Date
Publisher
arXiv
Intelligent tutoring systems (ITS) using artificial intelligence (AI)
technology have shown promise in supporting learners with diverse abilities;
however, they often fail to meet the specific communication needs and cultural
nuances needed by d/Deaf and Hard-of-Hearing (DHH) learners. As large language
models (LLMs) provide new opportunities to incorporate personas to AI-based
tutors and support dynamic interactive dialogue, this paper explores how DHH
learners perceive LLM-powered ITS with different personas and identified design
suggestions for improving the interaction. We developed an interface that
allows DHH learners to interact with ChatGPT and three LLM-powered AI tutors
with different experiences in DHH education while the learners watch an
educational video. A user study with 16 DHH participants showed that they
perceived conversations with the AI tutors who had DHH education experiences to
be more human-like and trustworthy due to the tutors' cultural knowledge of DHH
communities. Participants also suggested providing more transparency regarding
the tutors' background information to clarify each AI tutor's position within
the DHH community. We discuss design implications for more inclusive LLM-based
systems, such as supports for the multimodality of sign language.
Study at a glance
- Question: How do deaf and hard-of-hearing learners perceive AI tutors designed with different personas?
- Setting and data: 16 deaf and hard-of-hearing learners watching an educational video.
- Method: User study testing an interface with different AI tutor personas.
Why it matters
While AI intelligent tutoring systems show promise for diverse learners, they often fail to meet the specific communication needs and cultural nuances of d/Deaf and Hard-of-Hearing learners.
Key findings
- In a study of 16 deaf and hard-of-hearing learners, participants perceived AI tutors with deaf education experience as more human-like and trustworthy.
- Participants attributed the higher trustworthiness and human-like quality to the AI tutors' cultural knowledge of deaf communities.
- Participants reported wanting more transparent background information to clarify each AI tutor's position within the deaf community.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
What is the application?
Who is the user?
Who age?
Why use AI?
Study design
