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Usability und User Experience (UX) haben als Design-Aspekte in der Produktentwicklung zunehmend an Bedeutung gewonnen. Daher ist es sinnvoll, die organisationale Kompetenz zur Entwicklung von Produkten mit einer positiven UX zu stärken. Veränderungen in Organisationen sind jedoch mit großem Aufwand verbunden. Deshalb müssen Organisationen entscheiden, welche Aktivitäten zur Veränderung der eigenen Kompetenz durchgeführt werden sollen und welche nicht. Die bisherige Forschung hat sich weitgehend auf die Anwendbarkeit bestimmter Methoden im Projekt- und Produktkontext konzentriert. Um geeignete Aktivitäten zur Verbesserung der organisationalen UX-Kompetenz zu identifizieren, wurden 17 UX-Professionals befragt. Diese UX-Professionals haben mindestens zehn Jahre Erfahrung durch die Arbeit in mehreren Unternehmen und durch die Übernahme einer Führungsrolle im Bereich UX gesammelt. Aus diesen Interviews wurden 13 mögliche Maßnahmen zur Steigerung der UX-Kompetenz von Organisationen abgeleitet. Dazu gehören beispielsweise die Erhöhung der Kompetenz einzelner Mitarbeiter, das Teilen von UX-Erfolgsgeschichten oder das Ermöglichen von User Research.
This paper introduces FaceHaptics, a novel haptic display based on a robot arm attached to a head-mounted virtual reality display. It provides localized, multi-directional and movable haptic cues in the form of wind, warmth, moving and single-point touch events and water spray to dedicated parts of the face not covered by the head-mounted display.The easily extensible system, however, can principally mount any type of compact haptic actuator or object. User study 1 showed that users appreciate the directional resolution of cues, and can judge wind direction well, especially when they move their head and wind direction is adjusted dynamically to compensate for head rotations. Study 2 showed that adding FaceHaptics cues to a VR walkthrough can significantly improve user experience, presence, and emotional responses.
Risk-based Authentication (RBA) is an adaptive security measure that improves the security of password-based authentication by protecting against credential stuffing, password guessing, or phishing attacks. RBA monitors extra features during login and requests for an additional authentication step if the observed feature values deviate from the usual ones in the login history. In state-of-the-art RBA re-authentication deployments, users receive an email with a numerical code in its body, which must be entered on the online service. Although this procedure has a major impact on RBA's time exposure and usability, these aspects were not studied so far.
We introduce two RBA re-authentication variants supplementing the de facto standard with a link-based and another code-based approach. Then, we present the results of a between-group study (N=592) to evaluate these three approaches. Our observations show with significant results that there is potential to speed up the RBA re-authentication process without reducing neither its security properties nor its security perception. The link-based re-authentication via "magic links", however, makes users significantly more anxious than the code-based approaches when perceived for the first time. Our evaluations underline the fact that RBA re-authentication is not a uniform procedure. We summarize our findings and provide recommendations.
Risk-based Authentication (RBA) is an adaptive security measure to strengthen password-based authentication. RBA monitors additional features during login, and when observed feature values differ significantly from previously seen ones, users have to provide additional authentication factors such as a verification code. RBA has the potential to offer more usable authentication, but the usability and the security perceptions of RBA are not studied well.
We present the results of a between-group lab study (n=65) to evaluate usability and security perceptions of two RBA variants, one 2FA variant, and password-only authentication. Our study shows with significant results that RBA is considered to be more usable than the studied 2FA variants, while it is perceived as more secure than password-only authentication in general and comparably secure to 2FA in a variety of application types. We also observed RBA usability problems and provide recommendations for mitigation. Our contribution provides a first deeper understanding of the users' perception of RBA and helps to improve RBA implementations for a broader user acceptance.
Exploring Future Work - Co-Designing a Human-robot Collaboration Environment for Service Domains
(2020)
There has been increasing interest in the application of humanoid robots in service domains like retail or care homes in recent years. Here, most use cases focus on serving customer needs autonomously. Frequently, human intervention becomes necessary to support the robot in exceptional situations. However, direct intervention of service operators is often not possible and requires specialized personnel. In a co-design process with 13 service operators from a pharmacy, we designed a remote working environment for human-robot collaboration that enables first-time experiences and collaboration with robots. Five participants took part in an assessment study and reported on their experiences about the utility, usability and user experience. Results show that participants were able to control and train the robot through the remote control environment. We discuss implications of our results for future work in service domains and emphasize a shift of focus from full robot automatization to human-robot collaboration forms.
