INTEGRATING ARTIFICIAL INTELLIGENCE AND GROUP WORK IN TEACHING DEAF AND HARD–OF–HEARING STUDENTS

Artificial intelligence (AI) is increasingly recognised for enabling personalised, flexible learning and for helping reduce communication barriers. In the meantime, group–based interventions have shown significant positive results for socially excluded populations (Gonyea and Burns, 2013; Robertson and Evans, 2015; Lewis et al., 2016). Yet, AI adaptation into inclusive education settings for deaf and hard–of–hearing students (DHHS) has not been rigorously evaluated. This paper aims to report a realistic evaluation of an AI–based inclusive education program, Artificial Intelligence in Group Social Work for Deaf and Hard of Hearing (AIGS–DHH) in Ho Chi Minh City, Vietnam. Our 3–month pioneering program was proposed and implemented at the Center for Research and Education of the Deaf and Hard of Hearing (CED). We conducted qualitative interviews and focus group data from two randomly assigned participant groups: the Experimental group (n = 5) and the Control group (n = 5). The Rosenberg Self–Esteem Scale (RSES) (Rosenberg, 1965) and the Kessler Psychological Distress Scale (K10) (Kessler and Mroczek, 1992) were administered to all participants prior to and after the program to record changes in self–esteem and psychological distress over the period. The AIGS–DHH program fulfils its aim of integrating AI–supported tools with a group–based approach to enhance accessible learning and communication, psychosocial development, and social inclusion for DHHS. The positive growth among DHHS implies a priority of participatory and DHHS–led design, ensuring DHHS’s active involvement in future AI–Supported group interventions.