Introduction:

AI-mediated communication (AI-MC) has gained popularity as an accessibility tool in higher education. Both Deaf and Hard of Hearing (DHH) individuals and hearing students and staff rely heavily on AI-MC tools, such as transcription and translation services (e.g., Otter.ai, DeepL). These tools are especially valuable when a DHH individual cannot secure an interpreter or when a hearing individual is unable to type. Additionally, both groups use language correction tools (e.g., ChatGPT, Grammarly) to save time and reduce costs associated with hiring editors. However, it remains unclear whether AI-MC tools positively impact digital communication access for both DHH and hearing individuals or if they have a negative effect on mental health. Moreover, the effectiveness of these tools as cost-effective alternatives for university administrations compared to hiring sign language interpreters is uncertain. Furthermore, it is unknown whether DHH and hearing individuals prefer AI-MC tools over interpreters when privacy concerns and personal boundaries arise. Therefore, the aim of the study is to explore the experiences of DHH and hearing students and staff with communication technology and their values regarding AI-mediated communication.

Research Questions:

1. What AI-MC tools do DHH and hearing university students and staff value the most?
2. Does the environment of use (e.g., classroom, hospital) influence the choice of DHH and hearing students/staff between free translation software and sign language interpreters?
3. Which option—free translation software or a sign language interpreter—do DHH and hearing students and staff prefer for communication with each other?
4. Do the findings differ based on demographics such as university location, age, gender, ethnicity/race, level of education, specialization, audiological levels, income, and preferred communication methods?
5. What recommendations can be made for improving the accessibility of AI-MC tools for DHH and hearing students and staff at universities?

Methodology:

The study adopts a concurrent mixed-methods design, collecting both surveys and in-depth interviews with selected participants, then analysing and merging the data. The target populations are: (1) DHH university students/staff, or (2) hearing university students/staff who have interacted with DHH students or staff at a university in the United Kingdom.

In the first phase, the researcher will conduct a nationwide survey addressing the experiences of DHH and hearing university students and staff with communication technology and their values toward AI-mediated communication tools. In the second phase, the researcher will conduct in-depth follow-up interviews with DHH and hearing students and staff who completed the first phase and expressed interest in participating in the interview. In the final phase, the researcher will merge and analyse the quantitative and qualitative data.

Expected Outcome:

If the study reveals that DHH and hearing students and staff place higher value on free translation software over sign language interpreters, universities could implement initiatives to provide free translation software for these individuals, promoting cost-effectiveness. This would also enhance communication access for DHH students and staff in situations where a sign language interpreter is unavailable or when they prefer not to use one for reasons of confidentiality. Furthermore, if the study indicates that excessive use of technology contributes to mental health challenges among DHH and hearing students and staff, the university might consider strategies to balance online and in-person communication. Additionally, the findings could offer valuable feedback to product developers and engineers on the need for AI-MC tools that function without network access. This is particularly important in emergency situations where connectivity may be limited or non-existent. We hope that the results of this study will lead to recommendations for improving AI-mediated communication accessibility for DHH students and staff members at universities.