Multiple-cue Probability Learning Tasks Research Articles

External validity of individual differences in multiple cue probability learning: The case of pilot training

AbstractIndividuals differ in their ability to deal with unpredictable environments. Could impaired performances on learning an unpredictable cue-criteria relationship in a laboratory task be associated with impaired learning of complex skills in a natural setting? We focused on a multiple-cue probability learning (MCPL) laboratory task and on the natural setting of pilot training. We used data from three selection sessions and from the three corresponding selected pilot student classes of a national airline pilot selection and training system. First, applicants took an MCPL task at the selection stage (N = 556; N = 701; N = 412). Then, pilot trainees selected from the applicant pools (N = 44; N = 60; N = 28) followed the training for 2.5 to 3 yrs. Differences in final MCPL performance were associated with pilot training difficulties. Indeed, poor MCPL performers experienced almost twice as many pilot training difficulties as better MCPL performers (44.0% and 25.0%, respectively).

Gender differences in the use of high-variance strategies in tournament competition

We report on a series of experiments in which participants first completed a simple game of chance and then competed in a tournament based on a multiple cue probability learning task. The results show that men made riskier choices in the simple game of chance, but women adopted the high-variance strategy more frequently in the tournament. However, after controlling for differences in forecasting skill, we find no significant differences in the rates at which men and women adopted a high-variance strategy. Although altering the difficulty of the forecasting task produces differences in the rate at which participants selected the high-variance strategy, it did not produce a significant difference in the rate at which men and women selected the strategy. Thus, this paper suggests that although women are more risk-averse than men, women are no less likely to adopt a high-variance strategy in a tournament competition.

Missing information in multiple-cue probability learning

In a multiple-cue probability learning task, participants learned to use six discrete symptoms (i.e., cues) to diagnose which of three possible flu strains a hypothetical patient suffered from. For some patients, information regarding the status of certain symptoms was not available. Various possible ways in which the missing cue information might be processed were distinguished and tested in a series of three experiments (Ns = 80, 109, and 61). The results suggest that the judged probability of the outcome variable (i.e., flu strain) was assessed by "filling in" the missing cue information with a mean value based on previous observations. The predictions of other methods of processing missing cue information are inconsistent with the data.

How well do elderly people cope with uncertainty in a learning task?

The relation between age, task complexity and learning performance in a Multiple Cue Probability Learning task was studied by systematically varying the level of uncertainty present in the task, keeping constant the direction of relationships. Four age groups were constituted: young adults (mean age=21), middle-aged adults (45), elderly people (69) and very elderly people (81). Five uncertainty levels were considered: predictability=0.96, 0.80, 0.64, 0.48, and 0.32. All relationships involved were direct ones. A strong effect of uncertainty on `control', a measure of the subject’s consistency with respect to a linear model, was found. This effect was essentially a linear one. To each decrement in predictability of the task corresponded an equal decrement in participants' level of control. This level of decrement was the same, regardless of the age of the participant. It can be concluded that elderly people cope with uncertainty in probability learning tasks as well as young adults.

Separable and unitary stimuli in nonmetric multiple-cue probability learning

Two experiments were run to study the effects of separable and unitary stimuli dimensions in a probabilistic, decision-making-like environment. Using a nonmetric multiple-cue probability learning task with two relevant dimensions and additional relevant configural information, no differences in utilization were found for these two types of stimuli. However, in an environment that subjects find more difficult, one in which one dimension is relevant along with the pattern of two additional dimensions, an effect was found. Unitary stimuli were found to facilitate utilization of configural information, but no difference was found for utilization of dimensional information.

Note on subjects' hypotheses in multiple-cue probability learning

Subjects' hypotheses in multiple-cue probability learning was studied by trial-by-trial verbal reports in tasks with linear and nonlinear cue-criterion relations. In accordance with earlier findings, the results of the present experiment show that subjects learned linear tasks rapidly, while nonlinear tasks were not learned at all. The subjects' verbal hypotheses show that the subjects were concerned with rules for combining cue values, rather than with cue-criterion functions. This explains why the subjects fail to learn nonlinear multiple-cue tasks. It also shows that, although the subjects seem to learn multiple-cue tasks through a hypothesis testing process of the same kind as in single-cue probability tasks, the hypotheses tested in multiple-cue tasks are different from those tested in single-cue tasks. Finally, the present results suggest that the picture of the subjects' cognitive models of multiple-cue probability learning tasks provided by the customary multiple regression analysis may be fundamentally misleading in that it suggests that the subjects learn the validity of each cue rather than a combination rule.

