Problem solving and the search for crucial evidence

Summary Four experiments are reported that examine performance on a complex reasoning task. Subjects have to determine which factory has polluted a river by ordering a series of tests for the presence or absence of various pollutants. Previous research has shown that people typically employ a non-optimal exhaustive search stragegy on this task. Experiments 1 and 2 attempt to identify some of the boundary conditions of this strategy. It is found that the order in which pollutants appear on the matrix list does not seem to be a critical factor, whereas the overall size of the factory-pollutant matrix is. Experiments 3 and 4 attempt to deter people directly from adopting the exhaustive strategy. The results show that even when people are deterred from using the exhaustive method, this will not necessarily result in their adopting a more efficient strategy.     

PROMOTING SAFETY BELT USE WITH TRAFFIC SIGNS AND PROMPTERS

Two studies were conducted examining the stimulus-control effects of conventional traffic signs as prompts for motor vehicle driver safety belt use. Following pilot research which suggested that a traffic sign reading “Fasten Safety Belt” posted at a parking lot exit was effective in producing small increases in safety belt use, Study I demonstrated the superiority of having human prompters display such signs compared to simply posting the signs. Study II replicated the findings of Study I and found that posted signs became more effective in prompting safety belt use if simple posting was preceded by a period involving human prompters who displayed the signs. The results bear upon the development of more effective use of traffic signs in promoting safety belt use and in viewing such use as an instance of rule-governed behavior.     

The three-factor structure of the Eysenck personality inventory revealed by a two-step confirmatory procedure

Evidence for the existence of the assumed three-subscale structure of the Eysenck Personality Inventory has been persistent but tenuous. It was suggested that a substantial reason for this may be the discrepancy between the numbers of items in the Lie (L) scale (9 items) and those in the other two scales [Neuroticism (N) and Extraversion (E)] which have 24 items in each. A two-step confirmatory procedure to circumvent this problem was proposed, involving a two-factor analysis of the Neuroticism and Extraversion items, followed by a three-factor analysis of equal numbers of N, E and L scale items. An analysis of the responses of 386 undergraduates demonstrating the proposed procedure revealed in the first step, quite unequivocally, the presence of Neuroticism and Extraversion factors, and in the second step, a third factor clearly congruent with the L scale.     

Pretrial EEG coherence as a predictor of semantic priming effects

Twenty subjects were presented 240 randomized trials of a lexical decision task (LDT) while connected to a 16-electrode EEG montage. EEG data were acquired for 2 sec prior to the onset of each LDT trial. Alpha (9-13 Hz) coherence, alpha power, and 3- to 30-Hz power from five different combinations of EEG electrodes were used to predict semantic effects in the LDT trials. High pretrial coherence in the Right Hemisphere and Left Posterior-Parietal regions was associated with greater semantic facilitation (faster reaction times) in related-prime trials and greater semantic inhibition (slower reaction times) in unrelated-prime trials, relative to neutral-prime trials. No power variables were associated with semantic effects. Results support an information flow model of the functional significance of EEG coherence to cognitive processing.     

Implicit learning: Below the subjective threshold

In this review, we consider three possible criteria by which knowledge might be regarded as implicit or inaccessible: It might be implicit only in the sense that it is difficult to articulate freely, or it might be implicit according to either an objective threshold or a subjective threshold. We evaluate evidence for these criteria in relation to artificial grammar learning, the control of complex systems, and sequence learning, respectively. We argue that the convincing evidence is not yet in, but construing the implicit nature of implicit learning in terms of a subjective threshold is most likely to prove fruitful for future research. Furthermore, the subjective threshold criterion may demarcate qualitatively different types of knowledge. We argue that (1) implicit, rather than explicit, knowledge is often relatively inflexible in transfer to different domains, (2) implicit, rather than explicit, learning occurs when attention is focused on specific items and not underlying rules, and (3) implicit learning and the resulting knowledge are often relatively robust.