Intention-use gaps and displacement of valued activities predict social media regret more strongly than duration, with pre-session context generalizing across users and physiological signals adding person-specific predictive power.
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WhatIf provides an interactive platform for real-time exploration of LLM-driven social simulations, enabling policymakers to iteratively test plans, reflect on assumptions, and uncover vulnerabilities in emergency preparedness scenarios.
SoulNote enables multi-session GenAI songwriting for DHH users, producing measurable gains in self-insight, emotion regulation, and self-care attitudes.
Open-ended preference data reveals substantial plurality in what people want from AI and divergent interpretations of shared values such as truthfulness.
A participatory red-teaming project in the Global South created the PLACES dataset of 26k T2I failure examples that reveal unique cultural and linguistic harms missed by existing safety frameworks.
Users entangle their lived experiences with AI predictions in menstrual tracking apps, leading to self-fulfilling prophecies, limited critical awareness from UI, and isolation for non-normative users.
A survey of 457 papers yields a six-dimensional design space for abstraction in interactive systems that reframes gulfs of execution and evaluation while articulating cognitive and design processes for bridging abstraction gaps.
LLM-based conversational interface for Android reduces task time and mental effort for blind users versus traditional gesture-based screen readers like TalkBack.
A scoping review and empirical analysis produce a six-category taxonomy of factors driving AI non-development and abandonment, showing that practical issues like resource limits and organizational dynamics often outweigh ethical concerns in real decisions.
AI improves brainstorming quality for general-purpose impact assessment but not specialized applications when it offers hints early and structures ideas later, based on workshop evaluations with 54 participants.
ANVIL automates analogy-based instructional animations for computer science by chaining LLM analogy generation, screenplay structuring, manim code production with repair, and mixed human-automated evaluations.
Interviews with practitioners and educators yield a systematic account of annotation design considerations, trade-offs, and contextual judgments in visualization practice.
A four-year mixed-methods study of game-based systems for Indian CHWs yields eight design guidelines for sustained engagement, learning transfer, and contextual appropriateness in low-resource health training.
StreetDesignAI provides structured multi-persona feedback on cycling designs and a user study shows it broadens designers' grasp of diverse cyclist perspectives and improves design decision confidence.
PREFAB applies preference learning grounded in the peak-end rule to let users annotate only key affective change segments while interpolating the rest, reducing workload and improving confidence in a 25-participant study.
The authors conduct a systematic literature review and real-world analysis to define Crowdsourced Context Systems and map a six-aspect design space with normative implications.
A method merges codebooks via LLM and evaluates human and AI inductive coding with four new metrics on an online conversation dataset.
Qualitative interviews with five Muslim women highlight the need for balanced, optional contextual links between Qur'an, Hadith, and Seerah in learning apps, leading to the concept of layered contextuality.
PAPEL, a parent-AI collaborative system with four modules grounded in play scenes, led to more integrated parent utterances and increased parent-child conversational turns in a study of 16 dyads compared to a chatbot baseline.
Biofoundries reshape scientific creativity by displacing sensory cues and redistributing responsibility, and should be designed as Creativity Support Tools based on interviews with nine experts.
Introduces Semantic Repulsion Technique (SRT) that boosts semantic diversity in AI creative outputs by 85-167% and receives higher usefulness and coherence ratings than baselines in a 16-person user study.
Mixed-methods study of agile teams finds fragmented practices and organizational barriers limit neurodivergent inclusion despite agile methods' potential.
Longitudinal surveys show AI coding assistants reduce time on code writing but increase supervisory verification tasks, with stable productivity perceptions yet rising reports of worsened developer experience.
Post-editors changed one in three metaphors in NMT and LLM outputs for literary texts, rated quality poor, and found post-editing more laborious than original translation.
citing papers explorer
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Before You Scroll Again: Predicting Regretful Social Media Sessions from In-the-Wild Contextual and Wearable Sensing
Intention-use gaps and displacement of valued activities predict social media regret more strongly than duration, with pre-session context generalizing across users and physiological signals adding person-specific predictive power.
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WhatIf: Interactive Exploration of LLM-Powered Social Simulations for Policy Reasoning
WhatIf provides an interactive platform for real-time exploration of LLM-driven social simulations, enabling policymakers to iteratively test plans, reflect on assumptions, and uncover vulnerabilities in emergency preparedness scenarios.
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From Daily Song to Daily Self: Supporting Reflective Songwriting of Deaf and Hard-of-Hearing Individuals through Generative Music AI
SoulNote enables multi-session GenAI songwriting for DHH users, producing measurable gains in self-insight, emotion regulation, and self-care attitudes.
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What Do People Actually Want From AI? Mapping Preference Plurality
Open-ended preference data reveals substantial plurality in what people want from AI and divergent interpretations of shared values such as truthfulness.
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Going PLACES: Participatory Localized Red Teaming for Text-to-Image Safety in the Global South
A participatory red-teaming project in the Global South created the PLACES dataset of 26k T2I failure examples that reveal unique cultural and linguistic harms missed by existing safety frameworks.
