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Teaching microbiology with generative AI: a survey-style playbook to empower microbiology faculty to integrate AI into courses

Kara Mosovsky, J. Jordan Steel, Michael Barnhart · Journal of Microbiology & Biology Education · 2026

ABSTRACT Generative artificial intelligence (GenAI) has reached a critical inflection point in STEM education, presenting a challenge to traditional assessment but also an unprecedented opportunity for instructional innovation. For microbiology faculty who often manage a substantial operational load of lecture and laboratory preparation, GenAI can be a powerful tool to increase efficiency, student engagement, and comprehension, while maintaining educators’ high standards for quality instruction. This article provides a survey-style playbook of GenAI applications categorized into two frameworks: AI assisting with course design and organization (instructor-focused) and AI assisting with student-learning (student-focused). Instructor-focused use cases include streamlining course design through student-friendly syllabus summaries, organizing laboratory supply logistics, and generating custom visuals for complex microbial processes. Student-focused activities rely on active learning, such as “interviewing” historical figures or pathogens through role-play and receiving real-time feedback on technical skills like streak plates.

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