Visual perspective taking for avatars in a Simon task

In modern digital applications, users often interact with virtual representations of themselves or others, called avatars. We examined how these avatars and their perspectives influence stimulus–response compatibility in a Simon task. Participants responded to light/dark blue stimuli with left/right key presses in the presence of a task-irrelevant avatar. Changes in stimulus–response compatibility were used to quantify changes in the mental representation of the task and perspective taking toward this avatar. Experiments 1 and 2 showed that perspective taking for an avatar occurred in orthogonal stimulus–response mappings, causing a compatibility effect from the avatar’s point of view. In the following two experiments we introduced a larger variety of angular disparities between the participant and avatar. In Experiment 3, the Simon effect with lateralized stimulus positions remained largely unaffected by the avatar, pointing toward an absence of perspective taking. In Experiment 4, after avatar hand movements were added in order to strengthen the participants’ sense of agency over the avatar, a spatial compatibility effect from the avatar’s perspective was observed again, and hints of the selective use of perspective taking on a trial-by-trial basis were found. Overall, the results indicate that users can incorporate the perspective of an avatar into their mental representation of a situation, even when this perspective is unnecessary to complete a task, but that certain contextual requirements have to be met.     

Intended and unintended effects of explicit warnings on eyewitness suggestibility: Evidence from source identification tests

Previous studies have shown that source identification (ID) tests reduce, and in some cases eliminate, eyewitness suggestibility errors. The present study showed that the suggestibility errors participants committed on a source ID test were further reduced when they were given the explicit postwarning that the experimenter was trying to trick them. These postwarnings reduced suggestibility to the same extent as prewarnings, and they did so for both once and repeatedly suggested items. In addition, the benefits of the pre- and postwarnings persisted when participants were retested 1 week later, but only if the suggestions had been repeated. For once-suggested items, the warning had the unintended effect of improving old/new recognition of the suggested information at retest, an effect that offset the improvements in source discrimination accuracy conferred by the warning. The advantages of using source ID tests for investigating group differences in eyewitness suggestibility are discussed.     

Examining the effectiveness of a community-based self-help program to increase women's readiness for smoking cessation

This study investigated the effectiveness of two components of a smoking cessation intervention: a reading manual and a series of televised programs. Female smokers in the Chicago metropolitan area with a high school education or less were interviewed at 4 different times: baseline, immediate postintervention, and 6 and 12 months. We examined the effects of several baseline measures (race, age, number of cigarettes smoked, and stage of readiness to change) and exposure to the intervention components on subsequent stage of change. Race, baseline smoking rate, baseline stage, and exposure to both intervention components had direct effects on stage at immediate postintervention, with both intervention components increasing readiness to quit. Furthermore, exposure to the manual interacted with baseline stage, such that the manual benefited women at earlier stages more than women at later stages. Effects of both components were sustained at 6 months, and the effects of the manual were sustained at 12 months.     

Age-of-acquisition and cumulative frequency have independent effects

Lewis (1999) argued that effects of age of acquisition (AoA) are entirely attributable to cumulative frequency. He reported an instance-based model in which the number of instances of the stimulus stored in memory predicts reaction time. We note four aspects of the literature on AoA that cannot be explained by this instance-based approach. Firstly, an effect of AoA has been observed in the absence of an effect of frequency. Secondly, an effect of AoA has been observed when cumulative frequency has been controlled. Thirdly, the effect of AoA is dependent on task. Fourthly, the effect of word frequency is dependent on stimulus modality. Lewis reported an experiment in which participants make a decision based on identity-specific semantic information to celebrity faces to demonstrate an effect of the number of instances in memory, which he interpreted as an effect of AoA. We note that effects of AoA have been found in lexical and perceptual tasks, but to date all attempts to demonstrate an advantage for early-acquired items in semantic classification tasks have failed. We conclude that the effects of AoA cannot be attributed solely to the effects of cumulative frequency.     

Influences of age, performance, and item relatedness on verbatim and gist recall of verb-noun pairs

Age differences in adults' memory for performed actions (e.g., wave hand) are sometimes smaller than age differences in memory for nonperformed phrases. In this study, we examined the conditions under which performance reduces age differences in recall. Younger and older adults performed or read verb-noun phrases that were either related (e.g., actions performed in a kitchen) or unrelated. Performance did not reduce age differences in recall of the exact verbs and nouns used to describe an action, but performance did reduce age differences in memory for the gist of related actions. Older adults especially had difficulty recalling the exact verb used to describe the action. These results suggest that older adults may have better memory for actions than is revealed by tests of verbatim recall. They may remember performing the action but not remember the exact words used to describe the action.     

Knowledge level learning and the power law: A soar model of skill acquisition in scheduling

Zusammenfassung. Das hier vorgestellte Modell lernt graduell, Planungsaufgaben aus der Klasse der Maschinenbelegungsprobleme (job-shop-scheduling problems) zu lösen. Mit Hilfe des Chunking-Mechanismus von Soar wird episodisches Wissen über die Belegungsreihenfolge von Aufträgen auf Maschinen memoriert. Bei der Entwicklung des Modells wurden zahlreiche qualitative (z. B. Transfereffekte) und quantitative Befunde (z. B. Bearbeitungszeiten) aus einer früheren empirischen Untersuchung berücksichtigt. In einer Validierungsstudie wurden dieselben Aufgaben von 14 Probanden und dem Modell bearbeitet. Die Passung von Simulationsdaten und empirischen Ergebnissen fiel insgesamt gut aus. Allerdings löst das Modell die Aufgaben schneller und zeigt auch einen etwas besseren Lernverlauf als die Probanden. Das Modell liefert eine Erklärung für das Rauschen, das typischerweise bei Bearbeitungszeiten zu beobachten ist: es handelt sich um erworbenes Wissen, das mehr oder weniger gut und auch unterschiedlich häufig auf neue Situationen übertragen wird. Der Lernverlauf der Probanden entspricht nur für aggregierte Daten einer Potenzfunktion (power law). Der vorgestellte Mechanismus zeigt, wie ein symbolisches Modell der Informationsverarbeitung graduelle Verhaltensänderungen generiert und wie der offensichtliche Erwerb allgemeiner Prozeduren ohne explizites Lernen von deklarativen Regeln erfolgen kann. Es wird nahegelegt, daß es sich hier um die Modellierung einer Form impliziten Lernens handelt. Summary. The model presented here gradually learns how to perform a job-shop scheduling task. It uses Soar's chunking mechanism to acquire episodic memories about the order to schedule jobs. The model was based on many qualitative (e.g., transfer effects) and quantitative (e.g., solution time) regularities found in previously collected data. The model was tested with new data where scheduling tasks were given to the model and to 14 subjects. The model generally fit these data with the restrictions that the model performs the task (in simulated time) faster than the subjects, and its performance improves somewhat more quickly than the subjects' performance. The model provides an explanation of the noise typically found in problem solving times - it is the result of learning actual pieces of knowledge that transfer more or less to new situations but rarely by an average amount. Only when the data are averaged (i.e., over subjects) does the smooth power law appear. This mechanism demonstrates how symbolic models can exhibit a gradual change in behavior and how the apparent acquisition of general procedures can be performed without resorting to explicit declarative rule generation. We suggest that this may represent a type of implicit learning.