Understanding and Improving the Performance of Action PointingAction pointing involves choosing and executing an action at a specific place in the workspace (e.g., choosing a tool and clicking to start drawing, or selecting an object and copying with a shortcut). The elements of action pointing (choosing an action, specifying a position, and triggering the action) can be carried out in many ways - and our analysis of current techniques identified limitations on performance, particularly for repeated sequences of interactions. To empirically analyse interaction alternatives for action pointing, we developed and evaluated two techniques: ModeKeys removes modifier keys from keyboard shortcuts used to choose actions; AimKeys goes further by using the shortcut (not the mouse) to trigger the action. Three studies over three tasks showed that these reconfigurations were highly effective - in all studies, either AimKeys or ModeKeys were faster, easier, and preferred overall. Our studies show that small variations in the configuration of action pointing can have a large impact, offering opportunities to improve performance with direct-manipulation systems.2025CBCameron Beattie et al.University of SaskatchewanFull-Body Interaction & Embodied InputKnowledge Worker Tools & WorkflowsCHI
Effects of Device Environment and Information Layout on Spatial Memory and Performance in VR Selection TasksVirtual Reality systems are increasingly proposed as a platform for everyday interactive software. Many applications are dependent on actions such as navigation and selection, but it is not clear how well immersive environments support these basic activities. Previous studies have suggested advantages for spatial learning in VR, so we carried out a study that investigated two aspects of immersion on spatial memory and selection: the degree to which the user is immersed in the data, and whether the system uses immersive input and output. The study showed that more-immersive conditions had substantially worse selection performance, and did not improve spatial learning. However, most participants believed that the immersive conditions were better for learning object locations, and most people preferred the immersive layout and the HMD. Our study suggests that designers should be cautious about assuming that everyday software applications will benefit from being deployed in an immersive VR environment.2024KKKim Kargut et al.University of SaskatchewanEye Tracking & Gaze InteractionImmersion & Presence ResearchCHI
`Specially For You' -- Examining the Barnum Effect's Influence on the Perceived Quality of System RecommendationsThe ‘Barnum effect’ is a psychological phenomenon under which people assign higher quality ratings to personality descriptions developed ‘specially for you’ than the same descriptions described as ‘generally true of people.’ This effect suggests that recommender interfaces could elevate the perceived quality of recommendations simply by indicating that they are explicitly personalised. We therefore conducted a crowd-sourced experiment (n=492) that examined the perceived quality of personalised versus non-personalised movie recommendations for good and bad movies – importantly, the actual recommendations were identical, and were merely presented as being either personalised or not. Contrary to the Barnum effect, results showed numerically lower mean quality scores for personalised recommendations, but with no significant difference. Our findings suggest that Barnum-like effects of personalisation have at most a small influence on perceived quality, and that designers should not rely on this effect to improve user experience (despite online design guidance suggesting the opposite).2023PSPang Suwanaposee et al.University of CanterburyRecommender System UXVisualization Perception & CognitionCHI
Probability Weighting in Interactive Decisions: Evidence for Overuse of Bad Assistance, Underuse of Good AssistanceThe effective use of assistive interfaces (i.e. those that offer suggestions or reform the user's input to match inferred intentions) depends on users making good decisions about whether and when to engage or ignore assistive features. However, prior work from economics and psychology shows systematic decision-making biases in which people overreact to low probability events and underreact to high probability events -- modelled using a probability weighting function. We examine the theoretical implications of this probability weighting for interaction, including its suggestion that users will overuse inaccurate interface assistance and underuse accurate assistance. We then conduct a new analysis of data from a previously published study, quantifying the degree of bias users exhibited, and demonstrating conformance with these predictions. We discuss implications for design, including strategies that could be used to mitigate the deleterious effects of the observed biases.2022ACAndy Cockburn et al.University of CanterburyExplainable AI (XAI)AI-Assisted Decision-Making & AutomationAI Ethics, Fairness & AccountabilityCHI
More Errors vs. Longer Commands: The Effects of Repetition and Reduced Expressiveness on Input Interpretation Error, Learning, and User PreferenceMany interactive systems are susceptible to misinterpreting the user's input actions or gestures. Interpretation errors are common when systems gather a series of signals from the user and then attempt to interpret the user's intention based on those signals -- e.g., gesture identification from a touchscreen, camera, or body-worn electrodes -- and previous work has shown that interpretation error can cause significant problems for learning new input commands. Error-reduction strategies from telecommunications, such as repeating a command or increasing the length of the input while reducing its expressiveness, could improve these input mechanisms -- but little is known about whether longer command sequences will cause problems for users (e.g., increased effort or reduced learning). We tested performance, learning, and perceived effort in a crowd-sourced study where participants learned and used input mechanisms with different error-reduction techniques. We found that error reduction techniques are feasible, can outperform error-prone ordinary input, and do not negatively affect learning or perceived effort.2022KLKevin C. Lam et al.University of SaskatchewanHand Gesture RecognitionHuman Pose & Activity RecognitionCHI