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"It became a self-fulfilling prophecy": How Lived Experiences are Entangled with AI Predictions in Menstrual Cycle Tracking Apps
Users entangle their lived experiences with AI predictions in menstrual tracking apps, leading to self-fulfilling prophecies, limited critical awareness from UI, and isolation for non-normative users.
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Making Abstraction Concrete: A Design Space and Interaction Model of Abstraction in Interactive Systems
A survey of 457 papers yields a six-dimensional design space for abstraction in interactive systems that reframes gulfs of execution and evaluation while articulating cognitive and design processes for bridging abstraction gaps.
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Insight: Enhancing Mobile Accessibility for Blind and Visually Impaired Users with LLMs
LLM-based conversational interface for Android reduces task time and mental effort for blind users versus traditional gesture-based screen readers like TalkBack.
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To Build or Not to Build? Factors that Lead to Non-Development or Abandonment of AI Systems
A scoping review and empirical analysis produce a six-category taxonomy of factors driving AI non-development and abandonment, showing that practical issues like resource limits and organizational dynamics often outweigh ethical concerns in real decisions.
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When and How AI Should Assist Brainstorming for AI Impact Assessment
AI improves brainstorming quality for general-purpose impact assessment but not specialized applications when it offers hints early and structures ideas later, based on workshop evaluations with 54 participants.
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ANVIL: Analogies and Videos for Lecturers
ANVIL automates analogy-based instructional animations for computer science by chaining LLM analogy generation, screenplay structuring, manim code production with repair, and mixed human-automated evaluations.
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Designing Annotations in Visualization: Considerations from Visualization Practitioners and Educators
Interviews with practitioners and educators yield a systematic account of annotation design considerations, trade-offs, and contextual judgments in visualization practice.
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Design Guidelines for Game-Based Refresher Training of Community Health Workers in Low-Resource Contexts
A four-year mixed-methods study of game-based systems for Indian CHWs yields eight design guidelines for sustained engagement, learning transfer, and contextual appropriateness in low-resource health training.
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StreetDesignAI: Broadening Designer Perspectives Through Multi-Persona Evaluation of Cycling Infrastructure
StreetDesignAI provides structured multi-persona feedback on cycling designs and a user study shows it broadens designers' grasp of diverse cyclist perspectives and improves design decision confidence.
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PREFAB: PREFerence-based Affective Modeling for Low-Budget Self-Annotation
PREFAB applies preference learning grounded in the peak-end rule to let users annotate only key affective change segments while interpolating the rest, reducing workload and improving confidence in a 25-participant study.
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Beyond Community Notes: A Framework for Understanding and Building Crowdsourced Context Systems for Social Media
The authors conduct a systematic literature review and real-world analysis to define Crowdsourced Context Systems and map a six-aspect design space with normative implications.
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A Computational Method for Measuring "Open Codes" in Qualitative Analysis
A method merges codebooks via LLM and evaluates human and AI inductive coding with four new metrics on an online conversation dataset.
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Designing for Interconnected Islamic Learning: A Qualitative Study of Muslim Women's Experiences with Qur'an, Hadith, and Seerah Apps
Qualitative interviews with five Muslim women highlight the need for balanced, optional contextual links between Qur'an, Hadith, and Seerah in learning apps, leading to the concept of layered contextuality.
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PAPEL: A Collaborative System for Parental Guidance during Preschool Play-Based English Learning
PAPEL, a parent-AI collaborative system with four modules grounded in play scenes, led to more integrated parent utterances and increased parent-child conversational turns in a study of 16 dyads compared to a chatbot baseline.
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Creativity in the BioFoundry: Supporting scientific creativity in the age of automation
Biofoundries reshape scientific creativity by displacing sensory cues and redistributing responsibility, and should be designed as Creativity Support Tools based on interviews with nine experts.
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Seeing the Hivemind: A Consensus-Aware Interaction Technique for Mitigating AI Homogenization
Introduces Semantic Repulsion Technique (SRT) that boosts semantic diversity in AI creative outputs by 85-167% and receives higher usefulness and coherence ratings than baselines in a 16-person user study.
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Neurodiversity in Agile Teams: Obstacles and Inclusion Barriers
Mixed-methods study of agile teams finds fragmented practices and organizational barriers limit neurodivergent inclusion despite agile methods' potential.
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The Impact of AI Coding Assistants on Software Engineering: A Longitudinal Study
Longitudinal surveys show AI coding assistants reduce time on code writing but increase supervisory verification tasks, with stable productivity perceptions yet rising reports of worsened developer experience.
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Metaphors in Literary Post-Editing: Opening Pandora's Box?
Post-editors changed one in three metaphors in NMT and LLM outputs for literary texts, rated quality poor, and found post-editing more laborious than original translation.
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What Would GPT Click: Practical Effects of Human-AI Behavioral Misalignment and the Cost of Synthetic Participants in User Experience
GPT produces click distributions significantly different from real humans in 53% of UX first-click tasks, with prompting techniques like personas and chain-of-thought failing to improve alignment.
