Cognitive Research-Principles and Implications最新文献

Data visualizations play a crucial role in communicating patterns in quantitative data, making data visualization literacy a key target of STEM education. However, it is currently unclear to what degree different assessments of data visualization literacy measure the same underlying constructs. Here, we administered two widely used graph comprehension assessments (Galesic and Garcia-Retamero in Med Dec Mak 31:444-457, 2011; Lee et al. in IEEE Trans Vis Comput Graph 235:51-560, 2016) to both a university-based convenience sample and a demographically representative sample of adult participants in the USA (N=1,113). Our analysis of individual variability in test performance suggests that overall scores are correlated between assessments and associated with the amount of prior coursework in mathematics. However, further exploration of individual error patterns suggests that these assessments probe somewhat distinct components of data visualization literacy, and we do not find evidence that these components correspond to the categories that guided the design of either test (e.g., questions that require retrieving values rather than making comparisons). Together, these findings suggest opportunities for development of more comprehensive assessments of data visualization literacy that are organized by components that better account for detailed behavioral patterns.

Predicting quitting rules is critical in visual search: Did I search enough for a cancer nodule in a breast X-ray or a threat in a baggage airport scanner? This study examines the predictive power of search organization indexes like best-r, mean ITD, PAO, or intersection rates as optimal criteria to leave a search in foraging (looking for several targets among distractors). In a sample of 29 adults, we compared static and dynamic foraging. Also, we reanalyze data from diverse foraging tasks in the lifespan already published to replicate results. Using ROC curves, all results consistently show that organization measures outperform classic intake rates commonly used in animal models to predict optimal human quitting behavior. Importantly, a combination of organization and traditional intake rates within a unitary factor is the best predictor. Our findings open a new research line for studying optimal decisions in visual search tasks based on search organization.

Humans usually adjust their attentional mode to tackle the challenges posed by environmental inputs. Depending on the uncertainty level, different attentional strategies may be adopted. As people face increasingly complicated daily situations-e.g., driving a car or chatting online-where intervals between significant events do not necessarily follow certain rules but are likely random, it appears important to understand how temporal contexts with different uncertainty levels affect temporal attention allocation when processing rapid serial inputs. We pursued this issue by employing a task examining the temporal limit of attention-the attentional blink (AB). The manipulation of temporal context was achieved by presenting trials with different inter-target intervals following either a "random-walk" or a "random" sequence. The results suggest a facilitated recovery from the AB deficit in the "random" compared to "random-walk" context, without a corresponding change in AB magnitude. Such effect is likely attributed to the higher perceived uncertainty in the former, and could be attenuated by a decrease in the temporal uncertainty level. These observations suggest that observers likely adopted a more flexible temporal attention allocation in the more unpredictable "random" context; they also support non-overlapping mechanisms responsible for AB width/duration and amplitude or lag-1 sparing. The flexibility of temporal attentional control may provide an evolutionary advantage for organisms to deal with unpredictable changes and is likely to be exploited for reference in the design of human-machine interacting platforms.

Non-rigid spatial thinking, or mental transformations where the distance between two points in an object changes (e.g., folding, breaking, bending), is required for many STEM fields but remains critically understudied. We developed and tested a non-rigid, ductile spatial skill measure based on reasoning about knots with 279 US adults (M = 30.90, SD 5.47 years; 76% White; 48% women). The resultant 54-item measure had good reliability (α = .88). Next, 147 US adults (M = 20.65, SD 2.80 years; 48% White; 56% women) completed existing spatial skills measures, the knot reasoning measure, a verbal skill measure, and surveys of current and childhood spatial activities. Knot reasoning performance was significantly, positively correlated with existing measures of spatial skill. Mental rotation and paper folding, but not bending, predicted knot reasoning task performance. We replicated work showing that men performed better than women on mental rotation and unexpectedly found that men also outperformed women on paper folding and knot reasoning, but not bending, tasks. Using structural equation modeling, we found several significant mediation effects. Men who reported less masculine-stereotyped spatial activity engagement had higher performance on the mental rotation and knot reasoning tasks. Women who reported greater engagement in feminine-stereotyped spatial activities had higher paper folding and backwards knot reasoning performance. Spatial skills did not differ among math-intensive STEM, non-math-intensive STEM, and non-STEM majors. The studies introduce a reliable measure of non-rigid, ductile string transformations and provide initial evidence of the role of gender and gendered spatial activities on non-rigid spatial skills.

False alarming, or detecting an error when there is not one, is a pervasive problem across numerous industries. The present study investigated the role of elaboration, or additional information about non-error differences in complex visual displays, for mitigating false error responding. In Experiment 1, learners studied errors and non-error differences about a virtual LEGO® model. Half of the participants received information about the error (location, omission, orientation) and difference (color, addition) categorization and identification (i.e., what constituted the error or difference). The other half of participants received the same information plus further elaboration about (1) the potential consequences of errors and (2) why differences would not pose potential problems. Receiving additional elaboration about errors and differences aided learners' ability to accurately reject non-error differences at test. Experiment 2 replicated these results with a new stimulus model and extended findings by testing whether receiving elaboration on the first model transferred to support learning in a second, similar model that did not provide elaborations. Our results replicated and extended findings from Experiment 1, such that learners who received elaboration while learning the first model also performed better at correctly rejecting non-error differences at test on the second model. Taken together, our findings provide insight on the transferrable role of feature elaboration to reduce false alarm rates during complex visual display assessments.

