AI-ASSISTED CASE METHOD IN ESP FOR SOCIAL WORKERS
AI-ASSISTED CASE METHOD IN ESP FOR SOCIAL WORKERS

Summary/Abstract: This study examines the implementation of artificial intelligence-assisted case method instruction in English for Specific Purposes courses for first-year social work students in Ukrainian higher education. The research addresses critical gaps in ESP pedagogy including scarcity of culturally relevant materials, ethical limitations of using authentic client cases, and challenges of integrating language skills with professional competency. The three-phase methodology leverages AI to generate realistic, culturally appropriate case profiles reflecting Ukrainian social issues (internally displaced persons, school bullying, single-parent families). The study’s implementation with 20 first-year students during 2024-2025 demonstrated notable improvements in vocabulary acquisition (students recorded an average of 50-60 professional terms with high retention), speaking confidence (progressing from hesitant code-switching to sustained English discussions), reading comprehension, and writing skills (developing from simple to professionally appropriate materials). Qualitative analysis reveals high student engagement, emotional connection to culturally relevant materials, and integration of language learning with professional identity development. The study concludes that AI-assisted case method instruction effectively prepares Ukrainian social work students for real-world English communication while maintaining ethical standards, cultural relevance, and pedagogical scalability.

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