The influence of cue unreliability on judgment in a multiple cue probability learning task

The effect of cue reliability was tested in a two-cue multiple-cue probability learning (MCPL) task. Subjects were 42 undergraduates. The cue validities were.78 and.37. Unreliability in a cue was defined as variability in multiple observations of that cue on a given trial. That variability was provided by adding random errors to the true value of the cue. One group was given consistent cues (i.e., the more valid cue was the more reliable cue), one group was given inconsistent cues, and the control group was given true scores. Cue reliability did not affect subjects' consistency or achievement, but did interact with the presence of outcome feedback. The subjective weights showed that subjects thought they weighted the more reliable cue more heavily regardless of the cue validities or their actual cue weightings. There were wide individual differences in performance, illustrating the need for an idiographic-statistical approach in studying decision making.

Delayed exposure to configural information in nonmetric multiple-cue probability learning

The effects of delayed exposure to relevant configural information were studied. Three groups were run for 480 trials in a two-cue nonmetric multiple-cue probability learning task. All groups had one relevant cue dimension. One group had no relevant configural information, while another always had relevant configural information. The third group began without relevant configural information and was switched to relevant configural information after trial 120. The switched group did learn to utilize the configural information, but not nearly as strongly as the group which always had relevant configural information. A follow-up study explored the effects of the length of the delay before exposure to the relevant configural information. Four groups were run under the above conditions but were switched at trial 40, 80, 120, or 200, respectively. The results replicated the effect for the group switched at trial 120 and showed no differences between the four groups, indicating that the effect of delayed exposure is constant and requires little delay.

Does having to justify one's judgments change the nature of the judgment process?

The effects of justification on subjects' application of judgment policies in a multiple-cue probability learning task under conditions of high versus low task predictability and provision versus no provision of feedback were investigated. The results showed that having to justify one's judgments will lead to higher consistency in the judgment policy when task predictability is low and no feedback is provided. The results are interpreted as indicating that justification may lead to an analytical mode of functioning in judgment behavior. Implications for research in cognitive conflict are also discussed.

The influence of formal, substantive, and contextual task properties on the relative effectiveness of different forms of feedback in multiple-cue probability learning tasks

Previous research shows that when participants are given information that allows them to compare task properties with properties of their cognitive system (cognitive feedback) they reach higher levels of achievement in multiple-cue probability learning (MCPL) tasks than when they are shown the correct answer after each trial (outcome feedback). It was hypothesized that this finding was in part due to the use of neutral task content in nearly all previous research, for neutral content fails to provide information about task properties in the outcome feedback condition. A study was conducted to compare the level of achievement reached with cognitive and outcome feedback under three conditions which varied the congruence between task properties implied by task content and actual task properties. The study supported the above hypothesis. When task content provided no task information, the level of achievement with cognitive feedback was higher than that reached with outcome feedback, even with perfect task predictability. When the task information provided by task content was congruent with actual task properties, however, the level of achievement with outcome feedback was as high as that with cognitive feedback. And when the task information provided by task content was incongruent with actual task properties, the level of achievement with cognitive feedback was as low as that with outcome feedback. Two additional experiments suggest that the effectiveness of cognitive feedback depends on contextual task properties, such as the number of blocks of trials and the credibility of the feedback. The results indicate that the relative effectiveness of outcome and cognitive feedback depends on formal, substantive, and contextual task properties.

Content and consistency in probabilistic inference tasks

Four experiments investigated the relation between content and consistency in multiple-cue probability learning tasks. The first two experiments show that giving the task a content seen by the subjects as indicating probabilistic cue-criterion relations, does not change their general approach to the task; subjects behave in the same way in these conditions as in conditions involving no task content. The results of Experiments 3 and 4 replicate earlier results from abstract single-cue probability learning tasks which indicated that giving information about the probabilistic nature of the task and the strategy to use does not lead to better performance. It is concluded that although an inappropriate, deterministic strategy may be the explanation why subjects perform suboptimally in probabilistic inference tasks, changing this strategy to a more appropriate statistical one does not help, presumably because the subjects lack the processing capacity needed to implement this kind of strategy.

