LLM-enhanced Interactions in Human-Robot Collaborative Drawing with Older Adults

Fuente: arXiv
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Auteurs principaux: Bossema, Marianne, Allouch, Somaya Ben, Plaat, Aske, Saunders, Rob
Format: Preprint
Publié: 2025
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author Bossema, Marianne
Allouch, Somaya Ben
Plaat, Aske
Saunders, Rob
author_facet Bossema, Marianne
Allouch, Somaya Ben
Plaat, Aske
Saunders, Rob
contents The goal of this study is to identify factors that support and enhance older adults' creative experiences in human-robot co-creativity. Because the research into the use of robots for creativity support with older adults remains underexplored, we carried out an exploratory case study. We took a participatory approach and collaborated with professional art educators to design a course Drawing with Robots for adults aged 65 and over. The course featured human-human and human-robot drawing activities with various types of robots. We observed collaborative drawing interactions, interviewed participants on their experiences, and analyzed collected data. Findings show that participants preferred acting as curators, evaluating creative suggestions from the robot in a teacher or coach role. When we enhanced a robot with a multimodal Large Language Model (LLM), participants appreciated its spoken dialogue capabilities. They reported however, that the robot's feedback sometimes lacked an understanding of the context, and sensitivity to their artistic goals and preferences. Our findings highlight the potential of LLM-enhanced robots to support creativity and offer future directions for advancing human-robot co-creativity with older adults.
format Preprint
id arxiv_https___arxiv_org_abs_2506_18711
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle LLM-enhanced Interactions in Human-Robot Collaborative Drawing with Older Adults
Bossema, Marianne
Allouch, Somaya Ben
Plaat, Aske
Saunders, Rob
Human-Computer Interaction
The goal of this study is to identify factors that support and enhance older adults' creative experiences in human-robot co-creativity. Because the research into the use of robots for creativity support with older adults remains underexplored, we carried out an exploratory case study. We took a participatory approach and collaborated with professional art educators to design a course Drawing with Robots for adults aged 65 and over. The course featured human-human and human-robot drawing activities with various types of robots. We observed collaborative drawing interactions, interviewed participants on their experiences, and analyzed collected data. Findings show that participants preferred acting as curators, evaluating creative suggestions from the robot in a teacher or coach role. When we enhanced a robot with a multimodal Large Language Model (LLM), participants appreciated its spoken dialogue capabilities. They reported however, that the robot's feedback sometimes lacked an understanding of the context, and sensitivity to their artistic goals and preferences. Our findings highlight the potential of LLM-enhanced robots to support creativity and offer future directions for advancing human-robot co-creativity with older adults.
title LLM-enhanced Interactions in Human-Robot Collaborative Drawing with Older Adults
topic Human-Computer Interaction
url https://arxiv.org/abs/2506.18711