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Teaching microbiology with generative AI: a survey-style playbook to empower microbiology faculty to integrate AI
Kara Mosovsky1,2, J Jordan Steel1, Michael Barnhart1
1Department of Biology, United States Air Force Academy, Colorado Springs, Colorado, USA.
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. By ensuring an approach that safeguards critical thinking, scientific reasoning, and academic integrity, this guide, which includes example prompts and concrete use cases, will not only empower microbiology faculty to lead the AI transition in academia but will also cultivate and nurture essential AI literacy and fluency needed in the future scientific workforce.
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