Reversal of Order of Information in a Multiple-Cue Probability Learning Task

Summary The present study investigated a modified version of the conventional paradigm employed in research on multiple-cue probability learning. The modified training paradigm, in which the criterion is presented before the cues, was compared with the conventional paradigm, in which the cues are followed by the criterion. A total of 252 male and female introductory psychology students were tested in three experiments. In Experiment I, 72 male and female Ss were required to learn the cue-criterion function form for each of three probabilistic cues. In Experiment II, 108 male and female Ss were required to learn validities of the three probabilistic cues. In Experiment III, 72 male and female Ss were required to learn cue-criterion function forms and cue validities for either three or five cues. Learning occurred with the presentation of criterion information in each experiment; however, there was no significant difference between training paradigms.

Ingredients of intuitive regression

Conflicting evidence, mainly from multiple-cue probability learning tasks, leans toward the proposition that people predict uncertain events better than they can express the process that generates them. Since data on that question from single-cue probability learning tasks are almost completely lacking, the experiment attempts to supply it. It used scaled variables in four task validities with positive and negative sign and high and moderate cue-event correlations. Cue weightings inferred from subjects' predictions were more accurate than weightings which they made explicit. Brehmer's findings were confirmed that rate of learning is affected by factors different from those affecting final level of achievement. Overtracking was found, but not as an inverse function of cue-validity; previous reports of that finding are challenged. Subjects were more effective in arriving at a predictive scheme which would have worked well if consistently followed than they were in adhering to it. The hypothesis was strengthened that people's effectiveness in predicting uncertain events exceeds their ability to express insight into their prediction process.

The influence of shifting cue validity distributions and group discussion feedback on multiple cue probability learning

The effects of group discussion feedback and shifting cue validities on subjects' achievement, consistency, and matching in a multiple cue probability learning task were investigated in a task of constant system predictability. Students utilized distributions of meaningfully labeled cues of equal or unequal validity to predict final exam performance. Subjects' performance was examined in two conditions in which a shift in cue validities occurred and in two conditions in which the same validities were employed throughout the task. Feedback from group discussion was provided for half the subjects. Results indicated that subject performance was best when equally valid cues were utilized, especially after an anticipated shift in cue validities. Group discussion feedback facilitated performance only when a shift occurred. The results were discussed in the context of dynamic prediction environments.

Feedback and task predictability as determinants of performance in multiple cue probability learning tasks

Several studies conducted within the last decade have suggested that outcome feedback is less than optimal feedback in a multiple cue probability learning situation. Some of these studies have neglected one or more of the following: a no feedback control group, analysis of the several different types of feedback, assessment of feedback over time, and the effect of feedback on tasks of different difficulty levels. Two 2(outcome feedback) × 2(cue utilization feedback) × 2(task information) × 3(trial blocks) experiments were conducted. It was found that outcome feedback resulted in significantly less consistency, and task information resulted in significantly better matching. Cue utilization feedback enhanced achievement and matching only in combination with task information and only in high predictability tasks. Further research on feedback should focus on feedback and task difficulty interactions as well as the effects of delay of feedback.

Feedback effects in a metric multiple-cue probability learning task

Three forms of augmented feedback were compared with simple outcome feedback in a computer-run, metric, multiple-cue probability learning task. These were: (a) lens model feedback, (b) provision of the predicted criterion value, and (c) provision of categorical information about the criterion. There was significant improvement in performance across six blocks of 25 trials, but no differences among the feedback treatments. In a second study, two additional groups were run without outcome feedback. These groups received either lens model feedback or predicted criterion feedback. The major result was a sharp increase in consistency, which mediated an increase in achievement, when outcome feedback was not provided.

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.

Cognitive and outcome feedback in multiple-cue probability learning tasks.

Cognitive and outcome feedback in multiple-cue probability learning tasks.

Cognitive and outcome feedback in multiple-cue probability learning tasks.

Cognitive and outcome feedback in multiple-cue probability learning tasks.

The effect of different types of feedback in multiple-cue probability learning

The purpose of this study was to determine the effect of different sorts of feedback upon performance in a multiple-cue probability learning task with binary cues and binary events. In addition to traditional outcome feedback, subjects were given periodic feedback messages throughout the experiment. Different types of feedback included percentage of correct responses, cue-event validity coefficients, cue-response utilization coefficients, and a combination of both of the last two types. Feedback was based upon either all previous trials (long-term feedback) or the last 20 trials (short-term feedback) or both. Two different tasks were used. Nine hundred seventy-two subjects were assigned to 32 groups in a 4 (feedback type) by 2 (short-term feedback) by 2 (long-term feedback) by 2 (task) design, and were individually run for 300 noncontingent trials. In general, the results were that no type of feedback enhanced performance, but all feedback types except percentage correct feedback resulted in a decrement in performance. Long-term and short-term feedback interaction effects were found.