惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Y
Y Combinator Blog
S
SegmentFault 最新的问题
WordPress大学
WordPress大学
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
美团技术团队
博客园 - 叶小钗
大猫的无限游戏
大猫的无限游戏
罗磊的独立博客
Hugging Face - Blog
Hugging Face - Blog
博客园 - 司徒正美
小众软件
小众软件
博客园 - 聂微东
阮一峰的网络日志
阮一峰的网络日志
博客园 - 三生石上(FineUI控件)
月光博客
月光博客
The Cloudflare Blog
T
Tailwind CSS Blog
博客园 - 【当耐特】
Jina AI
Jina AI
量子位
有赞技术团队
有赞技术团队
博客园 - Franky
V
Visual Studio Blog
V
V2EX

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
Don't Leave Me Alone: Retrospective Think Aloud supported...
Alexandros Liapis, Christos Katsanos, Michalis Xenos · 2018-02-12 · via cs.HC updates on arXiv.org

Think aloud protocols are widely applied in user experience studies. In this paper, the effect of two different applications of the Retrospective Think Aloud (RTA) protocol on the number of user-reported usability issues is examined. To this end, 30 users were asked to use the National Cadastre and Mapping Agency web application and complete a set of tasks, such as measuring the land area of a square in their hometown. The order of tasks was randomized per participant. Next, participants were involved in RTA sessions. Each participant was involved in two different RTA modes: (a) the strict guidance, in which the facilitator stayed in the background and prompted participants to keep thinking aloud based on his judgement and experience, and (b) the physiology-supported interventions, in which the facilitator intervened based on real-time monitoring of user's physiological signals. During each session, three participant's physiological signals were recorded: skin conductance, skin temperature and blood volume pulse. Participants were also asked to provide valence-arousal ratings for each self-reported usability issue. Analysis of the collected data showed that participants in the physiology-supported RTA mode reported significantly more usability issues. No significant effect of the RTA mode was found on the va-lence-arousal ratings for the reported usability issues. Participants' physiological signals during the RTA sessions did not also differ significantly between the two modes.