Strategic adaptation to performance objectives in a dual-task setting

How do people interleave attention when multitasking? One dominant account is that the completion of a subtask serves as a cue to switch tasks. But what happens if switching solely at subtask boundaries led to poor performance? We report a study in which participants manually dialed a UK‐style telephone number while driving a simulated vehicle. If the driver were to exclusively return his or her attention to driving after completing a subtask (i.e., using the single break in the xxxxx‐xxxxxx representational structure of the number), then we would expect to see a relatively poor driving performance. In contrast, our results show that drivers choose to return attention to steering control before the natural subtask boundary. A computational modeling analysis shows that drivers had to adopt this strategy to meet the required performance objective of maintaining an acceptable lateral position in the road while dialing. Taken together these results support the idea that people can strategically control the allocation of attention in multitask settings to meet specific performance criteria.     

The Importance of Community Context for Young Women’s Occupational Aspirations

The effects of community context on occupational aspirations are examined in a national sample of young women in high school in the USA in 1979 (n = 2,210). Multilevel statistical models indicate that young women living in counties with a lower divorce rate, a lower percentage of women working, and more people employed in the wholesale and retail industrial sector tended to be less likely to aspire to paid work than young women living in areas with a higher divorce rate, a higher percentage of women working, and fewer people employed in the wholesale and retail industrial sector. Community context does not affect the level of young women’s occupational aspirations as predicted by prior scholarship. An earlier version of this paper was presented at the 2006 Southern Sociological Society Annual Meetings. The author thanks John Reynolds, Patricia Yancey Martin, Irene Padavic, Robert Kunovich, Jennifer Keene, Mary Guy, and the editor and reviewers at Sex Roles for their helpful comments on previous drafts of this paper.     

Preliminary evidence of diurnal rhythms in everyday behaviors associated with positive affect

The authors used the Electronically Activated Recorder (EAR) to track within-day variability in everyday behaviors associated with positive and negative affect across two samples. The EAR is a portable audio recorder that periodically samples snippets of ambient sounds from participants’ momentary environments. The recorded sounds are then coded for different behaviors. The study tested whether previous findings regarding diurnal patterns in self-reported mood extend to naturalistically observed behavior. Across both samples, behavior associated with positive affect (i.e., socializing, laughing, and singing) varied according to a sinusoidal 24-h rhythm centered around participants’ average waketime while behavior associated with negative affect (i.e., arguing and sighing) did not. Further, there was preliminary evidence that personality traits can moderate these rhythms (e.g., their amplitude).     

Never quite good enough: The paradox of sticky developmental relationships for elite university graduates

Drawing on the mentoring, education, and social psychology literatures, this longitudinal study examines how the persistence of developmental relationships from an elite graduate school influences subjective career outcomes during early career. Participants (n = 136) were surveyed about their developmental networks—a group of individuals who take an active interest in and action to advance a focal individual’s career—and subjective career outcomes over the 10 years (1996-2006) post graduation. Results show that although receiving mentoring from one’s entire developmental network was positively related to career-related self-efficacy and perceptions of career success, this was not the case for ties retained from graduate school. Continuing to receive mentoring support from developers from graduate school and further, from peers from graduate school, was negatively related to perceptions of career success. These findings offer insight into the dynamics and potentially negative consequences of developmental networks and highlight the significance of social comparison during early career.     

A computational model of early argument structure acquisition

How children go about learning the general regularities that govern language, as well as keeping track of the exceptions to them, remains one of the challenging open questions in the cognitive science of language. Computational modeling is an important methodology in research aimed at addressing this issue. We must determine appropriate learning mechanisms that can grasp generalizations from examples of specific usages, and that exhibit patterns of behavior over the course of learning similar to those in children. Early learning of verb argument structure is an area of language acquisition that provides an interesting testbed for such approaches due to the complexity of verb usages. A range of linguistic factors interact in determining the felicitous use of a verb in various constructions —associations between syntactic forms and properties of meaning that form the basis for a number of linguistic and psycholinguistic theories of language. This article presents a computational model for the representation, acquisition, and use of verbs and constructions. The Bayesian framework is founded on a novel view of constructions as a probabilistic association between syntactic and semantic features. The computational experiments reported here demonstrate the feasibility of learning general constructions, and their exceptions, from individual usages of verbs. The behavior of the model over the timecourse of acquisition mimics, in relevant aspects, the stages of learning exhibited by children. Therefore, this proposal sheds light on the possible mechanisms at work in forming linguistic generalizations and maintaining knowledge of exceptions.     

