Current augmented reality (AR) headset applications often fail to consider users’ natural interaction preferences, which leads to unintuitive interfaces and increased user frustration. We conducted an open-ended elicitation study with 30 adults to discover their natural interaction preferences in AR headsets. Participants proposed first-choice and second-choice interactions for 17 3D virtual cube actions (e.g., moving, rotating) using any interaction modality they preferred (e.g., gesture, speech, etc.). We broke down the participants’ most common interactions for each cube action. We found that while hand gestures were the overwhelming first choice (82%), over half of all second choices (52%) involved a switch to a different modality (e.g., from gesture to speech), highlighting a critical need for interaction flexibility in AR headset applications. Additionally, our open-ended approach uncovered interactions that go beyond standard 3D commercial AR headset interactions, such as thinking, blowing air, and air-drawing. Based on our findings, we contribute an understanding of adults’ natural AR headset expectations for 3D virtual object manipulation that can inform future applications.

Children are increasingly using augmented reality (AR) headsets in different contexts, such as education. However, it is unclear how children expect to interact with virtual objects in AR headsets; children’s expectations for technology can significantly differ from adults. Therefore, we conducted an elicitation study with 20 children (ages 9-12), in which children proposed interactions for tasks with a virtual cube (e.g., moving, expanding, creating, etc.) in an AR headset. We constructed a conceptual model of children’s expectations with virtual-object interactions in AR headsets and analyzed their proposed interactions. We found that children preferred gestures, expecting to utilize their whole body (e.g., pushing, kicking) and external objects (e.g., hammer, sword) to interact with the cube, and rarely considered speech, which differs from adults. Children also frequently added their own motivations, creating a narrative behind their interactions. We provide foundational insights into children’s expectations for virtual-object interaction in AR headsets.

Augmented Reality (AR) interactions feature users interacting with virtual objects registered in the physical world. With contemporary AR experiences increasingly featuring interactions at distances, we conceptualized The Force, a technique that allows users to clone distant objects and manipulate their replicas. An empirical evaluation was conducted, comparing it against two well-established techniques including controller-based ray-casting and a gaze-based pinching technique in a pick-and-place task. We employed a within-subjects design, collecting data on both objective performance and subjective user experience. Results suggest that The Force allows for higher levels of accuracy and efficiency in medium-field tasks that require precision and fine motor control. Furthermore, we discovered avenues towards iteratively refining this technique. We go on to discuss the implications of our findings in an effort to facilitate better interactions in augmented reality.

From handheld devices to head-mounted displays, augmented reality (AR) technologies are becoming commonplace in everyday settings, supporting tasks in education, healthcare, gaming, and beyond. Prior research has developed a number of evidence-based design recommendations for AR apps. However, these recommendations are often scattered across academic literature and differ in scope and focus. In addition, there are still open research questions about the degree to which existing guidelines are applied in practice, particularly in handheld AR contexts. To address these gaps, we synthesized AR design recommendations from academic literature and organized them into an integrated set of guidelines. We then empirically analyzed 52 commercial handheld AR apps to assess how well they align with these guidelines. We found that while most apps follow basic usability guidelines, such as using familiar UI layouts, many apps do not adopt context-aware features, offer limited support for multimodal interaction and feedback, and overlook key usability practices such as onboarding and navigational aids. In addition, we saw very few guidelines related to data privacy, collaborative AR, safety and accessibility. We contribute a synthesis of evidence-based AR recommendations and identify key areas of disconnect between recommendations and practice for handheld AR apps, which aids future designers and developers.

Although children are increasingly using smart technology, there is limited knowledge on what children define as “smart” for technology. Understanding what children expect as “smart” would ensure more effective positive experiences with smart devices. To investigate children's expectations, we conducted five participatory design sessions with 10 children focused on designing smart technology. The children also interacted with four commercial smart devices (i.e., robot, AR headset, voice assistant, tablet with AR applications) and judged them on intelligence. We found that children expect smart technologies to have advanced intelligence, human-like characteristics, immersive experiences, and serve multiple purposes. Furthermore, children thought smart devices should be difficult and complex to make. We also observed negative interactions with current smart devices, such as physical device limitations. The insights gained from this study can inform the design and development of future smart technology devices, ensuring they are engaging and aligned with children's needs and preferences.

Mobile health applications for weight maintenance offer self-monitoring as a tool to empower users to achieve health goals (e.g., losing weight); yet maintaining consistent self-monitoring over time proves challenging for users. These apps use push notifications to help increase users’ app engagement and reduce long-term attrition, but they are often ignored by users due to appearing at inopportune moments. Therefore, we analyzed whether delivering push notifications based on time alone or also considering user context (e.g., current activity) affected users’ engagement in a weight maintenance app, in a 4-week in-the-wild study with 30 participants. We found no difference in participants’ overall (across the day) self-monitoring frequency between the two conditions, but in the context-based condition, participants responded faster and more frequently to notifications, and logged their data more timely (as eating/exercising occurs). Our work informs the design of notifications in weight maintenance apps to improve their efficacy in promoting self-monitoring.