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An Activity-Theoretical Approach to Teacher Professional Development in Pedagogical AI Agent Design
Teachers disengage from AI agent creation after training due to systemic contradictions that thwart psychological needs rather than skill gaps, and a CHAT-SDT redesign can resolve this by boosting both capacity and willingness.
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Modeling AI-TPACK in Practice Insights from Teachers Multi-Agent Workflow Design
Cluster analysis of teacher multi-agent workflow designs reveals three archetypes where AI-TPACK emerges dynamically from systems thinking, pedagogical beliefs, and self-efficacy.
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Fine-Tuning Models for Automated Code Review Feedback
PEFT fine-tuning of Code Llama yields feedback on student Java bugs that students judge equal to ChatGPT and better than prompt engineering, using BLEU/ROUGE/BERTScore plus human ratings.
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Why AI Harms Can't Be Fixed One Identity at a Time: What 5300 Incident Reports Reveal About Intersectionality
Large-scale review of 5300 AI incident reports shows harms are amplified up to three times at specific intersections including adolescent girls, lower-class people of color, and upper-class political elites.
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Trust as a Situated User State in Social LLM-Based Chatbots: A Longitudinal Study of Snapchat's My AI
Trust in social LLM chatbots is a dynamic, situated user state that evolves through ongoing interactions rather than forming as a stable one-time judgment.
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Audio Video Verbal Analysis (AVVA) for Capturing Classroom Dialogues
AVVA is a new framework adapting verbal analysis for classroom discourse with triangulation across ten steps and a four-criterion validation scheme for temporal stability, applied to 23 hours of recordings.
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Language, Place, and Social Media: Geographic Dialect Alignment in New Zealand
New Zealand Reddit users link language to place and form contiguous speech communities with complex geographic alignment; Word2Vec embeddings reveal semantic variations and shifts in NZ English on a 4.26 billion word corpus.
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NexusAI: Enabling Design Space Exploration of Ideas through Cognitive Abstraction and Functional Decomposition
NexusAI decomposes LLM inspirations into navigable functional fragments and abstractions to improve creative design space exploration, with a user study showing reduced cognitive overhead.
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Foreign Domestic Workers' Perspectives on an LLM-Based Emotional Support tool for Caregiving Burden
Exploratory interviews reveal FDWs find LLM chatbots psychologically safe, linguistically flexible, and useful for reassurance and companionship.
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Not a Collaborator or a Supervisor, but an Assistant: Striking the Balance Between Efficiency and Ownership in AI-incorporated Qualitative Data Analysis
Interviews with 16 qualitative researchers identify efficiency, ownership, and trust as key factors shaping preferences for AI as a supportive assistant rather than a full collaborator or supervisor in qualitative data analysis.
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Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration
Interviews reveal a four-stage vibe coding workflow that accelerates prototyping while introducing tensions between quick efficiency and reflective design intention, plus asymmetries in trust and ownership.
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Unpacking "Personal" Health Informatics for Proactive Collective Care
Mixed-methods research shows collective care practices are constrained by personal, relational, technological, and structural factors in existing PHI systems, leading to the CC-Proact operational map with three design levers and ten recommendations for collective health informatics.
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The impact of artificial intelligence on enterprise software user roles
Qualitative study of 20 interviews and 24 workshop participants finds AI-driven automation and human-AI collaboration are shifting development roles in SAP BTP and require updates to the existing BTP User Type Matrix.
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Organizing in the Digital Age: Understanding Community, Challenges, and Consequences in Digitally-facilitated Labor Organizing
Qualitative study of 17 interviews finds digital tools support labor organizing but introduce challenges in technical security, information overload, and building trust and consensus.
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Understanding LLMs in Title-Abstract Screening: From Disagreements to Recommendations
Analysis of LLM vs human disagreements in six software engineering systematic reviews reveals recurring causes like term ambiguity and proposes recommendations for LLM deployment.
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UXR PoV for Neuroinclusive Emotion Regulation
The paper describes a Generative AI-supported UXR methodology that integrates DBT, SDT and COM-B to create ten Play Cards for neuroinclusive ADHD emotion regulation interventions.
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Framing an AI with Values Reduces AI Reliance in AI-supported Writing Tasks
An online experiment finds that showing users an overview of an AI's values reduces reliance on AI suggestions during writing tasks.
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Measuring Changes in Instructor Class Design and Student Learning After the Release of Large Language Models (LLMs)
A pilot mixed-methods study at one university uses surveys and pre/post-LLM grade data to document patterns in faculty course design and student learning outcomes after generative AI release.
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Understanding Clinician Experiences with Game-Based Interventions for Autistic Children to Inform a Future Game Platform Focused on Improving Motor Skills
Therapist perspectives on game-based motor interventions for autistic children reveal rigidity issues, leading to a proposed modular customizable game platform.
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Effects of Collaboration on the Performance of Interactive Theme Discovery Systems
The study introduces a framework and reports differences in consistency, cohesiveness, and correctness of themes produced under synchronous versus asynchronous collaboration across three interactive NLP tools.
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Human-AI Agent Interaction in a Business Context
Exploratory mixed-methods research identifying user expectations for positive UX with AI agents in business and informing a follow-up survey experiment.
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