Modeling the role of emotions in viewing oneself maturely

Adolescents develop a mature view on themselves: they view positive as well as negative self-attributes, but they hold a positive stance toward themselves. The literatures on identity, the self, parent-offspring relationships, and friendships provide hints on how such a view may develop. This article integrates this literature into an emotion-based dynamic systems mathematical model built to explain the development of maturity of such views. An innovative methodological design was used to collect empirical data: four students daily reported their experiences and emotions for a period of 5 months, while they temporarily studied abroad. At the beginning and end of this period, they were interviewed on their views on themselves. These mostly qualitative data were used to provide support to the suggested mathematical model. The usefulness, weaknesses, and strengths of such a methodological design and mathematical modeling are discussed.     

Expectation confirmation: An examination of three competing models

We discuss three theoretical models from met expectations research in the fields of organizational behavior and consumer psychology. Based on the fundamental arguments in the models, we term these models: disconfirmation, ideal point, and experiences only. We present three-dimensional graphical and analytical representations of the models, with satisfaction being a function of expectations and experiences. We tested the models in the context of a new information system implementation in an organization, with expectations, experiences, and system satisfaction measured for both ease of use and usefulness, the focal constructs of the Technology Acceptance Model (TAM). We found that an experiences only model in which expectations had no measurable effect best explained the data for ease of use. The results for usefulness indicated a modified version of the experiences only model in which the positive effect of experiences becomes slightly stronger—i.e., more positive—as expectations increase.     

Modeling and prediction of driver preparations for making a right turn based on vehicle velocity and traffic conditions while approaching an intersection

This paper focuses on modeling and predicting the influence of a vehicle’s velocity and the relative position between a driver’s vehicle and a vehicle to the front or rear on the onset of driver preparations for making a right turn at an intersection. Repeated experiments were carried out on a public road to measure driver preparations, including releasing the accelerator pedal, moving the right foot to cover the brake pedal, and activating the turn signal, as well as to record vehicle velocity and the relative distances to the leading and following vehicles. Structural equation modeling was applied to estimate these relationships quantitatively. Two separate latent variables accounting for the interaction between the driver’s vehicle and leading or following vehicles, and the onset point where driving behavior changes from straight mode to preparation mode before a right turn, were introduced in the specification of the structural equation model. The model estimates and testing indicate that the proposed structural equation model represents well the relationship hypothesized by observational analysis: that the vehicle velocity and the traffic conditions surrounding the driver’s vehicle strongly influence the driver’s deceleration and more weakly influenced turn signal activation. The proposed structural equation model contributes to the prediction of the onset locations of covering the brake pedal and activating the turn signal based on the vehicle velocity and the relative distances to the front and rear vehicles when the accelerator pedal is released. The prediction accuracy is high compared with predictions in which the vehicle velocity and the headway or rear distances are not taken into account or predictions using a single regression model with one independent variable, namely driving speed. Finally, a possible new addition to in-vehicle navigation systems that detects unusual driver behavior by predicting the driver’s preparatory maneuvers is discussed.     

Autonomous construction of ecologically and socially relevant semantics

This article presents a synthetic modeling approach to the problem of grounded construction of concepts. In many computational models of grounded language acquisition and evolution, meanings are created in the process of discrimination between a chosen object and other objects present on the scene of communication. We argue that categories constructed for the purpose of identification rather than discrimination are more suitable for the detached language use (talking about things not present here and now). We describe a semantics based on so-called identification criteria constructed by extracting cross-situational similarities among instances of a category, and present several computational models. In the model of individual category construction, the instances are grouped to categories by common motor programs (affordances), while in the model of social learning, focused on the influence of naming on category formation, entities are considered members of the same category, if they are labeled with the same word by an external teacher. By these two mechanisms, the learner can construct interactionally grounded representation of objects, properties, relations, changes, complex situations and events. We also report and analyze simulation results of an experiment focused on the dynamics of meanings in iterated intergenerational transmission.