Augmented reality (AR) headsets are being utilized in different task-based domains (e.g., healthcare, education) for both adults and children. However, prior work has mainly examined the applicability of AR headsets instead of how to design the visual information being displayed. It is essential to study how visual information should be presented in AR headsets to maximize task performance for both adults and children. Therefore, we conducted two studies (adults vs. children) analyzing distinct design combinations of critical and secondary textual information during a procedural assembly task. We found that while the design of information did not affect adults' task performance, the location of information had a direct effect on children's task performance. Our work contributes new understanding on how to design textual information in AR headsets to aid in adults’ and children's task performance. In addition, we identify specific differences on how to design textual information between adults and children.

Situational awareness is the perception and understanding of the surrounding environment. Maintaining situational awareness is vital for performance and error prevention in safety critical domains. Prior work has examined applying augmented reality (AR) to the context of improving situational awareness, but has mainly focused on the applicability of using AR rather than on information design. Hence, there is a need to investigate how to design the presentation of information, especially in AR headsets, to increase users' situational awareness. We conducted a Systematic Literature Review to research how information is currently presented in AR, especially in systems that are being utilized for situational awareness. Comparing current presentations of information to existing design recommendations aided in identifying future areas of design. In addition, this survey further discusses opportunities and challenges in applying AR to increasing users' situational awareness.

Children are being presented with augmented reality (AR) in different contexts, such as education and gaming. However, little is known about how children conceptualize AR, especially AR headsets. Prior work has shown that children's interaction behaviors and expectations of technological devices can be quite different from adults’. It is important to understand children's mental models of AR headsets to design more effective experiences for them. To elicit children's perceptions, we conducted four participatory design sessions with ten children on designing content for imaginary AR headsets. We found that children expect AR systems to be highly intelligent and to recognize and virtually transform surroundings to create immersive environments. Also, children are in favor of using these devices for difficult tasks but prefer to work on their own for easy tasks. Our work contributes new understanding on how children comprehend AR headsets and provides recommendations for designing future headsets for children.

Mode switching allows applications to support a wide range of operations (e.g. selection, manipulation, and navigation) using a limited input space. While the performance of different mode switching techniques has been extensively examined for pen- and touch-based interfaces, investigating mode switching in augmented reality (AR) is still relatively new. Prior work found that using non-preferred hand is an efficient mode switching technique in AR. However, it is unclear how the technique performs when increasing the number of modes, which is more indicative of real-world applications. Therefore, we examined the scalability of non-preferred hand mode switching in AR with two, four, six, and eight modes. We found that as the number of modes increase, performance plateaus after the four-mode condition. We also found that counting gestures have varying effects on mode switching performance in AR. Our findings suggest that modeling mode switching performance in AR is more complex than simply counting the number of available modes. Our work lays a foundation for understanding the costs associated with scaling interaction techniques in AR.

Fitts' law has accurately modeled both children's and adults' pointing movements, but it is not as precise for modeling movement to small targets. To address this issue, prior work presented FFitts' law, which is more exact than Fitts' law for modeling adults' finger input on touchscreens. Since children's touch interactions are more variable than adults, it is unclear if FFitts' law should be applied to children. We conducted a 2D target acquisition task with 54 children (ages 5-10) to examine if FFitts' law can accurately model children's touchscreen movement time. We found that Fitts' law using nominal target widths is more accurate, with a R2 value of 0.93, than FFitts' law for modeling children's finger input on touchscreens. Our work contributes new understanding of how to accurately predict children's finger touch performance on touchscreens.

Augmented Reality (AR) headsets are being employed in industrial settings (e.g., the oil industry); however, there has been little work on how information should be presented in these headsets, especially in the context of situational awareness. We present a study examining three different presentation styles (Display, Environment, Mixed Environment) for textual secondary information in AR headsets. We found that the Display and Environment presentation styles assisted in perception and comprehension. Our work contributes a first step to understanding how to design visual information in AR headsets to support situational awareness.

Classification accuracy of whole-body gestures can be improved by selecting gestures that have few conflicts (i.e., confusions or misclassifications). To identify such gestures, an understanding of the nuances of how users articulate whole-body gestures can help, especially when conflicts may be due to confusion among seemingly dissimilar gestures. To the best of our knowledge, such an understanding is currently missing in the literature. As a first step to enable this understanding, we designed a method that facilitates investigation of variations in how users move their body parts as they perform a motion. This method, which we call filterJoint, selects the key body parts that are actively moving during the performance of a motion. The paths along which these body parts move in space over time can then be analyzed to make inferences about how users articulate whole-body gestures. We present two case studies to show how the filterJoint method enables a deeper understanding of whole-body gesture articulation, and we highlight implications for the selection of whole-body gesture sets as a result of these insights.

