University of Illinois Urbana-Champaign

Designing AI-driven conversational agents to support older adults’ virtual reality learning and lifelong growth

Cheng, Qiyuan

This item's files can only be accessed by the System Administrators group.

Permalink

https://hdl.handle.net/2142/127516

Description

Title
Designing AI-driven conversational agents to support older adults’ virtual reality learning and lifelong growth
Author(s)
Cheng, Qiyuan
Issue Date
2024-12-11
Director of Research (if dissertation) or Advisor (if thesis)
Gupta, Avinash
Department of Study
Industrial&Enterprise Sys Eng
Discipline
Industrial Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
  • AI-driven Conversational Agents
  • Virtual Reality
  • Older Adults
  • Participatory Design
  • Human-AI Interaction
  • Design for Aging
  • Learning Support
  • Technology Adoption
Abstract
This research investigates how AI-driven conversational agents (CAs) can support older adults in learning and engaging with virtual reality (VR) technology. Through semi-structured interviews with three participants aged 50+ and a participatory design workshop, we explored the challenges older adults face when learning VR, their specific support needs, and their expectations for AI assistance. Our findings reveal a complex set of challenges in VR learning, including physical barriers, interface complexity, and social-contextual factors. Participants expressed a need for personalized, adaptive support that respects their autonomy while offering consistent guidance. Their expectations for AI-driven CAs emphasized natural interaction, context awareness, and appropriate emotional engagement, while maintaining clear professional boundaries. Based on these insights, we offer design recommendations for AI-driven CAs to effectively support older adults’ VR learning. These include balancing functionality with usability, integrating emotional intelligence with professional boundaries, and ensuring seamless adaptation to diverse social and environmental contexts. This research contributes to the growing field of age-inclusive technology design and provides practical guidelines for developing AI-supported VR learning systems that foster lifelong growth and engagement.
Graduation Semester
2024-12
Type of Resource
Thesis
Handle URL
https://hdl.handle.net/2142/127516
Copyright and License Information
Copyright 2024 Qiyuan Cheng

Owning Collections

Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at Illinois