Stakeholder Perspectives on Whether and How Social Robots Can Support Mediation and Advocacy for Higher Education Students with Disabilities

TL;DR

This study investigates how social robots and large language models (LLMs) could mediate and advocate for disabled students in higher education through an iterative, participatory design process at the University of Cambridge. It combines Phase 1 interviews with disability practitioners and students and Phase 2 focus groups to elicit problem-space insights and co-design considerations, emphasizing empathy, regulatory clarity, workload, power dynamics, and authenticity. The findings identify potential robot roles (e.g., signposting, study companion, venting partner) and design dimensions (neutral appearance, multilingual capabilities, adaptive personality, consent mechanisms) while flagging ethical risks such as bias, data privacy, and the risk of reinforcing existing inequities. The paper argues for a shift from corrective technological interventions to empowering tools that amplify self-advocacy, and offers recommendations rooted in social disability models, double empathy considerations, and design-justice principles to guide future research and deployment.

Abstract

This paper presents an iterative, participatory, empirical study that examines the potential of using artificial intelligence, such as social robots and large language models, to support mediation and advocacy for students with disabilities in higher education. Drawing on qualitative data from interviews and focus groups conducted with various stakeholders, including disabled students, disabled student representatives, and disability practitioners at the University of Cambridge, this study reports findings relating to understanding the problem space, ideating robotic support and participatory co-design of advocacy support robots. The findings highlight the potential of these technologies in providing signposting and acting as a sounding board or study companion, while also addressing limitations in empathic understanding, trust, equity, and accessibility. We discuss ethical considerations, including intersectional biases, the double empathy problem, and the implications of deploying social robots in contexts shaped by structural inequalities. Finally, we offer a set of recommendations and suggestions for future research, rethinking the notion of corrective technological interventions to tools that empower and amplify self-advocacy.

Figures (9)

• Figure 1: Interview themes and subthemes from thematic analysis of Phase 1 of the study
• Figure 2: Interactive activity in the second focus group in phase 2 of the study. Participant's matched examples of robot roles derived from the first focus group with pictures of different robots
• Figure 3: Overview of the themes and subthemes derived from focus group 1
• Figure 4: First task in the focus group was to indicate existing usage of technological tools
• Figure 5: A word cloud from the question 'What are the first words coming to mind after seeing these robots?' after showing the video clip of social robots during the Ideating Robotic Support part of the focus groups