Social Robot Interaction and HRI

External reference: https://openalex.org/T10709

  1. Affective and Goal-Oriented Factors of Relationship Formation in the Digital Therapeutic Alliance: A Longitudinal Study of Mental Health Chatbots
    Study reveals that emotional support and practical assistance drive user relationships with mental health chatbots, with trust and satisfaction as outcomes rather than predictors.
  2. Tracking Together: A Robot-and-App-Based Speech Analysis System to Support Shared Meaning-Making Among Dementia Care Partners
    Study examines how people with dementia and care partners want to use tracking technology, revealing needs for autonomy support, actionable insights, and relational understanding.
  3. AI-robot-supported learning improved preschool health education outcomes
    Study examines how AI robots combined with task-based learning affect motivation and problem-solving in preschool health education for ages 5-6.
  4. A Wizard for Kids: A Platform for Improvised Child–Robot Interactions
    Platform design for teleoperated social robots in classrooms, enabling safe child-robot interactions and iterative prototyping of educational robot applications.
  5. Play-based AI curriculum increased teacher confidence
    Design-based study of a play-centered AI literacy curriculum for early childhood, examining teacher co-design, implementation feasibility, and emerging design principles for sustainable AI education.
  6. Improvisational Participatory Storming: A Toolkit of Improvisational Design Methods for Human-Robot Interaction
    Improvisational Participatory Storming integrates theatre-based methods with drama therapy for inclusive human-robot interaction design, enabling direct community participation while protecting.
  7. Designing Care-fully: Robots for Acute Cancer Care
    Care ethics framework for designing social robots in acute cancer care, examining how robots can amplify compassion in emergency department settings through collaborative stakeholder research.
  8. Neural Transparency: Mechanistic Interpretability Interfaces for Anticipating Model Behaviors for Personalized AI
    Neural transparency interface for LLM chatbot design enabling users to anticipate model behaviors through mechanistic interpretability visualization of behavioral trait vectors.