Auditory alarm deafness is a failure to notice a salient auditory signal in a high-load context, which is one of the major causes of flight accidents. Therefore, it is of great practical significance for aviation safety to explore ways to avoid auditory alarm deafness under a high-load scenario. One potential reason for its occurrence could be the fact that cognitive resources are limited. Working memory (WM) capacity is important for the availability of cognitive resources. The present study investigated the effects of different types of WM ability and transcranial direct current stimulation (tDCS) combined with WM training on auditory alarm sensitivity in a simulated high-load aeronautical decision-making task in two experiments, with participants who were not trained pilots. The results showed that different types of WM storage capacity did not predict auditory alarm deafness. However, individuals with high executive function of WM were more sensitive to the auditory alarm than those with low executive function. During WM training, tDCS over the right dorsolateral prefrontal cortex not only improved WM executive function but also improved auditory alarm sensitivity under high-load conditions. These findings suggest that the storage and executive function of WM have different roles in auditory alarm sensitivity. WM training based on brain stimulation technology can provide empirical evidence for the enhancement of auditory alarm alertness and cognitive function in the human-machine context.

In contexts where people lack prior knowledge and risk awareness-such as the COVID-19 pandemic-even truthful visualizations of data can seem surprising. This can lead people to mistrust the veracity of the data and to discount it, leading to poor risk decisions. In this work, we illustrate how narrative visualizations can achieve a balance between the benefits of three common risk communication mediums (static visualizations, interactive simulations, and affect-laden anecdotes). We demonstrate empirically that viewing a narrative visualization mitigates the reduced concern induced by a static visualization when communicating COVID-19 transmission risk (Study 1). Through mediation analysis, we show that narrative visualizations are more effective than static visualizations at increasing concern about large risks because they increase one's perceived understanding and trust in data (Study 2). We argue that narrative visualizations deserve attention as a distinct class of visualizations that have the potential to be powerful tools for scientific communication (especially in contexts where data are surprising, and empiricism is important).

People navigate in various types of spaces, including indoor and outdoor environments. These differ in availability of navigational cues, such as distal landmarks, clear boundaries, and regular grid structures. Does learning the layout of different types of environments rely on the same or diverse cognitive abilities? Do separate measures of learning reflect different abilities? In a study of individual differences, 88 people learned the layout of two virtual environments from first person experience: a grid-like maze, and a campus-like open environment. After learning each environment, their knowledge was measured by three tasks; onsite pointing, map-reconstruction, and wayfinding. Performance on these measures was significantly correlated. In confirmatory factor analyses, the best fitting model indicated separate factors for spatial knowledge acquisition of the grid-like maze and the outdoor open environment. However, these two factors also shared considerable variance, indicating that they reflect a common underlying ability. There was no evidence that different measures of learning (pointing, map reconstruction, and wayfinding) defined separate abilities, adding to their validity as alternative measures of configural knowledge. Performance of map-based navigation and path integration in the mobile navigation game Sea Hero Quest was generally not correlated with performance in the environment learning tasks, nor were self-report measures of sense of direction and spatial anxiety. Our research suggests that there is a common ability related to learning spatial layout in different contexts, but this may be distinct from other navigation abilities.

In two experiments, we examine how features of an imperfect automated decision aid influence compliance with the aid in a simplified, simulated nautical collision avoidance task. Experiment 1 examined the impact of providing transparency in the pre-task instructions regarding which attributes of the task that the aid uses to provide its recommendations. Results showed that transparency here positively influenced compliance with the aid, leading to better task performance. Experiment 2 manipulated transparency via confidence estimates presented alongside the aid's recommendations. There were no benefits from this form of transparency. In Experiment 2, lower compliance with the aid's recommendations was found on more difficult collision problems, via a mediating loss of aid reliability and therefore trust. This runs contrary to the hypothesis that harder problems to solve ought to make participants more, rather than less dependent on the aid. Both experiments produced relatively low correlations between trust and compliance. The findings have important implications for the effectiveness of different kinds of transparency implementations, as well as providing a model/framework for understanding how generic factors such as automation reliability and problem difficulty influence both compliance and trust.

Being able to notice that a cause-effect relation is getting stronger or weaker is important for adapting to one's environment and deciding how to use the cause in the future. We conducted an experiment in which participants learned about a cause-effect relation that either got stronger or weaker over time. The experiment was conducted with a typical procedure in which the learning cases were presented rapidly, and with a mobile phone procedure, in which participants experienced the cause-effect relation over 24 days. First, we found that people could detect the change in contingency. They were better at doing so in the artificial short timeframe task, but still could do so in the more realistic long timeframe task. Second, when making summary judgments about the cause-effect relation, participants exhibited a recency effect for most measures in the long timeframe, but did not exhibit a primacy or recency effect in the short timeframe. Third, though participants' episodic memories for individual cause-effect events in the learning sequence were quite poor, they did exhibit primacy and recency effects in the short timeframe; these were attenuated in the long timeframe. These findings raise fundamental questions about causal learning; they suggest that people automatically recognize changes and store representations of the contingency during different phases of learning, but this ability is not predicted by most existing theories of causal learning.