“Technically speaking I’m at the top of the hierarchy”: How System Administrators Think About PowerSystem administrators (sysadmins) hold considerable organizational power by controlling access, enforcing or bypassing security, and mediating between users and systems. Previous research on sysadmins highlighted their technical practices, collaboration, update behavior, and misconfigurations, but rarely addressed questions of power, responsibility, and ethics within organizations. We surveyed 262 sysadmins from various countries and professional backgrounds on perceptions of power, morality, oversight, and insider threats. Sysadmins defined their power mainly through specific skills and their perceived irreplaceability, less in terms of destructive potential. Access rights played a role, but more important were how others---such as superiors---perceived them and their skills, as well as their actual decision-making authority. Demographic factors were largely irrelevant, though women were less confident than men when self-assessing their skills and power regarding their profession. Logging, dynamic privileges, and guidelines were not seen as restrictive. Sysadmins described facing ethical dilemmas and relying on their personal moral compass to work through them.2026LWLydia Weinberger et al.Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)Explainable AI (XAI)Privacy by Design & User ControlPrivacy Perception & Decision-MakingCHI
Leveraging Learner Errors in Digital Argumentation Learning: How ALure Helps Students Learn from their Mistakes and Write Better ArgumentsProviding argumentation feedback is considered helpful for students preparing to work in collaborative environments, helping them with writing higher-quality argumentative texts. Domain-independent natural language processing (NLP) methods, such as generative models, can utilize learner errors and fallacies in argumentation learning to help students write better argumentative texts. To test this, we collect design requirements, and then design and implement two different versions of our system called ALure to improve the students’ argumentation skills. We test how ALure helps students learn argumentation in a university lecture with 305 students and compare the learning gains of the two versions of ALure with a control group using video tutoring. We find and discuss the differences of learning gains in argument structure and fallacies in both groups after using ALure, as well as the control group. Our results shed light on the applicability of computer-supported systems using recent advances in NLP to help students in learning argumentation as a necessary skill for collaborative working settings.2025SNSeyed Parsa Neshaei et al.Fighting Misinformation, Building BelievabilityCSCW
Gamified Physical Activity App for Students at Universities: Results of Five Development LoopsThere is substantial evidence that young adults aren't exercising enough, which harms their health. Although occupational health services for students are expanding, they're often not used due to time, motivation, and accessibility constraints. Research has demonstrated that gamification and mobile solutions can effectively address these challenges. In light of these, we have developed a gamified mobile application, comprising various game levels and components, which was refined through successive design iterations. This article illustrates the steps in the game development process that have led to the greatest advances in user-friendliness and determines which optimizations achieve a top rating. The analysis was conducted after each game round, with the game elements optimized for the target audience. The results of the study, derived from four iterative design loops with N = 455 participants, are empirically proven and provide actionable recommendations for the efficient development of mobile health applications.2025JMJulia Müller et al.Serious & Functional GamesGamification DesignFitness Tracking & Physical Activity MonitoringMobileHCI
Pixel Memories: Do Lifelog Summaries Fail to Enhance Memory but Offer Privacy-Aware Memory Assessments?We explore the metaphorical "daily memory pill" concept – a brief pictorial lifelog recap aimed at reviving and preserving memories. Leveraging psychological strategies, we explore the potential of such summaries to boost autobiographical memory. We developed an automated lifelogging memory prosthesis and a research protocol (Automated Memory Validation ``AMV'') for conducting privacy-aware, in-situ evaluations. We conducted a real-world lifelogging experiment for a month (n=11). We also designed a browser ``Pixel Memories’’ for browsing one-week worth of lifelogs. The results suggest that daily timelapse summaries, while not yielding significant memory augmentation effects, also do not lead to memory degradation. Participants' confidence in recalled content remains unaltered, but the study highlights the challenge of users' overestimation of memory accuracy. Our core contributions, the AMV protocol and "Pixel Memories" browser, advance our understanding of memory augmentations and offer a privacy-preserving method for evaluating future ubicomp systems.2025PEPassant ElAgroudy et al.German Research Centre for Artificial Intelligence (DFKI); RPTU KaiserslauternContext-Aware ComputingUbiquitous ComputingCHI
