Embellishments Revisited: Perceptions of Embellished Visualisations Through the Viewer's Lens.

Embellishments are features commonly used in everyday visualisations which are demonstrated to enhance assimilation and memorability. Despite their popularity, little is known about their impact on enticing readers to explore visualisations. To address this gap, we conducted 18 interviews with a diverse group of participants who were consumers of news media but non-experts in visualisation and design. Participants were shown ten embellished and plain visualisations collected from the news and asked to rank them based on enticement and ease of understanding. Extending prior work, our interview results suggest that visualisations with multiple embellishment types might make a visualisation perceived as more enticing. An important finding from our study is that the widespread of certain embellishments in the media might have made them part of visualisation conventions, making a visualisation appear more objective but less enticing. Based on these findings, we ran a follow-up online user study showing participants variations of the visualisations with multiple embellishments to isolate each embellishment type and investigate its effect. We found that variations with salient embellishments were perceived as more enticing. We argue that to unpack the concept of embellishments; we must consider two factors: embellishment saliency and editorial styles. Our study contributes concept and design considerations to the literature concerned with visualisation design for non-experts in visualisation and design.

Assumptions about the positioning of virtual stimuli affect gaze direction estimates during Augmented Reality based interactions.

We investigated gaze direction determination in dyadic interactions mediated by an Augmented Reality (AR) head-mounted-display. With AR, virtual content is overlaid on top of the real-world scene, offering unique data visualization and interaction opportunities. A drawback of AR however is related to uncertainty regarding the AR user's focus of attention in social-collaborative settings: an AR user looking in our direction might either be paying attention to us or to augmentations positioned somewhere in between. In two psychophysical experiments, we assessed what impact assumptions concerning the positioning of virtual content attended by an AR user have on other people's sensitivity to their gaze direction. In the first experiment we found that gaze discrimination was better when the participant was aware that the AR user was focusing on stimuli positioned on their depth plane as opposed to being positioned halfway between the AR user and the participant. In the second experiment, we found that this modulatory effect was explained by participants' assumptions concerning which plane the AR user was focusing on, irrespective of these being correct. We discuss the significance of AR reduced gaze determination in social-collaborative settings as well as theoretical implications regarding the impact of this technology on social behaviour.

Dividing Attention Between Tasks: Testing Whether Explicit Payoff Functions Elicit Optimal Dual-Task Performance.

We test people's ability to optimize performance across two concurrent tasks. Participants performed a number entry task while controlling a randomly moving cursor with a joystick. Participants received explicit feedback on their performance on these tasks in the form of a single combined score. This payoff function was varied between conditions to change the value of one task relative to the other. We found that participants adapted their strategy for interleaving the two tasks, by varying how long they spent on one task before switching to the other, in order to achieve the near maximum payoff available in each condition. In a second experiment, we show that this behavior is learned quickly (within 2-3 min over several discrete trials) and remained stable for as long as the payoff function did not change. The results of this work show that people are adaptive and flexible in how they prioritize and allocate attention in a dual-task setting. However, it also demonstrates some of the limits regarding people's ability to optimize payoff functions.

Ignore Similarity If You Can: A Computational Exploration of Exemplar Similarity Effects on Rule Application.

It is generally assumed that when making categorization judgments the cognitive system learns to focus on stimuli features that are relevant for making an accurate judgment. This is a key feature of hybrid categorization systems, which selectively weight the use of exemplar- and rule-based processes. In contrast, Hahn et al. (2010) have shown that people cannot help but pay attention to exemplar similarity, even when doing so leads to classification errors. This paper tests, through a series of computer simulations, whether a hybrid categorization model developed in the ACT-R cognitive architecture (by Anderson and Betz, 2001) can account for the Hahn et al. dataset. This model implements Nosofsky and Palmeri's (1997) exemplar-based random walk model as its exemplar route, and combines it with an implementation of Nosofsky et al. (1994) rule-based model RULEX. A thorough search of the model's parameter space showed that while the presence of an exemplar-similarity effect on response times was associated with classification errors it was possible to fit both measures to the observed data for an unsupervised version of the task (i.e., in which no feedback on accuracy was given). Difficulties arose when the model was applied to a supervised version of the task in which explicit feedback on accuracy was given. Modeling results show that the exemplar-similarity effect is diminished by feedback as the model learns to avoid the error-prone exemplar-route, taking instead the accurate rule-route. In contrast to the model, Hahn et al. found that people continue to exhibit robust exemplar-similarity effects even when given feedback. This work highlights a challenge for understanding how and why people combine rules and exemplars when making categorization decisions.

Strategic Adaptation to Task Characteristics, Incentives, and Individual Differences in Dual-Tasking.

We investigate how good people are at multitasking by comparing behavior to a prediction of the optimal strategy for dividing attention between two concurrent tasks. In our experiment, 24 participants had to interleave entering digits on a keyboard with controlling a randomly moving cursor with a joystick. The difficulty of the tracking task was systematically varied as a within-subjects factor. Participants were also exposed to different explicit reward functions that varied the relative importance of the tracking task relative to the typing task (between-subjects). Results demonstrate that these changes in task characteristics and monetary incentives, together with individual differences in typing ability, influenced how participants choose to interleave tasks. This change in strategy then affected their performance on each task. A computational cognitive model was used to predict performance for a wide set of alternative strategies for how participants might have possibly interleaved tasks. This allowed for predictions of optimal performance to be derived, given the constraints placed on performance by the task and cognition. A comparison of human behavior with the predicted optimal strategy shows that participants behaved near optimally. Our findings have implications for the design and evaluation of technology for multitasking situations, as consideration should be given to the characteristics of the task, but also to how different users might use technology depending on their individual characteristics and their priorities.

Designing devices with the task in mind: which numbers are really used in hospitals?

