Learning in multimodal training: Visual guidance can be both appealing and disadvantageous in spatial tasks

Multimodal training involving both visual and auditory information was shown to improve text comprehension and reduce cognitive load. However, it is argued that in spatial tasks visual guidance can impair training effectiveness because it encourages shallow performance strategies and little exploration. Moreover, visual aids are attractive to both trainers as well as trainees, who tend to use them despite their potential disadvantages. To examine this potential training trap, two experimental studies were conducted. In Study 1, each trainer instructed trainees on how to perform a 3-D puzzle in two conditions: vocal guidance (17 trainees), where only vocal instructions were possible, and vocal guidance with mouse pointing (17 trainees), where the trainer could also use a mouse to point out positions on the trainee's screen. The results showed that while the use of the mouse pointer reduced trainees' mental load during training, it also drastically lowered performance level on a non-supervised test. In Study 2, a real-world version of puzzle was trained. A comparison of a vocal guidance group (16 trainees) to a group trained with an additional mouse pointing and drawing option (16 trainees) showed, as well, reduced performance levels with the additional visual aids. The results suggest that the abundant use of multimodal training in Augmented Reality (AR) applications should be re-evaluated.     

Application of a computational decision model to examine acute drug effects on human risk taking.

In 3 previous experiments, high doses of alcohol, marijuana, and alprazolam acutely increased risky decision making by adult humans in a 2-choice (risky vs. nonrisky) laboratory task. In this study, a computational modeling analysis known as the expectancy valence model (J. R. Busemeyer & J. C. Stout, 2002) was applied to individual-participant data from these studies, for the highest administered dose of all 3 drugs and corresponding placebo doses, to determine changes in decision-making processes that may be uniquely engendered by each drug. The model includes 3 parameters: responsiveness to rewards and losses (valence or motivation); the rate of updating expectancies about the value of risky alternatives (learning/memory); and the consistency with which trial-by-trial choices match expected outcomes (sensitivity). Parameter estimates revealed 3 key outcomes: Alcohol increased responsiveness to risky rewards and decreased responsiveness to risky losses (motivation) but did not alter expectancy updating (learning/memory); both marijuana and alprazolam produced increases in risk taking that were related to learning/memory but not motivation; and alcohol and marijuana (but not alprazolam) produced more random response patterns that were less consistently related to expected outcomes on the 2 choices. No significant main effects of gender or dose by gender interactions were obtained, but 2 dose by gender interactions approached significance. These outcomes underscore the utility of using a computational modeling approach to deconstruct decision-making processes and thus better understand drug effects on risky decision making in humans. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Decision making and personality in traffic offenders: a study of Israeli drivers

Traffic offences present danger to the offender, and to others. This study examines differences in decision making and personality between traffic offenders and non-offenders. Fifty-one traffic offenders participating in penalty courses were compared to a control group of 36 drivers who were not penalized for traffic offences in the 5 years prior to the study. All participants performed the Iowa Gambling Task (IGT), a popular decision task employed for assessing cognitive impulsivity, and completed the "big five" personality questionnaire. The results showed that traffic offenders made fewer advantageous choices on the IGT; and an analysis with a formal cognitive model, the Expectancy Valance model, suggests that this results from offenders' high weighting of gains compared to losses. An examination of personality factors reveals that traffic offenders were more extraverted. The predictive power of IGT performance was comparable to that of the personality factor. These results demonstrate that the IGT can be useful for studying individual differences in risk taking in a real-world task, and combined with the EV model, identify the sources of these differences.     

A formal cognitive model of the go/no-go discrimination task: Evaluation and implications.

This article proposes and tests a formal cognitive model for the go/no-go discrimination task. In this task, the performer chooses whether to respond to stimuli and receives rewards for responding to certain stimuli and punishments for responding to others. Three cognitive models were evaluated on the basis of data from a longitudinal study involving 400 adolescents. The results show that a cue-dependent model presupposing that participants can differentiate between cues was the most accurate and parsimonious. This model has 3 parameters denoting the relative impact of rewards and punishments on evaluations, the rate that contingent payoffs are learned, and the consistency between learning and responding. Commission errors were associated with increased attention to rewards; omission errors were associated with increased attention to punishments. Both error types were associated with low choice consistency. The parameters were also shown to have external validity: Attention to rewards was associated with externalizing behavior problems on the Achenbach scale, and choice consistency was associated with low Welsh anxiety. The present model can thus potentially improve the sensitivity of the task to differences between clinical populations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Melioration and the transition from touch-typing training to everyday use

Previous research shows that success in touch-typing training does not ensure its continuation into everyday use. It is postulated that an important contributor to this problem is melioration--that is, maximizing local rates of reinforcement. In the context of typing, melioration implies an intuitive tendency to choose typing strategies that lead to a better immediate performance level than that obtained by touchtyping. One such strategy is visually guided typing, in which the performer looks at the keys to locate their position. The present research describes a training approach that changes the reinforcement structure by increasing the attractiveness of looking at the screen while typing. This approach is implemented by using a secondary task that requires typists to respond to signals appearing on the screen. In an experiment that evaluated this solution, 22 students were given a touch-typing training course followed by a period in which they had to type their own homework. The results showed that under a modified reinforcement condition, the effect of melioration on touch-typing scores in the posttraining phase decreased. In addition, the experimental manipulation facilitated the acquisition and maintenance of the touch-typing skill. Actual or potential applications of this research include research in training, choice behavior, and human-computer interaction.