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arxivcs.HC2026-06-25

MedSWFlow: An Open-Source LLM Workflow for Drafting Medical Social Work Case Plans

Yulin Mao, Shiyu Li, Shuping Song, Yuling Zhang, Yajun Song

We present MedSWFlow, an open-source, model-agnostic LLM workflow for drafting medical social work case plans. The framework translates professional case-planning tasks into six stages: assessment, problem analysis, goal setting, intervention planning, risk anticipation, and planned effect evaluation. Drawing on established social work and behavioral frameworks, MedSWFlow standardizes case inputs, builds structured case profiles, and generates reviewable assessment forms and service plans through staged prompting. The system is released as an open-source research framework for reproducible case-plan generation across LLM providers. Outputs are intended as practitioner-reviewed drafts rather than final service decisions. Source code: https://github.com/santhiyacw-droid/MedSWFlow/tree/main.

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When LLM Tutoring Responses Work: Evidence from Student Programming Conversations

Mohammad Fahim Abrar, Shayla Sharmin, Roghayeh Leila Barmaki

As students increasingly use LLM tutors in computer science education, one question becomes especially important: what kind of response helps a student continue productively? Prior work has studied how students use LLMs in computer science education, but less is known about how t…

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