Integrating generative artificial intelligence into social work education: using chatbot simulations to train students for community engagement

This paper examines the integration of GenAI-powered chatbots into social work education, focusing on community engagement and assessment skills, drawing on insights from a university teaching development project. The initiative aimed to harness AI technologies to enhance student engagement with diverse service users and improve their ability to tackle community-level challenges. By utilizing GenAI-powered chatbot simulations, the project offered structured simulations to support practice preparation. Our findings from 36 student responses indicate increased confidence in using AI tools and positive learning experiences in AI-supported community engagement practice. This study explores how AI can enhance traditional social work education by addressing the limitations of conventional face-to-face methods in simulating practice complexity, while acknowledging key limitations. Quantitative findings revealed neutral student ratings regarding the chatbot’s ability to provide realistic role-plays or accurately simulate complex real-world population. The paper discusses the AI’s potentialto bridge theoretical knowledge and practical skills, providing students with structured conversational simulations approximating selected aspects of social interactions recognizing their limited humanistic nuance and structural accuracy. It highlights the need to prepare students for a digitally transformed professional landscape while preserving the core ethical and relational foundations.