Prior work has shown that intelligent user interfaces (IUIs) that use modalities such as speech, gesture, and writing pose challenges for children due to their developing cognitive and motor skills. Research has focused on improving recognition and accuracy by accommodating children's specific interaction behaviors. Understanding children's expectations of IUIs is also important to decrease the impact of recognition errors that occur. To understand children's conceptual model of IUIs, we completed four consecutive participatory design sessions on designing IUIs with an emphasis on error detection and correction. We found that, while children think of interactive systems in terms of both user input and behavior and system output and behavior, they also propose ideas that require advanced system intelligence, e.g., context and conversation. Our work contributes new understanding of how children conceptualize IUIs and new methods for error detection and correction, and will inform the design of future IUIs for children to improve their experience.

Virtual humans are used to facilitate interactions in sensitive contexts such as healthcare. In such contexts, trust in the information source plays an important role in reception of the information. Prior work has shown that physical appearance affects trustworthiness in human-human interactions; therefore, we examined the effect of virtual human's appearance on users' trust. We ran a between-users study with 12 adult participants, who watched a video of a virtual human with professional attire (e.g., lab coat) or with general attire (e.g., button-down shirt). We examined the duration of eye fixation on the virtual human's face along with participants' self-reported trust levels. We found that there was no statistical difference in eye contact or trust between the two test conditions.

Prior work has shown that children exhibit negative collaborative behaviors, such as blocking others' access to objects, when collaborating on interactive tabletop computers. We implemented previous design recommendations, namely separate physical territories and activity roles, which had been recommended to decrease these negative collaborative behaviors. We developed a multi-touch "I-Spy" picture searching application with separate territory partitions and activity roles. We conducted a deep qualitative analysis of how six pairs of children, ages 6 to 10, interacted with the application. Our analysis revealed that the collaboration styles differed for each pair, both in regards to the interaction with the task and with each other. Several pairs exhibited negative physical and verbal collaborative behaviors, such as nudging each other out of the way. Based on our analysis, we suggest that it is important for a collaborative task to offer equal opportunities for interaction, but it may not be necessary to strive for complete equity of collaboration. We examine the applicability of prior design guidelines and suggest open questions for future research to inform the design of tabletop applications to support collaboration for children.

Fully autonomous vehicles, commonly referred to as self-driving vehicles, are an emerging technology that may hold tremendous mobility potential for individuals who are blind or visually impaired who have been previously disadvantaged by an inability to operate conventional motor vehicles. This study explores the opinions of 38 participants who are blind and low vision, through the use of focus group methodology, regarding this emerging self-driving vehicle technology. Participants were overwhelmingly optimistic about the potential for independence and mobility that self-driving vehicles may provide but were concerned that the needs of individuals with visual impairments were not being adequately considered in the development of the technology. Participants also raised questions about how the technology would satisfy their need for situational awareness, how the technology would enable blind or visually impaired operators to verify their arrival at their desired location and a host of issues related to parking, vehicle location and roadside assistance. Participants also expressed a preference for smartphone and speech input capabilities as a primary means of system interaction. These findings suggest that at a minimum more needs to be done to engage individuals with visual impairments in the development of self-driving vehicle technology and to increase awareness of manufacturer efforts.

The proliferation of smartphones and tablets has increased children’s access to and usage of touchscreen devices. Prior work on smartphones has shown that children’s touch interactions differ from adults’. However, larger screen devices like tablets and tabletops have not been studied at the same granularity for children as smaller devices. We present two studies: one of 13 children using tablets with pen and touch, and one of 18 children using a touchscreen tabletop device. Participants completed target touching and gesture drawing tasks. We found significant differences in performance by modality for tablet: children responded faster and slipped less with touch than pen. In the tabletop study, children responded more accurately to changing target locations (fewer holdovers), and were more accurate touching targets around the screen. Gesture recognition rates were consistent across devices. We provide design guidelines for children’s touchscreen interactions across screen sizes to inform the design of future touchscreen applications for children.

No abstract available.

Most touchscreen devices are not designed specifically with children in mind, and their interfaces often do not optimize interaction for children. Prior work on children and touchscreen interaction has found important patterns, but has only focused on simplified, isolated interactions, whereas most interfaces are more visually complex. We examine how interface complexity might impact children's touchscreen interactions. We collected touch and gesture data from 30 adults and 30 children (ages 5 to 10) to look for similarities, differences, and effects of interface complexity. Interface complexity affected some touch interactions, primarily related to visual salience, and it did not affect gesture recognition. We also report general differences between children and adults. We provide design recommendations that support the design of touchscreen interfaces specifically tailored towards children of this age.

Artists and animators have observed that children’s movements are quite different from adults performing the same action. Previous computer graphics research on human motion has primarily focused on adult motion. There are open questions as to how different child motion actually is, and whether the differences will actually impact animation and interaction. We report the first explicit study of the perception of child motion (ages 5 to 9 years old), compared to analogous adult motion. We used markerless motion capture to collect an exploratory corpus of child and adult motion, and conducted a perceptual study with point light displays to discover whether naive viewers could identify a motion as belonging to a child or an adult. We find that people are generally successful at this task. This work has implications for creating more engaging and realistic avatars for games, online social media, and animated videos and movies.