Goal‐directed cognition is often discussed in terms of specialized memory structures like the “goal stack.” The goal‐activation model presented here analyzes goal‐directed cognition in terms of the general memory constructs of activation and associative priming. The model embodies three predictive constraints: (1) the interference level, which arises from residual memory for old goals; (1) the strengthening constraint, which makes predictions about time to encode a new goal; and (3) the priming constraint, which makes predictions about the role of cues in (...) retrieving pending goals. These constraints are formulated algebraically and tested through simulation of latency and error data from the Tower of Hanoi, a means‐ends puzzle that depends heavily on suspension and resumption of goals. Implications of the model for understanding intention superiority, postcompletion error, and effects of task interruption are discussed. (shrink)

A postcompletion error is a type of procedural error that occurs after the main goal of a task has been accomplished. There is a strong theoretical foundation accounting for postcompletion errors (Altmann & Trafton, 2002; Byrne & Bovair, 1997). This theoretical foundation has been leveraged to develop a logistic regression model of postcompletion errors based on reaction time and eye movement measures (Ratwani, McCurry, & Trafton, 2008). This study further develops and extends this predictive model by (a) validating the model (...) and the general set of predictors on a new task to test the robustness of the model, and (b) determining which specific theoretical components are most important to postcompletion error prediction. (shrink)

Working memory resources are needed for processing and maintenance of information during cognitive tasks. Many models have been developed to capture the effects of limited working memory resources on performance. However, most of these models do not account for the finding that different individuals show different sensitivities to working memory demands, and none of the models predicts individual subjects' patterns of performance. We propose a computational model that accounts for differences in working memory capacity in terms of a quantity called (...) source activation, which is used to maintain goal‐relevant information in an available state. We apply this model to capture the working memory effects of individual subjects at a fine level of detail across two experiments. This, we argue, strengthens the interpretation of source activation as working memory capacity. (shrink)

Negotiation between two individuals is a common task that typically involves two goals: maximize individual outcomes and obtain an agreement. However, research on the simplest negotiation tasks demonstrates that although naive subjects can be induced to improve their performance, they are often no more likely to achieve fully optimal solutions. The present study tested the prediction that a decrease in a particular type of argumentative behavior, substantiation, would result in an increase in optimal agreements. As substantiation behaviors depend primarily on (...) supplied content of the negotiation task, it was also predicted that substantiation behavior would be reduced by curtailing the content. A 2 × 2 experimental design was employed, where both negotiation tactics (list of tactics present versus absent) and negotiation task content (high versus low) were varied to determine the processes leading beyond solution improvement to solution optimality. Sixty‐one dyads engaged in a two‐party, four‐issue negotiation task. All negotiations were videotaped and analyzed. Although the list of negotiation tactics resulted in improved performance, only the content manipulation resulted in a significant increase in dyads achieving optimal solutions. Analyses of the coded protocols indicated that the key difference in achieving optimality was a reduction in persistent substantiation‐related operators (substantiation, along with single‐issue preferences and procedures) and an increase in a complex macro‐operator, multi‐issue offers that reduced the problem space, facilitating the search for optimality. (shrink)

Understanding the nature of errors in a simple, rule‐based task—programming a VCR—required analyzing the interactions among human cognition, the artifact, and the task. This analysis was guided by least‐effort principles and yielded a control structure that combined a rule hierarchy task‐to‐device with display‐based difference‐reduction. A model based on this analysis was used to trace action protocols collected from participants as they programmed a simulated VCR. Trials that ended without success (the show was not correctly programmed) were interrogated to yield insights (...) regarding problems in acquiring the control structure. For successful trials (the show was correctly programmed), steps that the model would make were categorized as matches to the model; steps that the model would not make were violations of the model. The model was able to trace the vast majority of correct keystrokes and yielded a business‐as‐usual account of the detection and correction of errors. Violations of the model fell into one of two fundamental categories. The model provided insights into certain subcategories of errors; whereas, regularities within other subcategories of error suggested limitations to the model. Although errors were rare when compared to the total number of correct actions, they were important. Errors were made on 4% of the keypresses that, if not detected, would have prevented two‐thirds of the shows from being successfully recorded. A misprogrammed show is a minor annoyance to the user. However, devices with the approximate complexity of a VCR are ubiquitous and have found their way into emergency rooms, airplane cockpits, power plants, and so on. Errors of ignorance may be reduced by training; however, errors in the routine performance of skilled users can only be reduced by design. (shrink)