition to being an ex post facto explanation of data selection in inference tasks, this conceptualization predicts that there are situations in which people will consider alternatives. These are: 1. “action” problems, where the alternatives are possible courses of action; 2. “inference” problems, in which evidence favours an alternative hypothesis. Experiment 1 tested the first prediction. Subjects were given action or inference problems, each with two alternatives and two items of data relevant to each alternative. They received probabilistic information about the relation between one datum and one alternative and picked one value from among the other three possible pairs of such relations. Two findings emerged; (1) a strong tendency to select information about only one alternative with inferences; and (2) a strong tendency, compared to inferences, to select information about both alternatives with actions. Experiment 2 tested the second prediction. It was predicted that data suggesting that one alternative was incorrect would lead many subjects to consider, and select information about, the other alternative. For actions, it was predicted that this manipulation would have no effect. Again the data were as predicted.

It has long been known that subjects in certain inference tasks will seek evidence which can confirm their present hypotheses, even in situations where disconfirmatory evidence could be more informative. We sought to alter this tendency in a series of experiments which employed a rule discovery task, the 2-4-6 problem first described by Wason. The first experiment instructionally modified subjects confirmatory tendencies. While a disconfirmatory strategy was easily induced, it did not lead to greater efficiency in discovering the rule. The second experiment introduced subjects to the possibility of disconfirmation only after they had developed a strongly held hypothesis through the use of confirmatory evidence. This manipulation also failed to alter the efficiency of rule discovery. In the third experiment, subjects were taught to use multiple hypotheses at each step, in the manner of Platt's “Strong Inference”. This operation actually worsened performance. Finally, in the fourth experiment, the structure of the problem was altered slightly by asking subjects to seek two interrelated rules. A dramatic increase in performance resulted, perhaps because information which in previous tasks was seen as merely erroneous could now be related to an alternative rule. The four studies have broad implications for the psychological study of inference processes in general, and for the study of scientific inference in particular.

Advanced undergraduate science majors attempted for approximately 10h each to discover the laws governing a dynamic system. The system included 27 fixed objects, some of which influenced the direction of a moving particle. At a given time, any one screen of a nine-screen matrix could be observed on a plasma display screen. Confirmatory strategies were the rule, even though half the subjects had been carefully instructed in strong inference. Falsification was counterproductive for some subjects. It seems that a firm base of inductive generalizations, supported by confirmatory research, is a prerequisite to useful implementation of a falsification strategy.

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