ASL Educators’ Perspectives on AI for Enhancing Student Learning in American Sign Language Education

Paper Title

ASL Educators’ Perspectives on AI for Enhancing Student Learning in American Sign Language Education

Publication Info

• Topic area: AI applications in American Sign Language education, focusing on educator perspectives.
• Keywords: American Sign Language, AI in education, Deaf educators, sign language pedagogy, feedback tools, conversational AI, linguistic diversity, cultural alignment, accessibility, higher education.

Background and Problem

• Problem / challenge: Despite growing interest in ASL education, limited program availability and practice opportunities hinder learning. AI tools for ASL education have focused on learners, often excluding educators’ perspectives, which are critical for aligning technology with pedagogical and cultural practices.
• Significance: Addressing this gap is essential for creating effective, culturally appropriate AI tools that support ASL learning while reducing educators’ workload and enhancing student outcomes.
• Motivation and related work: Prior research has explored AI applications in language learning but has largely neglected ASL educators, particularly Deaf educators. Existing tools often fail to account for ASL’s linguistic diversity, spatial grammar, and cultural nuances, highlighting the need for educator-centered design.

Solution

• Proposed approach: Conduct formative interviews and focus groups with ASL educators to gather insights on AI’s role in ASL education and identify design requirements for AI-powered feedback tools and conversational practice partners.
• Novelty:
  1. First study to center ASL educators’ perspectives on AI use in higher education.
  2. Empirical insights into linguistic, pedagogical, and equity considerations for AI tools in ASL education.
  3. Design recommendations for AI tools that align with ASL curricula and support diverse linguistic and cultural practices.
  4. Exploration of two key use cases: feedback tools and conversational practice partners.
• Procedure and key techniques:
  • Conducted interviews with 12 ASL educators and focus groups with 6 participants.
  • Explored educators’ views on AI integration, feedback tools, and conversational partners.
  • Used thematic analysis to identify key themes and design implications.

Results

• Concrete findings:
  • Educators emphasized the need for AI tools to align with curricula, support linguistic diversity, and provide tailored feedback.
  • AI tools should offer moderated feedback, adapt to learner contexts, and include bilingual scaffolding.
  • Conversational AI partners should be culturally adept, customizable, and simulate real-world scenarios.
• Advantage over baselines:
  • Addresses gaps in existing ASL tools by centering educator perspectives and focusing on linguistic and cultural alignment.
  • Provides actionable design insights for AI tools that enhance expressive skills and conversational practice.
• Experiments / evaluation:
  • Interviews and focus groups with ASL educators across U.S. higher education institutions.
  • Participants included 11 Deaf educators and 1 hearing educator, with diverse teaching experiences and institutional affiliations.
  • Analysis focused on thematic insights into AI integration, tool requirements, and equity considerations.
• Limitations and future work:
  • Did not test AI tools directly; findings are based on educator ideation and qualitative feedback.
  • Limited racial diversity among participants; future work should recruit more diverse educators.
  • Focused on higher education; future research should explore other educational contexts and sign languages.

Summary

This study explores ASL educators’ perspectives on AI tools for enhancing ASL education, identifying key requirements for feedback systems and conversational practice partners. Findings emphasize the importance of aligning AI tools with curricula, supporting linguistic diversity, and providing tailored, moderated feedback. Educators envision AI as a complementary tool to reduce workload and enhance learning opportunities, particularly for expressive skills and conversational practice. Future research should engage diverse stakeholders to design culturally and pedagogically appropriate AI tools that address equity and accessibility challenges.