There has been increasing interest in designing for dementia in recent years. Empirical investigation is now needed of the long-term role of caregivers in appropriating ICTs into the complex daily life of people with dementia (PwD). We present here the outcomes of a 4-month evaluation of the individual, social and institutional impact of a videogame-based training system. The everyday behavior and interactions of 52 PwD and 25 caregivers was studied qualitatively, focusing on the role played by caregivers in integrating the system into daily routines. Our results indicate that the successful appropriation of ICT for PwD depends partly on the physical, cognitive and social benefits for PwD, but especially on the added value perceived by their social care-network. We discuss the need for design in dementia to develop more socially embedded innovations that can address the social actors involved and thus contribute to practical solutions for professional and private care.
This paper presents groupware to study group behavior while conducting a creative task on large, high-resolution displays. Moreover, we present the results of a between-subjects study. In the study, 12 groups with two participants each prototyped a 2D level on a 7m x 2.5m large, high-resolution display using tablet-PCs for interaction. Six groups underwent a condition where group members had equal roles and interaction possibilities. Another six groups worked in a condition where group members had different roles: level designer and 2D artist. The results revealed that in the different roles condition, the participants worked significantly more tightly and created more assets. We could also detect some shortcomings for that configuration. We discuss the gained insights regarding system configuration, groupware interfaces, and groups behavior.
Gone But Not Forgotten: Evaluating Performance and Scalability of Real-Time Mesoscopic Agents
(2020)
This work presents the development of a measuring system for the quality control of ultrapure water. The new systems combines ozonation and UV radiation for the oxidation of organic substances. The change in conductivity caused by the oxidation is furthermore correlated with the TOC of the solution.
Evaluation of a Multi-Layer 2.5D display in comparison to conventional 3D stereoscopic glasses
(2020)
In this paper we propose and evaluate a custom-build projection-based multilayer 2.5D display, consisting of three layers of images, and compare performance to a stereoscopic 3D display. Stereoscopic vision can increase the involvement and enhance game experience, however may induce possible side effects, e.g. motion sickness and simulator sickness. To overcome the disadvantage of multiple discrete depths, in our system perspective rendering and head-tracking is used. A study was performed to evaluate this display with 20 participants playing custom-designed games. The results indicated that the multi-layer display caused fewer side effects than the stereoscopic display and provided good usability. The participants also stated a better or equal spatial perception, while the cognitive load stayed the same.
Compliant manipulation is a crucial skill for robots when they are supposed to act as helping hands in everyday household tasks. Still, nowadays, those skills are hand-crafted by experts which frequently requires labor-intensive, manual parameter tuning. Moreover, some tasks are too complex to be specified fully using a task specification. Learning these skills, by contrast, requires a high number of costly and potentially unsafe interactions with the environment. We present a compliant manipulation approach using reinforcement learning guided by the Task Frame Formalism, a task specification method. This allows us to specify the easy to model knowledge about a task while the robot learns the unmodeled components by reinforcement learning. We evaluate the approach by performing a compliant manipulation task with a KUKA LWR 4+ manipulator. The robot was able to learn force control policies directly on the robot without using any simulation.
Long-term variability of solar irradiance and its implications for photovoltaic power in West Africa
(2020)
West Africa is one of the least developed regions in the world regarding the energy availability and energy security. Located close to the equator West Africa receives high amounts of global horizontal irradiance (GHI). Thus, solar power and especially photovoltaic (PV) systems seem to be a promising solution to provide electricity with low environmental impact. To plan and to dimension a PV power system climatological data for global horizontal irradiance (GHI) and its variability need to be taken into account. However, ground based measurements of irradiances are not available continuously and cover only a few discrete locations.
