Teaching AI Literacy for Public Health Practice

This study evaluated an AI-driven assignment in an undergraduate public health course to enhance AI literacy among students preparing for health-related careers. Amid growing AI use in academia—and uncertain ethical perceptions—the project addressed the need for responsible AI application in public health and healthcare management education. Designed with constructivist strategies (experiential, inquiry-based, project-based, and collaborative learning), the assignment tasked student groups with creating AI-scaffolded community health promotion plans. Implemented in online sections, the project leveraged tools such as ChatGPT and ClaudeAI for data analysis, decision-making, and communication material development. Pre- and post-curriculum assessments, using the Meta AI Literacy Scale (MAILS) , showed significant gains in overall AI literacy, particularly in confidence, and evaluation skills, though ethical understanding improved minimally. Qualitative feedback highlighted students’ surprise and appreciation for using AI professionally. If expanded to all sections, the project will impact more than 200 students per year across three majors. The intervention underscores AI’s potential role in disease surveillance, health communication, and equity-focused interventions, aligning with CEPH and CAHME competencies (Appendix 1). Lessons for health promotion pedagogy emphasize that integrating AI enhances technical literacy while reinforcing community engagement and evidence-based practice. Future iterations could strengthen ethical focus and diversify AI tools to address remaining gaps.

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Publication Details

Journal
Pedagogy in Health Promotion
Published
2026-11-03
DOI
https://doi.org/10.1177/23733799261499988
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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article

Teaching AI Literacy for Public Health Practice

Amanda W. Scarbrough, Christine Cardinal, Stephen L. Brown
Pedagogy in Health Promotion
Artificial Intelligence in Healthcare and Education
article

Teaching AI Literacy for Public Health Practice

Amanda W. Scarbrough, Christine Cardinal, Stephen L. Brown
article en

Abstract

This study evaluated an AI-driven assignment in an undergraduate public health course to enhance AI literacy among students preparing for health-related careers. Amid growing AI use in academia—and uncertain ethical perceptions—the project addressed the need for responsible AI application in public health and healthcare management education. Designed with constructivist strategies (experiential, inquiry-based, project-based, and collaborative learning), the assignment tasked student groups with creating AI-scaffolded community health promotion plans. Implemented in online sections, the project leveraged tools such as ChatGPT and ClaudeAI for data analysis, decision-making, and communication material development. Pre- and post-curriculum assessments, using the Meta AI Literacy Scale (MAILS) , showed significant gains in overall AI literacy, particularly in confidence, and evaluation skills, though ethical understanding improved minimally. Qualitative feedback highlighted students’ surprise and appreciation for using AI professionally. If expanded to all sections, the project will impact more than 200 students per year across three majors. The intervention underscores AI’s potential role in disease surveillance, health communication, and equity-focused interventions, aligning with CEPH and CAHME competencies (Appendix 1). Lessons for health promotion pedagogy emphasize that integrating AI enhances technical literacy while reinforcing community engagement and evidence-based practice. Future iterations could strengthen ethical focus and diversify AI tools to address remaining gaps.

Pedagogy in Health Promotion
Sam Houston State University (US)
Openalex Percentile: Top 22%
Artificial Intelligence in Healthcare and Education
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Teaching AI Literacy for Public Health Practice — Amanda W. Scarbrough, Christine Cardinal, et al. · Pedagogy in Health Promotion (2026) | TGRS Research Map | TGRS