Generative AI-driven algorithm and rule development using Google Gemini (Gems) by creation and use of a clinical microbiology course tutorbot
Project Overview
The goal of this project is to engage medical laboratory science students in
generative AI-driven algorithm and rule development using Google Gemini (Gems) by
creation and use of a clinical microbiology course tutorbot. Using the Gemini Gems platform, students will be asked to practice instructor-facilitated rules and algorithms to train Gemini Gems to serve as a Socratic-method tutorbot. While not directly related to the commercial vendor AI tools used within the clinical microbiology laboratory, training a tutorbot in the clinical microbiology course allows students to develop practice rule/algorithm prompts, under instructor supervision, with defined UMN rules and regulations, whereby creating a “safe space” to experience emerging AI technology.