Problem solving in semantically rich domains: An example from engineering thermodynamics

Recent research on human problem solving has largely focused on laboratory tasks that do not demand from the subject much prior, task-related information. This study seeks to extend the theory of human problem solving to semantically richer domains that are characteristic of professional problem solving. We discuss the behavior of a single subject solving problems in chemical engineering thermodynamics. We use as a protocol-encoding device a computer program called SAPA which also doubles as a theory of the subject's problem-solving behavior. The subject made extensive use of means-ends analysis, similar to that observed in semantically less rich domains, supplemented by recognition mechanisms for accessing information in semantic memory.     

Gender Differences in Moral Influences on Adolescents’ Eyewitness Identification

Abstract

In this study, 232 (89 11- to 12-year-olds, 71 13- to 14-year-olds; 72 15- to 16-year-olds) students recruited from grades 6th–11th in an urban public high school participated in a study of eyewitness identification. The focus of this study was on the effects of age, gender and moral orientation on decisional bias and, as a secondary outcome, on accuracy (using signal detection analysis).The primary purpose of this and previous studies in this series is to uncover implicit moral decision-making in decisional bias. In this study the perpetrator, the bystanders and the foil were all females. Prior to completing the eyewitness identification task, participants were given instructions that emphasized either (a) fairness and crime prevention, or (b) neither. These instructions had no discernible effect on accuracy but, as in past studies, younger participants (below the age of 13) had lower decisional criteria, resulting in a higher rate of false alarms/positives. Further, those who judged the transgression as worse had a lower decisional criterion, indicating more false alarms. Females were more accurate than the males in identifying the female perpetrator and scored significantly higher on how bad they would feel if they were the victim than did the males.     

Situated Action: A Symbolic Interpretation

The congeries of theoretical views collectively referred to as “situated action” (SA) claim that humans and their interactions with the world cannot be understood using symbol-system models and methodology, but only by observing them within real-world contexts or building nonsymbolic models of them. SA claims also that rapid, real-time interaction with a dynamically changing environment is not amenable to symbolic interpretation of the sort espoused by the cognitive science of recent decades. Planning and representation, central to symbolic theories, are claimed to be irrelevant in everyday human activity. We will contest these claims, as well as their proponents' characterizations of the symbol-system viewpoint. We will show that a number of existing symbolic systems perform well in temporally demanding tasks embedded in complex environments, whereas the systems usually regarded as exemplifying SA are thoroughly symbolic (and representational), and, to the extent that they are limited in these respects, have doubtful prospects for extension to complex tasks. As our title suggests, we propose that the goals set forth by the proponents of SA can be attained only within the framework of symbolic systems. The main body of empirical evidence supporting our view resides in the numerous symbol systems constructed in the past 35 years that have successfully simulated broad areas of human cognition.     

Five Seconds or Sixty? Presentation Time in Expert Memory

For many years, the game of chess has provided an invaluable task environment for research on cognition, in particular on the differences between novices and experts and the learning that removes these differences, and upon the structure of human memory and its paramaters. The template theory presented by Gobet and Simon based on the EPAM theory offers precise predictions on cognitive processes during the presentation and recall of chess positions. This article describes the behavior of CHREST, a computer implementation of the template theory, in a memory task when the presentation time is varied from one second to sixty, on the recall of game and random positions, and compares the model to human data. Strong players are better than weak players in both types of positions, especially with long presentation times, but even after brief presentations. CHREST predicts the data, both qualitatively and quantitatively. Strong players' superiority with random positions is explained by the large number of chunks they hold in LTM. Their excellent recall with short presentation times is explained by templates, a special class of chunks. CHREST is compared to other theories of chess skill, which either cannot account for the superiority of Masters in random positions or predict too strong a performance of Masters in such positions.     

The effects of total sleep deprivation on the generation of random sequences of key-presses, numbers and nouns

According to a recent hypothesis, executive functions should be particularly vulnerable to the effects of total sleep deprivation. Random generation is a task that taps executive functions. In three experiments we examined the effects of total sleep deprivation on random generation of keypresses, numbers, and nouns, in particular on the suppression of prepotent responses and the selection of next responses by way of applying a local-representativeness heuristic. With random key-presses suppression of prepotent responses did not suffer from lack of sleep, but it became poorer at a sufficiently high pacing rate. In contrast, suppression of prepotent responses suffered when numbers and nouns were generated. According to these findings different types of random generation tasks involve different types of inhibitory process. With only four response alternatives, but not with larger response sets, application of the local-representativeness heuristic was impaired after a night without sleep. In terms of a simple formal model, serial-order representations of the preceding responses are used in selecting the next response only for the small response set, and not for larger response sets. Thus, serial-order representations are likely to suffer from loss of sleep. These findings strongly suggest that random generation involves multiple processes and that total sleep deprivation does not impair all sorts of executive functions, but only some.