The Effects of System Interpretation Errors on Learning New Input MechanismsInput mechanisms can produce noisy signals that computers must interpret, and this interpretation can misconstrue the user’s intention. Researchers have studied how interpretation errors can affect users’ task performance, but little is known about how these errors affect learning, and whether they help or hinder the transition to expertise. Previous findings suggest that increasing the user’s attention can facilitate learning, so frequent interpretation errors may increase attention and learning; alternatively, however, interpretation errors may negatively interfere with skill development. To explore these potentially important effects, we conducted studies where participants learned commands with various rates of artificially injected interpretation errors. Our results showed that higher rates of interpretation error led to worse memory retention, higher completion times, higher occurrences of user error (beyond those injected by the system), and greater perceived effort. These findings indicate that when input mechanisms must interpret the user's input, interpretation errors cause problems for user learning.2021KLKevin C. Lam et al.University of SaskatchewanHand Gesture RecognitionEye Tracking & Gaze InteractionCHI
Interaction Pace and User PreferencesThe overall pace of interaction combines the user's pace and the system's pace, and a pace mismatch could impair user preferences (e.g., animations or timeouts that are too fast or slow for the user). Motivated by studies of speech rate convergence, we conducted an experiment to examine whether user preferences for system pace are correlated with user pace. Subjects first completed a series of trials to determine their user pace. They then completed a series of hierarchical drag-and-drop trials in which folders automatically expanded when the cursor hovered for longer than a controlled timeout. Results showed that preferences for timeout values correlated with user pace -- slow-paced users preferred long timeouts, and fast-paced users preferred short timeouts. Results indicate potential benefits in moving away from fixed or customisable settings for system pace. Instead, systems could improve preferences by automatically adapting their pace to converge towards that of the user.2021AGAlix Goguey et al.Université Grenoble AlpesVisualization Perception & CognitionCHI
Interaction Interferences: Implications of Last-Instant System State ChangesWe study interaction interferences, situations where an unexpected change occurs in an interface immediately before the user performs an action, causing the corresponding input to be misinterpreted by the system. For example, a user tries to select an item in a list, but the list is automatically updated immediately before the click, causing the wrong item to be selected. First, we formally define interaction interferences and discuss their causes from behavioral and system-design perspectives. Then, we report the results of a survey examining users’ perceptions of the frequency, frustration, and severity of interaction interferences. We also report a controlled experiment, based on state-of-the-art experimental protocols from neuroscience, that explores the minimum time interval, before clicking, below which participants could not refrain from completing their action. Finally, we discuss our findings and their implications for system design, paving the way for future work.2020PSPhilippe Schmid et al.Privacy by Design & User ControlNotification & Interruption ManagementUIST
KeyMap: Improving Keyboard Shortcut Vocabulary Using Norman's MappingWe introduce a new shortcut interface called KeyMap that is designed to leverage Norman's principle of natural mapping. Rather than displaying shortcut command labels in linear menus, KeyMap displays a virtual keyboard with command labels displayed directly on its keys. A crowdsourced experiment compares KeyMap to Malacria et al.'s ExposeHK using an extension of their protocol to also test recall. Results show KeyMap users remembered 1 more shortcut than ExposeHK immediately after training, and this advantage increased to 4.5 more shortcuts when tested again after 24 hours. KeyMap users also incidentally learned more shortcuts that they had never practised. We demonstrate how KeyMap can be added to existing web-based applications using a Chrome extension.2020BLBlaine Lewis et al.University of TorontoPrototyping & User TestingCHI
Framing Effects Influence Interface Feature DecisionsStudies in psychology have shown that framing effects, where the positive or negative attributes of logically equivalent choices are emphasised, influence people's decisions. When outcomes are uncertain, framing effects also induce patterns of choice reversal, where decisions tend to be risk averse when gains are emphasised and risk seeking when losses are emphasised. Studies of these effects typically use potent framing stimuli, such as the mortality of people suffering from diseases or personal financial standing. We examine whether these effects arise in users' decisions about interface features, which typically have less visceral consequences, using a crowd-sourced study based on snap-to-grid drag-and-drop tasks (n = 842). The study examined several framing conditions: those similar to prior psychological research, and those similar to typical interaction choices (enabling/disabling features). Results indicate that attribute framing strongly influences users' decisions, that these decisions conform to patterns of risk seeking for losses, and that patterns of choice reversal occur.2020ACAndy Cockburn et al.University of CanterburyExplainable AI (XAI)Visualization Perception & CognitionUser Research Methods (Interviews, Surveys, Observation)CHI
Anchoring Effects and Troublesome Asymmetric Transfer in Subjective RatingsWithin-subjects experiments are prone to asymmetric transfer, which confounds results interpretation. While HCI researchers routinely test asymmetric transfer in objective data, doing so for subjective data is rare. Yet literature suggests that anchoring effects should make subjective measures particularly susceptible to asymmetric transfer. We report on four analyses of NASA-TLX data from four previously published HCI papers, with four main findings. First, asymmetric transfer is common, occurring in 42% of tests analysed. Second, the data conforms to predictions of anchoring effects. Third, the magnitude of the anchor's effect correlates with the magnitude of the difference between the interface ratings -- that is, the anchor's 'pull' correlates with the anchoring stimulus. Fourth, several of the previously published findings are changed when data are reanalysed using between-subjects treatment. We urge caution when analysing within-subjects subjective measures and recommend that researchers test for and report the occurrence of asymmetric transfer.2019ACAndy Cockburn et al.University of CanterburyChronic Disease Self-Management (Diabetes, Hypertension, etc.)Computational Methods in HCICHI
