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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
Mapping Executive Function Tasks for Children: A Scoping ...
Matheus Rodrigues Felizardo, Nuno Miguel Feixa Rodrigues, Antóni · 2025-03-28 · via cs.HC updates on arXiv.org

Background: Executive functions (EFs) are cognitive processes essential for controlling impulses, staying focused, thinking before acting, and managing information. Childhood is a critical period for EF development, but there is a lack of standardized tools that combine EF tasks with physical activity in a gamified approach. Objectives: This scoping review maps EF tasks for children, identifies common strategies, and explores methods for measuring outcomes, providing a foundation for a research-oriented platform to assess EF development. Design: A systematic search was conducted in SCOPUS, ScienceDirect, and ERIC databases with the query "executive function task" AND (children OR child OR childhood). Inclusion criteria were studies published between 2019 and 2024 in English, with participants aged 5 to 9 years. Data extracted included task details, scoring mechanisms, and stop conditions. Studies lacking clear methodological descriptions were excluded. Results: A total of 2044 articles were identified, with 113 duplicates removed. After selection, 23 studies met the inclusion criteria. The identified tasks are listed in Table 2. Key tasks, strategies, and measurement methodologies were highlighted. Conclusions: Integrating EF tasks into a structured platform offers a promising approach to standardize assessments, fill research gaps, and provide a reliable tool for studying EF development in children. Keywords: Executive Functions, Inhibition, Working Memory, Cognitive Flexibility, Task Design, Standardization