How Social Work and Engineering Co-Design AI-Powered Client Simulations for Social Casework Teaching

社工 × 工程之跨域共創：以AI驅動之個案模擬於社會個案工作教學

Dr. Johnson Chun-Sing Cheung

Senior Lecturer, The University of Hong Kong, Hong Kong SAR, China 中國香港大學高級講師

Abstract: Simulation-based learning represents the signature pedagogy in social work education, providing students with experiential opportunities to develop professional interviewing skills, decision-making capacity, and self-awareness in a controlled, safe environment. Despite its pedagogical value, traditional simulation-based approaches face persistent practical barriers: the substantial time and cost requirements for recruiting and training standardized patients or actors; limited availability of diverse, culturally specific client scenarios; spatial and temporal constraints that bind practice opportunities to scheduled classroom hours; and the challenge of accessing adequate practice time before fieldwork placement. These systemic constraints create inequities in student readiness and limit exposure to the full spectrum of complex, nuanced client presentations that characterize real social work practice. Generative artificial intelligence (GenAI) offers transformative potential to address these challenges at scale. However, the implementation requires more than deploying existing large language models (LLMs) as generic chatbots. This project demonstrates how meaningful cross-disciplinary collaboration between social work and engineering academics can co-create AI-powered virtual client simulations that are simultaneously technically sophisticated and grounded in social work's relational practice. The project is undertaken by a student interest group (SIG) at the HKU Innovation Wing comprising both social work and engineering undergraduates, supervised by faculty mentors from both disciplines. This creates a genuine co-learning environment where social work students understand technological development and limitations, while engineering students grapple with the human and ethical dimensions of social work. The virtual clients integrate real-time skill classification systems to provide students with immediate, objective feedback on their interviewing techniques.

Bio: Dr. Johnson Chun-Sing Cheung holds a Doctor of Social Work (DSW) from the Hong Kong Polytechnic University, a Master of Buddhist Counselling (MBC), a Master of Social Sciences (MSocSc) and Bachelor of Social Work (BSW) from the University of Hong Kong, and a Master of Arts in Philosophy from the Chinese University of Hong Kong. He is a Registered Social Worker (RSW) and a Certified Philosophical Counselor. Dr. Cheung has strong commitment in bridging technology and social work practice, advancing research and innovation at the intersection of digitalization, artificial intelligence, and human-centered social work. As a consultant for the Society for Innovation and Technology in Social Work (SITSW), Dr. Cheung actively shapes the discourse on responsible technology adoption in the social work profession. He is a member of the European Social Work Research Association (ESWRA) Social Work Research on Digitization and Technology Special Interest Group, where he contributes to advancing international research and practice on how digitalization, generative artificial intelligence, and emerging technologies connect with and impact social work.