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We report a detailed autoethnographic case study of a single-subject who deliberately constructed and operated a multi-modal prompt-engineering system (System A) designed to externalize cognitive self-regulation onto a large language model…
AI agents are increasingly active on social media platforms, generating content and interacting with one another at scale. Yet the behavioral diversity of these agents remains poorly understood, and methods for characterizing distinct agent…
This paper introduces the GO-DRiVeS application, an on demand ride sharing and requesting mobile application tailored specifically to save long walks and challenges which are time consuming and tiring especially during hot days or when…
Incorporating natural language input has the potential to improve the capabilities of biomedical data discovery interfaces. However, user interface elements and visualizations are still powerful tools for interacting with data. In our…
Studies have indicated that personality is related to achievement, and several personality assessment models have been developed. However, most are either questionnaires or based on marker systems, which entails limitations. We proposed a…
Bioscientists frequently seek to visualize the biological systems they have empirically characterized and reported in the literature. Realizing such visualizations requires biological structure modeling, an inherently complex process that…
Asynchronous data-driven explanations often fail because the content and presentation are not tailored to the target audience, and they provide limited opportunities for active audience engagement. We present a vision for Contextualized…
Large language models (LLMs) are increasingly used as collaborative assistants, yet dominant NLP evaluation practices remain centered on aggregate metrics such as accuracy and fluency. These approaches often overlook behaviors that are…
Deploying human activity recognition (HAR) at home is still rare because sensor signals vary wildly across houses, people, and time, essentially requiring in-situ data collection and training. Prior approaches use cameras to generate…
Designers of digital solutions increasingly consult Large Language Models (LLMs) for their work. However, it remains unclear how this may affect the user experiences they produce and there are no established practices. We investigate how…
Synthetic participants represent a methodologically concerning concept that threatens the integrity of UX research. Findings from previous experiments specify how AI outputs are misaligned with the behaviors and thoughts of real humans in…
MEEDAV is an open-source web-based application for the synchronised visualisation of electroencephalography (EEG), eye-tracking, and audio data collected in psycholinguistic research. While originally developed for the Eyetracked…
Vehicle platooning enables close-gap driving and offers potential benefits for traffic efficiency and safety. In conditionally automated platooning, drivers remain responsible for supervising the system and intervening when necessary,…
Trust calibration -- aligning user trust judgment with model capability -- is crucial for safe deployment of explainable AI (XAI), yet is often evaluated via global trust ratings detached from objective performance evidence. We present a…
Electronic waste (e-waste) is one of the fastest-growing waste streams worldwide due to rapid technological advancements and shorter device lifespans. Improper disposal releases hazardous substances that harm the environment and human…
Generative AI creates new opportunities for programming education, but many existing systems remain overly directive, producing lengthy explanations and premature solutions that can overwhelm K-12 novices. In this paper, we present a…
Motivation to perform movement therapy and caregiver burnout are major challenges to post-stroke life. Serious games have been shown to support therapeutic tasks in people with stroke, but there are few activities that simultaneously…
Cancer survivors face elevated rates of depression, anxiety, and general emotional distress, yet the precise moments they most need support are often the moments when self-report is sparse, a phenomenon we term the diary paradox. Passive…
Understanding mobile user interfaces is important for building intelligent systems such as automation tools, accessibility solutions, and UI-aware agents. However, progress in this area is still limited by the lack of high-quality datasets…
Asynchronous video learning, including massive open online courses (MOOCs), offers flexibility but often lacks students' affective engagement. This study examines how teachers' verbal and nonverbal vocal emotive expressions influence…