Peripheral Notifications in Large Displays: Effects of Feature Combination and Task InterferenceVisual notifications are integral to interactive computing systems. With large displays, however, much of the content is in the user's visual periphery, where human capacity to notice visual effects is diminished. One design strategy for enhancing noticeability is to combine visual features, such as motion and colour. Yet little is known about how feature combinations affect noticeability across the visual field, or about how peripheral noticeability changes when a user's primary task involves the same visual features as the notification. We addressed these questions by conducting two studies. Results of the first study showed that noticeability of feature combinations were approximately equal to the better of the individual features. Results of the second study suggest that there can be interference between the features of primary tasks and the visual features in the notifications. Our findings contribute to a better understanding of how visual features operate when used as peripheral notifications.2019AMAristides Mairena et al.University of SaskatchewanVisualization Perception & CognitionNotification & Interruption ManagementCHI
Investigating the Post-Training Persistence of Expert Interaction TechniquesExpert interaction techniques enable users to greatly improve their performance; however, to realize these advantages, the user must first acquire the skill necessary to use a technique, then choose to use it over competing novice techniques. This article investigates several factors that may influence whether use of an expert technique persists when the context of use changes. Two studies examine the effect of changing performance requirements, and find that a high performance requirement imposed in a training context can effectively push users to adopt an expert technique, and that use of the technique is maintained when the requirement is subsequently reduced or removed. In a final study, performance requirement, high-level task, and environment of use are changed—participants played a training game to learn the menu for a drawing application, which they then used to complete a series of drawings over the following week. Participants exhibited a somewhat surprising “all-or-nothing” effect, using the expert technique nearly exclusively or not at all, and maintaining this behavior over a range of qualitatively different tasks. This suggests that switching to an expert technique involves a global change by the user, rather than an incremental change as suggested by previous work.2018BLBenjamin Lafreniere et al.Autodesk ResearchPrototyping & User TestingCHI
Storyboard-Based Empirical Modeling of Touch Interface PerformanceTouch interactions are now ubiquitous, but few tools are available to help designers quickly prototype touch interfaces and predict their performance. For rapid prototyping, most applications only support visual design. For predictive modelling, tools such as CogTool generate performance predictions but do not represent touch actions natively and do not allow exploration of different usage contexts. To combine the benefits of rapid visual design tools with underlying predictive models, we developed the Storyboard Empirical Modelling tool (StEM) for exploring and predicting user performance with touch interfaces. StEM provides performance models for mainstream touch actions, based on a large corpus of realistic data. We evaluated StEM in an experiment and compared its predictions to empirical times for several scenarios. The study showed that our predictions are accurate (within 7% of empirical values on average), and that StEM correctly predicted differences between alternative designs. Our tool provides new capabilities for exploring and predicting touch performance, even in the early stages of design.2018AGAlix Goguey et al.University of SaskatchewanPrototyping & User TestingCHI
Reducing the Attentional Demands of In-Vehicle Touchscreens with Stencil OverlaysVehicle manufacturers are increasingly using touchscreens to support driver access to controls. However, input mechanisms displayed on touchscreens lack the tactile sensations of physical controls, creating risks of greater demand for visual attention. These risks can potentially be mitigated by restoring some degree of tactile feedback to touchscreen interaction. This paper describes a study that examines whether touchscreen target selection during simulated driving is improved by overlaying the touchscreen with a see-through 3D printed stencil that allows underlying touchscreen controls to be located or guided by feel. Results showed that touchscreen targets were selected more quickly and with shorter periods of visual attention towards the touchscreen when the stencil was present than when it was absent. Subjective preferences also favoured the stencil condition. The work demonstrates the value of adding tactile feedback to touchscreen interaction, and shows that stencils are a simple and effective way to reduce attentional demands.2018ACAndy Cockburn et al.In-Vehicle Haptic, Audio & Multimodal FeedbackAutoUI
HARK No More: On the Preregistration of CHI ExperimentsExperimental preregistration is required for publication in many scientific disciplines and venues. When experimental intentions are preregistered, reviewers and readers can be confident that experimental evidence in support of reported hypotheses is not the result of HARKing, which stands for Hypothesising After the Results are Known. We review the motivation and outcomes of experimental preregistration across a variety of disciplines, as well as previous work commenting on the role of evaluation in HCI research. We then discuss how experimental preregistration could be adapted to the distinctive characteristics of Human-Computer Interaction empirical research, to the betterment of the discipline.2018ACAndy Cockburn et al.University of CanterburyComputational Methods in HCIResearch Ethics & Open ScienceCHI