Computer workstations: Explorations in human and machine cognition

Professional and scientific work will increasingly be conducted at computer workstations. An expert-system adaptive interface is one method for supporting learning and raising productivity of workstation activities. A prototype application for an adaptive interface is described in terms of machine intelligence, needs, design philosophy, and cognitive research. The intelligent interface prototype includes the operator’s psychometric profile, prior performance history, and a current keystroke performance stack within a conventional expert system. Productions in the form of conditionals between the operator’s keystrokes and three types of commands to the underlying software are described and illustrated. Commands entered, syntax errors, excessive repetition of keystrokes, and skill level are used to detect the user’s intentions and accordingly modify the display and command structure of the underlying software. Determining human intentions to produce machine adaptation to individual users is not a trivial task. Efforts to develop a powerful and general adaptive interface pose significant problems, and success cannot be assured without intensive cognitive research.     

Naive theory and transfer of learning: When less is more and more is less

In this research, we examine how young children perform induction in the domain of biology. According to the essentialist view, even young children have a priori knowledge that some predictors of biological properties are central, whereas others are peripheral. According to the flexible-learning view, the roles of predictors are not fixed, and young children flexibly learn the predictive value of each predictor. In the experiment reported, 4- to 5-year-olds and 11- to 12-year-old preadolescents were taught the predictive values of features that were (by the essentialist account) either central or peripheral for predicting the biological properties of animals. Retention of the learned predictors was then tested immediately after learning, 1 h after leaning, and 2.5–3.5 months later. The results indicate that 2.5–3.5 months after learning, young children retained learned predictors well regardless of their putative centrality, whereas preadolescents were likely to retain and recall only central, but not peripheral, predictors.     

Is Change Bad? Personality Change Is Associated with Poorer Psychological Health and Greater Metabolic Syndrome in Midlife

Personality change is emerging as an important predictor of health and well‐being. Extending previous research, we examined whether two types of personality change, directional and absolute, are associated with both subjective and objective indicators of health. Utilizing the longitudinal Midlife in the United States survey (MIDUS) data, we examined whether both types of change over 10 years were associated with psychological well‐being, self‐reported global health, and the presence of metabolic syndrome (MetS) components and diagnosis. Socially undesirable personality change (e.g., becoming less conscientious and more neurotic) and absolute personality change were independently associated with worse perceived health and well‐being at Time 2. Notably, absolute personality change, regardless of the direction, was also associated with having a greater number of MetS components and a greater probability of diagnosis at Time 2. In sum, too much personality change may be bad for one's health: Socially undesirable and absolute personality change were both associated with worse psychological health and worse metabolic profiles over 10 years. These findings suggest that personality change may contribute to psychological and physical health, and provide initial insight into potential intermediate links between personality change and distal outcomes such as mortality.     

A Direct Study of Halo Effect

Five individuals were evaluated on a 7-point scale from strongly dislike (1) to strongly like (7). A week later the same people were rated on 16 relatively distinct traits, such as carefulness, sense of humor, fairness, and sociability. For three of the rated individuals, there were no extreme ratings on the general impression (liking) scale by raters, and the correlations between those scores and mean trait ratings were .26, .32, and .36. For the other two, there were sharp and extreme ratings on the general liking scale, and correlations between those scores and mean trait ratings were .60 and .76. This method provides a more appropriate and more meaningful index of halo effect than other methods because it is based more directly on Thorndike's (1920) original concept.     

Attributions for Memory Performance in Adulthood: Age Differences and Mediation Effects

We examined age differences in attributions to internal (controllable and uncontrollable), external (uncontrollable), and unstable factors for performance on a free recall memory task in 149 young, middle-aged, and older adults. Attributions varied by age and by level of memory performance. Middle-aged and older adults rated internal, uncontrollable factors (ability and genes) as more influential for high performance than for low performance, and they were less likely than young adults to attribute low performance to these factors. Within age groups, only the older adults rated memory ability as more influential than strategy use, even though they were as likely as the other age groups to use a categorization strategy. Attributions to both internal controllable (strategy use) and uncontrollable (ability) factors as well as to health were associated with better memory performance. These attributions partially mediated the relationship between age and memory performance. Thus, attributions may provide some insight into sources of age differences in memory performance.     

Time for change: using implementation intentions to promote physical activity in a randomised pilot trial

Objective: A common barrier to exercise is a perceived lack of time. The current pilot study examined the effects of an implementation intention intervention to enhance exercise self-efficacy, increase confidence to exercise when facing time constraints, and increase physical activity in middle-aged adults (n?=?63, aged 35–69). Design: Participants received a pedometer (Fitbit) to objectively measure activity and were randomly assigned to either a control or intervention condition. After a 1-week baseline, the intervention condition received instructions to plan how, where, and when they would add steps to their daily routine to meet their step goal, using personalised schedules and maps. Both groups were contacted nightly via email. Main Outcome Measures: Physical activity (steps and time spent in moderate-to-vigorous activity), goal achievement, exercise self-efficacy, time-relevant exercise self-efficacy and affect. Results: Compared to the control, the intervention condition significantly increased in steps, time spent in moderate-to-vigorous activity, and time-relevant exercise self-efficacy. Goal achievement was related to greater time-relevant exercise self-efficacy and more positive affect at the daily level. Conclusion: Findings suggest that the personalised planning intervention increased physical activity and confidence in achieving physical activity goals under time constraints. Avenues for future directions, especially for producing more sustained effects, are discussed.