Driving Simulation for Energy Efficiency Studies: Analyzing Electric Vehicle Eco-Driving With EcoSimLab and the EcoDrivingTestParkDriving simulators often lack fundamental components needed for accurate simulation of energy dynamics. We introduce EcoSimLab, a comprehensive electric vehicle driving simulation framework consisting of (1) a simulation of electric vehicle energy dynamics, (2) an optimization-based approach of structuring eco-driving behaviors, (3) a synthetic driver module as versatile benchmark model to analyze human behavior. Guided by fundamentals of energy modeling and considerations on human action regulation, we further present the development of the EcoDrivingTestPark, an exemplary set of energy-relevant scenarios to enable the analysis of individual differences in eco-driving and intervention effects (e.g., HMIs). To generate a first characterization of driving behavior, we conducted two empirical studies with human (𝑁S1 = 31, 𝑁S2a = 41) and synthetic drivers (𝑁S2b = 3). Results indicate substantial variations in driver behavior and considerable challenges for human drivers to achieve synthetic driver performance. Implications for augmenting human action regulation in eco-driving are discussed.2024MGMarkus Gödker et al.EV Charging & Eco-Driving InterfacesAutoUI
Impact of Privacy Protection Methods of Lifelogs on Remembered Memories Lifelogging is traditionally used for memory augmentation. However, recent research shows that users' trust in the completeness and accuracy of lifelogs might skew their memories. Privacy-protection alterations such as body blurring and content deletion are commonly applied to photos to circumvent capturing sensitive information. However, their impact on how users remember memories remain unclear. To this end, we conduct a white-hat memory attack and report on an iterative experiment (N=21) to compare the impact of viewing 1) unaltered lifelogs, 2) blurred lifelogs, and 3) a subset of the lifelogs after deleting private ones, on confidently remembering memories. Findings indicate that all the privacy methods impact memories' quality similarly and that users tend to change their answers in recognition more than recall scenarios. Results also show that users have high confidence in their remembered content across all privacy methods. Our work raises awareness about the mindful designing of technological interventions.2023PEPassant ElAgroudy et al.German Research Centre for Artificial Intelligence (DFKI), LMU MunichPrivacy by Design & User ControlPrivacy Perception & Decision-MakingCHI
The Energy Interface Challenge. Towards Designing Effective Energy Efficiency Interfaces for Electric Vehicles.The design of effective energy interfaces for electric vehicles needs an integrated perspective on the technical and psychological factors that together establish real-world vehicle energy efficiency. The objective of the present research was to provide a transdisciplinary synthesis of key factors for the design of energy interfaces for battery electric vehicles (BEVs) that effectively support drivers in their eco-driving efforts. While previous research tends to concentrate on the (visual) representation of common energy efficiency measures, we focus on the design of action-integrated metrics and indicators for vehicle energy efficiency that account for the perceptual capacities and bounded rationality of drivers. Based on this rationale, we propose energy interface examples for the most basic driving maneuvers (acceleration, constant driving, deceleration) and discuss challenges and opportunities of these design solutions.2019TFThomas Franke et al.EV Charging & Eco-Driving InterfacesAutoUI
Insert Needle Here! A Custom Display for Optimized Biopsy Needle PlacementNeedle-guiding templates are used for a variety of minimally invasive medical interventions. While physically supporting needle placement with a grid of holes, they lack integrated information where needles need to be inserted. Physicians must manually determine the correct holes based on the output of planning software - a workflow that is error-prone and lengthy. We address these issues by embedding a display into the template using electroluminescence (EL) screen printing. The EL display is connected to planning software and illuminates the correct hole. In an empirical evaluation with physicians and researchers from the medical domain, we compare the illuminated against the conventional template as used in magnetic resonance imaging (MRI) guided prostate biopsies. Our results show that the EL display significantly improves task completion time by 51 %, task load by 47 % and usability by 30 %.2018ARAnke Verena Reinschluessel et al.University of BremenFitness Tracking & Physical Activity MonitoringSurgical Assistance & Medical TrainingCHI