When a robotic agent experiences a failure while acting in the world, it should be possible to discover why that failure has occurred, namely to diagnose the failure. In this paper, we argue that the diagnosability of robot actions, at least in a classical sense, is a feature that cannot be taken for granted since it strongly depends on the underlying action representation. We specifically define criteria that determine the diagnosability of robot actions. The diagnosability question is then analysed in the context of a handle manipulation action, such that we discuss two different representations of the action – a composite policy with a learned success model for the action parameters, and a neural network-based monolithic policy – both of which exist on different sides of the diagnosability spectrum. Through this comparison, we conclude that composite actions are more suited to explicit diagnosis, but representations with less prior knowledge are more flexible. This suggests that model learning may provide balance between flexibility and diagnosability; however, data-driven diagnosis methods also need to be enhanced in order to deal with the complexity of modern robots.
Autonomous driving enables new mobility concepts such as shared-autonomous services. Although significant re-search has been done on passenger-car interaction, work on passenger interaction with robo-taxis is still rare. In this paper, we tackle the question of how passengers experience robo-taxis as a service in real-life settings to inform the interaction design. We conducted a Wizard of Oz study with an electric vehicle where the driver was hidden from the passenger to simulate the service experience of a robo-taxi. 10 participants had the opportunity to use the simulated shared-autonomous service in real-life situations for one week. By the week's end, 33 rides were completed and recorded on video. Also, we flanked the study conducting interviews before and after with all participants. The findings provided insights into four design themes that could inform the service design of robo-taxis along the different stages including hailing, pick-up, travel, and drop-off.
Bei der sechsten Ausgabe des wissenschaftlichen Workshops ”Usable Security und Privacy” auf der Mensch und Computer 2020 werden wie in den vergangenen Jahren aktuelle Forschungs- und Praxisbeiträge präsentiert und anschließend mit allen Teilnehmenden diskutiert. Drei Beiträge befassen sich dieses Jahr mit dem Thema Privatsphäre, einer mit dem Thema Sicherheit. Mit dem Workshop wird ein etabliertes Forum fortgeführt und weiterentwickelt, in dem sich Expert*innen aus unterschiedlichen Domänen, z. B. dem Usability- und Security-Engineering, transdisziplinär austauschen können.
Efficient and comprehensive assessment of students knowledge is an imperative task in any learning process. Short answer grading is one of the most successful methods in assessing the knowledge of students. Many supervised learning and deep learning approaches have been used to automate the task of short answer grading in the past. We investigate why assistive grading with active learning would be the next logical step in this task as there is no absolute ground truth answer for any question and the task is very subjective in nature. We present a fast and easy method to harness the power of active learning and natural language processing in assisting the task of grading short answer questions. A webbased GUI is designed and implemented to incorporate an interactive short answer grading system. The experiments show that active learning saves the time and effort of graders in assessment and reaches the performance of supervised learning with less amount of graded answers for training.
Telepresence robots allow people to participate in remote spaces, yet they can be difficult to manoeuvre with people and obstacles around. We designed a haptic-feedback system called “FeetBack," which users place their feet in when driving a telepresence robot. When the robot approaches people or obstacles, haptic proximity and collision feedback are provided on the respective sides of the feet, helping inform users about events that are hard to notice through the robot’s camera views. We conducted two studies: one to explore the usage of FeetBack in virtual environments, another focused on real environments.We found that FeetBack can increase spatial presence in simple virtual environments. Users valued the feedback to adjust their behaviour in both types of environments, though it was sometimes too frequent or unneeded for certain situations after a period of time. These results point to the value of foot-based haptic feedback for telepresence robot systems, while also the need to design context-sensitive haptic feedback.
Computers can help us to trigger our intuition about how to solve a problem. But how does a computer take into account what a user wants and update these triggers? User preferences are hard to model as they are by nature vague, depend on the user’s background and are not always deterministic, changing depending on the context and process under which they were established. We pose that the process of preference discovery should be the object of interest in computer aided design or ideation. The process should be transparent, informative, interactive and intuitive. We formulate Hyper-Pref, a cyclic co-creative process between human and computer, which triggers the user’s intuition about what is possible and is updated according to what the user wants based on their decisions. We combine quality diversity algorithms, a divergent optimization method that can produce many, diverse solutions, with variational autoencoders to both model that diversity as well as the user’s preferences, discovering the preference hypervolume within large search spaces.