Making TV Commercials as a Teaching Aid for Cognitive Psychology

Many students approach psychology in general, and cognitive psychology in particular, with serious misconceptions about the scientific nature of the discipline. In order to address this problem and bring laboratory findings in cognitive psychology into a real world context, we asked students in an introductory cognitive course to make TV commercials using principles learned in class. The success of the approach became evident from analysis of course evaluation forms and the generally high quality of students' productions.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Workload and Performance in FOPA: A Strategic Planning Interface for Air Traffic Control

The Flight Organizer Planning Aid (FOPA) interface was designed to aid strategic planning in air traffic control. In particular, FOPA was designed to address difficulties in solving en route sequencing problems (combining multiple streams of traffic into a single stream heading for a destination). We compared the planning performance of 12 full performance level air traffic controllers using either the FOPA interface or normal flight progress strips. Planning performance was significantly better when using FOPA; subjective workload was also reduced. The results indicate that a key advantage of FOPA lies in its dynamic linkage between the flight organizer screen where aircraft tokens can be categorized into color-coded blocks and their matching spatial representation on the radar.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Blame framing and prior knowledge influence moral judgments for people involved in the Tulsa Race Massacre among a combined Oklahoma and UK sample

IntroductionHow an event is framed impacts how people judge the morality of those involved, but prior knowledge can influence information processing about an event, which also can impact moral judgments. The current study explored how blame framing and self-reported prior knowledge of a historical act of racial violence, labeled as Riot, Massacre, or Event, impacted individual’s cumulative moral judgments regarding the groups involved in the Tulsa Race Massacre (Black Tulsans, the Tulsa Police, and White Tulsans).Methods and resultsThis study was collected in two cohorts including undergraduates attending the University of Oklahoma and individuals living in the United Kingdom. Participants were randomly assigned to a blame framing condition, read a factual summary of what happened in Tulsa in 1921, and then responded to various moral judgment items about each group. Individuals without prior knowledge had higher average Likert ratings (more blame) toward Black Tulsans and lower average Likert ratings (less blame) toward White Tulsans and the Tulsa Police compared to participants with prior knowledge. This finding was largest when what participants read was framed as a Massacre rather than a Riot or Event. We also found participants with prior knowledge significantly differed in how they made moral judgments across target groups; those with prior knowledge had lower average Likert ratings (less blame) for Black Tulsans and higher average Likert ratings (more blame) for White Tulsans on items pertaining to causal responsibility, intentionality, and punishment compared to participants without prior knowledge.DiscussionFindings suggest that the effect of blame framing on moral judgments is dependent on prior knowledge. Implications for how people interpret both historical and new events involving harmful consequences are discussed

ROCs in Eyewitness Identification: Instructions vs. Confidence Ratings

From the perspective of signal-detection theory, different lineup instructions may induce different levels of response bias (Clark, 2005). If so, then collecting correct and false identification rates across different instructional conditions will trace out the ROC – the same ROC that, theoretically, could also be traced out from a single instruction condition in which each eyewitness decision is accompanied by a confidence rating. We tested whether the two approaches do in fact yield the same ROC. Participants were assigned to a confidence rating condition or to an instructional biasing condition (liberal, neutral, unbiased, or conservative). After watching a video of a mock crime, participants were presented with instructions followed by a 6-person simultaneous photo lineup. The ROCs from both methods were similar, but they were not exactly the same. These findings have potentially important policy implications for how the legal system should go about controlling eyewitness response bias

Aiding Planning in Air Traffic Control: An Experimental Investigation of the Effects of Perceptual Information Integration

Prior research examined how controllers plan in their traditional environment and identified various information uncertainties as detriments to planning. A planning aid was designed to reduce this uncertainty by perceptually representing important constraints. This included integrating spatial information on the radar screen with discrete information (planned sequences of air traffic). Previous research reported improved planning performance and decreased workload in the planning aid condition. The purpose of this paper was to determine the source of these performance improvements. Analysis of computer interactions using loglinear modeling showed that the planning interface led to less repetitive - but more integrated - information retrieval compared with the traditional planning environment. Ecological interface design principles helped explain how the integrated information retrieval gave rise to the performance improvements. Actual or potential applications of this research include the design and evaluation of interface automation that keeps users in active control by modification of perceptual task characteristics.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Assessing Theoretical Conclusions With Blinded Inference to Investigate a Potential Inference Crisis

Scientific advances across a range of disciplines hinge on the ability to make inferences about unobservable theoretical entities on the basis of empirical data patterns. Accurate inferences rely on both discovering valid, replicable data patterns and accurately interpreting those patterns in terms of their implications for theoretical constructs. The replication crisis in science has led to widespread efforts to improve the reliability of research findings, but comparatively little attention has been devoted to the validity of inferences based on those findings. Using an example from cognitive psychology, we demonstrate a blinded-inference paradigm for assessing the quality of theoretical inferences from data. Our results reveal substantial variability in experts’ judgments on the very same data, hinting at a possible inference crisis

Insights into the accuracy of social scientists' forecasts of societal change

How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing the accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender–career and racial bias. After we provided them with historical trend data on the relevant domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N = 86 teams and 359 forecasts), with an opportunity to update forecasts on the basis of new data six months later (Tournament 2; N = 120 teams and 546 forecasts). Benchmarking forecasting accuracy revealed that social scientists’ forecasts were on average no more accurate than those of simple statistical models (historical means, random walks or linear regressions) or the aggregate forecasts of a sample from the general public (N = 802). However, scientists were more accurate if they had scientific expertise in a prediction domain, were interdisciplinary, used simpler models and based predictions on prior data