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cs.HC updates on arXiv.org

Quantitative Movement Testing: Measuring Patient Movements from a Single Smartphone Video Vision-Language Models Suppress Female Representations Under Ambiguous Input The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplace TUX: Measuring Human--AI Tacit Understanding LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback VideoFDB: Evaluating Full-Duplex Vision-Speech Capabilities in Conversational Agents Label Over Logic? How Source Cues Bias Human Fallacy Judgments More Than LLMs Inform, Coach, Relate, Listen: Auditing LLM Caregiving Support Roles How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality Analyzing Persona Effects in Generated Explanations from Multimodal LLM Agents in Urban Perception First head-to-head comparison of agentic AI applied to the analysis of simulated data of the Einstein Telescope Granuscore: A Reference-Free Measure of Granularity for Text Analysis and Question Answering The Timing Dependencies of Trust: Speed, Accuracy, and cBCI Neuro-Decoupling in Human-AI Teams Bayesian Distributional Models of Executive Functioning Visual Matters: Connecting Aesthetic Appeal and Production Quality of Photos, Infographics and Data Visualizations to Credibility of Social Media Posts Data-driven Head Motion Generation through Natural Gaze-Head Coordination Agreement Metrics for LLM-as-Judge Evaluation: What to Report and Why Perceptually Lossless Tactile Texture Synthesis with Compact Spectral Envelope Models MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data CogAdapt: Transferring Clinical ECG Foundation Models to Wearable Cognitive Load Assessment via Lead Adaptation Augmented Analytics and Decision Quality: The Role of Trust among Non-Technical BI Users Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build PaintCopilot: Modeling Painting as Autonomous Artistic Continuation Personality Engineering with AI Agents: A New Methodology for Negotiation Research PULSE: Agentic Investigation with Passive Sensing for Proactive Intervention in Cancer Survivorship Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education Conversations in Space: Structuring Non-Linear LLM Interactions on a Canvas MAPLE: Self-Supervised Learning-Enhanced Nonlinear Dimensionality Reduction for Visual Analysis nASR: An End-to-End Trainable Neural Layer for Channel-Level EEG Artifact Subspace Reconstruction in Real-Time BCI
The Developers' Design Thinking Toolbox in Hackathons: A ...
Kiev Gama, George Valença, Pedro Alessio, Rafael Formiga, André · 2022-06-10 · via cs.HC updates on arXiv.org

Hackathons are time-bounded collaborative events of intense teamwork to build prototypes usually in the form of software, aiming to specific challenges proposed by the organizers. These events became a widespread practice in the IT industry, universities and many other scenarios, as a result of a growing open-innovation trend in the last decade. Since the main deliverable of these events is a demonstrable version of an idea, such as early hardware or software prototypes, the short time frame requires participants to quickly understand the proposed challenge or even identify issues related to a given domain. To create solutions, teams follow an ad-hoc but effective design approach, that many times seems informal since the background of the participants is rather centered on technical aspects (e.g., web and mobile programming) and does not involve any training in Design Thinking. To understand this creative process, we conducted 37 interviews (32 hackathons winners and 5 hackathon organizers) with people from 16 countries. We aimed to identify the design processes and recurring design methods applied by winners in these events. Also, we conducted a focus group with 8 people experienced in hackathons (participants and organizers) to discuss our findings. Our analysis revealed that although hackathon winners with IT background have no formal training on Design Thinking, they are aware of many design methods, typically following a sequence of phases that involve divergent and convergent thinking to explore the problem space and propose alternatives in a solution space, which is the rationale behind Design Thinking. We derived a set of recommendations based on design strategies that seem to lead to successful hackathon participation. These recommendations can also be useful to organizers who intend to enhance the experience of newcomers in hackathons.