OBJECTIVE: We studied the patterns of digits and numbers used when programming infusion pumps with the aim of informing the design of number entry interfaces. BACKGROUND: Number entry systems on medical devices are designed with little thought given to the numbers that will be entered. In other fields, text and number entry interfaces are designed specifically for the task that they will be used for. Doing so allows for faster and more accurate interaction. METHOD: In Study 1, logs were taken from infusion pumps used in a hospital. Information about the numbers being typed was extracted. For Study 2, three common number entry interfaces were evaluated in light of these results to determine which were best suited to the task of programming infusions. RESULTS: There are clear patterns in the numbers being used in hospitals. The digit 0 is used far more frequently than any other digit. The numbers 1,000, 100, and 50 are used in nearly half of all infusions. Study 2 demonstrates that interfaces are not optimized for entering such data. CONCLUSION: Changes could be made to the design of the number entry interface on infusion pumps, leading to a reduction in the number of key presses necessary to program a device. We offer a set of four heuristics to guide the design of number entry interfaces on infusion devices. APPLICATION: Improving the design of the number entry interface of medical devices, such as infusion pumps, would lead to improved efficiency and a reduction in the likelihood of errors.

Making a task difficult: evidence that device-oriented steps are effortful and error-prone.

Errors in the execution of procedural tasks can have severe consequences. Attempts to ameliorate these slip errors through increased training and motivation have been shown to be ineffective. Instead, we identified the steps in a task procedure on which errors are most likely to occur, so that these might be designed out of the task procedure in the first place. Specifically, we considered whether device-oriented steps (i.e., steps in the task procedure that do not directly contribute to the achievement of the task goal) are more error-prone than task-oriented steps (i.e., steps that do directly contribute to the task goal). Two experiments are reported in which participants were trained to perform a novel procedural task. Across conditions, we manipulated the extent to which each step in the task procedure appeared to contribute to the achievement of the task goal (i.e., alternating the assignment of a task step between device- and task-oriented), while keeping the interface and underlying task procedure the same. Results show that participants made more errors and took longer to complete a task step when it played a device-oriented role rather than a task-orientated role. These effects were exacerbated by the introduction of a secondary task designed to increase working memory load, suggesting that when a task step plays a device-oriented role it is more weakly represented in memory. We conclude that device-oriented task steps are inherently problematic and should be avoided where possible in the design of task procedures.

Recovering from an interruption: investigating speed-accuracy trade-offs in task resumption behavior.

Interruptions are disruptive because they take time to recover from, in the form of a resumption lag, and lead to an increase in the likelihood of errors being made. Despite an abundance of work investigating the effect of interruptions on routine task performance, little is known about whether there is a link between how quickly a task is resumed following an interruption (i.e., the duration of the postinterruption resumption lag) and the likelihood that an error is made. Two experiments are reported in which participants were interrupted by a cognitively demanding secondary mental arithmetic task while working on a routine sequential data-entry task. In Experiment 1 the time-cost of making an error on the primary task was varied between conditions. When errors were associated with a high time-cost penalty, participants made fewer errors and resumed the primary task more slowly than when errors were associated with a low time-cost penalty. In Experiment 2 participants were prohibited from resuming the primary task quickly by a 10-s system lockout period following the completion of the interrupting task. This lockout period led to a significant reduction in resumption errors because the lockout prohibited fast, inaccurate task resumptions. Taken together, our results suggest that longer resumption lags following an interruption are beneficial in terms of reducing the likelihood of errors being made. We discuss the practical implications of how systems might be designed to encourage more reflective task resumption behavior in situations where interruptions are commonplace. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Identifying optimum performance trade-offs using a cognitively bounded rational analysis model of discretionary task interleaving.

We report the results of a dual-task study in which participants performed a tracking and typing task under various experimental conditions. An objective payoff function was used to provide explicit feedback on how participants should trade off performance between the tasks. Results show that participants' dual-task interleaving strategy was sensitive to changes in the difficulty of the tracking task and resulted in differences in overall task performance. To test the hypothesis that people select strategies that maximize payoff, a Cognitively Bounded Rational Analysis model was developed. This analysis evaluated a variety of dual-task interleaving strategies to identify the optimal strategy for maximizing payoff in each condition. The model predicts that the region of optimum performance is different between experimental conditions. The correspondence between human data and the prediction of the optimal strategy is found to be remarkably high across a number of performance measures. This suggests that participants were honing their behavior to maximize payoff. Limitations are discussed.

Strategic adaptation to performance objectives in a dual-task setting.

How do people interleave attention when multitasking? One dominant account is that the completion of a subtask serves as a cue to switch tasks. But what happens if switching solely at subtask boundaries led to poor performance? We report a study in which participants manually dialed a UK-style telephone number while driving a simulated vehicle. If the driver were to exclusively return his or her attention to driving after completing a subtask (i.e., using the single break in the xxxxx-xxxxxx representational structure of the number), then we would expect to see a relatively poor driving performance. In contrast, our results show that drivers choose to return attention to steering control before the natural subtask boundary. A computational modeling analysis shows that drivers had to adopt this strategy to meet the required performance objective of maintaining an acceptable lateral position in the road while dialing. Taken together these results support the idea that people can strategically control the allocation of attention in multitask settings to meet specific performance criteria.

Exemplar similarity and rule application.

We report four experiments examining effects of instance similarity on the application of simple explicit rules. We found effects of similarity to illustrative exemplars in error patterns and reaction times. These effects arose even though participants were given perfectly predictive rules, the similarity manipulation depended entirely on rule-irrelevant features, and attention to exemplar similarity was detrimental to task performance. Comparison of results across studies suggests that the effects are mandatory, non-strategic and not subject to conscious control, and as a result, should be pervasive throughout categorization.