THURS-107 - GenAI for Public Health Educators: Improve Learning, Accelerate Research
Thursday, April 23, 2026
5:00 PM - 6:00 PM PST
Location: Plaza Foyer, Plaza Level
Area of Responsibility: Area III: Implementation Keywords: Evaluation@@@Health Research@@@Technology, Subcompetencies: 4.3 Manage the collection and analysis of evaluation and/or research data using appropriate technology., 4.2.8 Adopt, adapt, and/or develop instruments for collecting data. Research or Practice: Research
Vice Dean of Education McWilliams School of Biomedical Informatics at UTHealth Houston Houston, Texas, United States
Learning Objectives:
At the end of this session, participants will be able to:
Describe how public health educators can leverage AI tools for personalized learning and health education tools.
Explain how to educate on the challenges and concerns of a growing AI presence in public health and how to responsibly use AI.
Discuss educational needs regarding three governance practices for responsible GenAI use (privacy safeguards, verification/citation steps, accessibility checks).
Brief Abstract Summary: Generative AI (GenAI) is rapidly transforming the way public health educators learn, teach, and conduct applied research. This session translates hype into practice: attendees will see concrete, low risk ways to use GenAI for lesson planning, training simulations, literature screening, qualitative coding, and plain language communication—while avoiding privacy, bias, and accuracy pitfalls. We will demonstrate effective prompting patterns (e.g., role, task, constraints, examples), share vetting and citation-checking workflows, and outline guardrails for using GenAI ethically without protected health information (PHI). Participants leave with checklists, prompt templates, and evaluation rubrics they can adapt to their public health education programs.
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Detailed abstract description: Why attend. Public health educators face mounting pressure to do more with less—design engaging learning, analyze diverse data sources, and communicate clearly in fast moving contexts. Generative AI (GenAI) can act as an assistant to accelerate these tasks when used responsibly. This session moves beyond concepts to demonstrate methods for applying GenAI in education and practice—what it excels at, where it falls short, and how to establish guardrails. By the end, participants will be able to: 1. Apply prompt frameworks to create lesson outlines, skills checklists, and training scenarios aligned to learning objectives; 2. Prototype research workflows (literature triage, codebook drafting, qualitative summarization, synthetic examples for practice) without exposing protected health information (PHI); 3. evaluate GenAI outputs for bias, hallucination, and accessibility; and 4. implement a simple governance toolkit for safe use in their organization. What we’ll cover (with practical demonstrations and templates): • Personalized learning: building adaptive case studies, formative quizzes, and feedback rubrics aligned to Bloom’s taxonomy. • Communication: drafting culturally and linguistically appropriate plain language messages and counter misinformation FAQs. • Research support: structured prompts for literature screening, data abstraction tables, qualitative coding starts, and transparent audit trails. • Guardrails: privacy-first workflows (no PHI in prompts), citations and verification, bias checks, accessibility/readability checks, and model limitations. Format & engagement (60 minutes): brief framing (10), guided demo/mini lab using prompt templates participants can adapt (30), small group application to a public health scenario (15), share outs (5). Participants receive a starter packet (prompt templates, checklists, and an evaluation rubric) to take back to their teams. Value to attendees: Everyone leaves with practical resources and a repeatable way to introduce GenAI ethically into public health learning and applied research—improving speed and consistency while maintaining equity, quality, and trust.
