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Artificial Intelligence Resources

Generative Artificial Intelligence Resources

Generative AI (Gen AI) “should be used as a supplement to rather than a replacement for human expertise and judgment” (Bhattacharya et al., 2023).

The purpose of this resource page is to assist faculty in considering the best way to invite Gen AI into their teaching. However, faculty should be aware of Gen AI’s limitations and rely on their own expertise when using it.

What is Generative Artificial Intelligence?

According to TechTarget, “artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems.”  Generative AI (Gen AI) platforms such as UT Verse, ChatGPT, Google Gemini, and Microsoft Copilot are large language models trained on specific information to imitate human language and cognitive processes such as problem-solving and decision-making. “It works by finding and replicating the most common patterns in speech available in its dataset” (Alqurashi & Zaylea, 2023). Gen AI then uses these patterns and information to respond to questions and prompts by creating written responses, having conversations, creating images, analyzing data, etc. Depending on the quality of prompts and specific platform utilized, the outputs can include a variety of formats such as text, images, video, audio, and code.

While Gen AI platforms can produce responses within seconds, there are several issues that may arise from its use. Responses, which mimic human conversation, can sound authentic but may contain “hallucinations” or factual errors prompting the necessity to examine them for accuracy. Gen AI may also construct responses that contain biased information emphasizing the importance of critically evaluating the outputs. Using Gen AI can present ethical concerns when inappropriately used including academic honesty, plagiarism, and authorship, as AI responses cannot be identified by detection software. These issues stress the importance of discussing Gen AI use with students emphasizing responsible usage of the platforms.

Types of Generative AI

Explore Generative AI tools that are available within the UT Health Science Center Ecosystem:  

  • UT Verse is the University of Tennessee’s “chat-based, AI-powered platform”. It has been trained on the GPT 4 platform for Microsoft Azure OpenAI. Data entered into the platform and responses created are not shared to those outside of UT.

  • Copilot is a chat-based “AI-powered platform developed by Microsoft. When you log into Copilot with your UT email address and password, you can use a protected version of the platform where the data entered and responses created are not shared to those outside of UT. Co-Pilot can also generate images.  

  • Adobe Firefly, part of the Adobe Creative Cloud, allows users to turn text descriptions into images.

  • Explore additional Gen AI models and tools collected by the University of Michigan.

How can faculty use Gen AI?

AI Decision Tree

  • A guide by Temple University to help you determine if you should allow students to use Gen AI.

  • A guide developed by Oregon State University to help you decide when and how to incorporate Gen AI into your work.

Learning Activities

  • Generate authentic scenarios for case-based, team-based, or problem-based learning experiences; based on cases have students create a differential diagnosis, identify diagnostic testing or management or treatment options, etc. This allows you to assess student’s critical thinking and reasoning skills and provide feedback when necessary.

  • Generate arguments for both sides of an issue and have students evaluate the rigor of the argument or appropriateness of responses.

  • Enhance communication to describe difficult concepts in laymen’s terms, tailor communication and instructions to patients and families, and provide translations.

  • Simulate a patient encounter: have Gen AI imitate a patient and have student ask appropriate questions for patient interviews, histories, and physicals.

  • Develop a list of health controversies for students to debate and discuss.

  • Reflect on AI response: have students revise, rewrite, critique, fact check, compare human creation to AI generated, or expand upon.

  • Provide students with prompts to enter into Gen AI to prepare for class.

  • Have students write a case scenario based on questions created by Gen AI.

Teacher Resources

  • Generate additional learning resources to help students learn concepts.

  • Draft course descriptions, learning objectives/outcomes, curriculum development, syllabus, course outlines, rubrics, and assessments.

  • Create practice questions, e.g., multiple choice, short answer, etc. based on specific exam formats.

  • Create reading passages with corresponding questions.

  • Generate writing prompts.

  • Create discussion questions that align with lecture content.

  • Summarize complex topics/concepts.

  • Generate list of teaching methodologies for teaching a specific topic.

  • Generate examples, explanations, and analogies for topics.

Research Assistance

  • Revise or proofread written projects.

  • Brainstorm research topics, ideas, issues, search terms.

  • Use Gen AI as a starting point to gather relevant information about a topic.

  • Conduct literature search (be sure to double check its accuracy).

Syllabus Statements

How to create prompts? 

Prompts are the questions and/or statements users enter into the Gen AI platform for it to generate a response. The prompts or questions should be specific; the more specific the prompt, the more useful the response may be. The quality of output relies heavily on the prompt or question asked. When writing prompts consider using the framework: Role (act as), Task (create a), Requirements (be sure to), and Output (turn into). Another framework recommended by Ethan and Lilach Mollick includes giving Gen AI a role, clear instructions, e.g., context and perspective, examples, and steps. After the initial prompt and response are generated, follow-up prompts or questions may be needed to refine the results.  

Prompt Examples:

  • You teach 2nd year medical students. Write a 6-week outline for a course on the Social Determinants of Health. Make sure to include lecture topics, readings, assessments, and engaging learning activities.
  • You are an educational researcher who wants to explore student pharmacists’ perceptions of a simulation activity. Suggest three areas of simulation in pharmacy education that are currently unexplored and explain why they are important.
  • You are an experienced faculty teaching first year dental students and are developing an introductory course on oral diagnostics. Write a simulation activity that includes the students providing patient care to a standardized patient. Make sure to include taking a dental and medical history, taking and interpreting x-rays, and oral exam.
  • You are an experienced nursing faculty who is teaching a course on pediatric and adolescent nursing concepts to 2nd year BSN students. Write 5 NCLEX style questions that include patient cases and questions that test students’ clinical reasoning and diagnostic skills. Make sure to include rationales for correct and incorrect answers.
  • You are a physical therapy faculty teaching a course on gross anatomy for physical therapists. Write 5 learning objectives based on Bloom's Taxonomy for this course. Make sure to include higher order thinking skills.

Practical AI for Instructors and Students Part 3: Prompting AI YouTube Video 

UT ITS Writing Prompts

Prompt Literacy in Academics by the University of Michigan

How do faculty mitigate the use of Gen AI?

Class Strategies

  • Set clear expectations around AI & academic dishonesty​.
  • Prompt learners to make their thinking known​, e.g. text annotation, scaffolded assignments, mind mapping, document history tracking.
  • Use authentic assessment strategies​.
  • Triangulate assignments with AI software​.
  • Create assignments that are personally relevant, e.g., reflections and portfolios.
  • Create assignments that reference content specifically from lecture or class discussions.
  • Engage students during in-class discussions.

Detection Tools

One of the ethical issues that arises from using Gen AI is the potential for plagiarism. One avenue that faculty have taken to identify plagiarism is employing detection software such as Turnitin. While there are Gen AI detection tools available, they are not reliable in distinguishing between human and AI generated texts. Currently, these tools frequently result in false positives and negatives indicating that they are not the best solution.


100+ Creative Ways to Use AI in Education

AI Guide by Harvard University

Brainstorming Tool: Educators can use this tool to brainstorm learning objectives, lecture topics, discussion questions, and case studies.

Generative AI Primer from the National Centre for AI

Getting Started with Generative Artificial Intelligence: U of M Instructor Guide

MedEd Mentor: AI for MedEd Research

Practical AI for Instructors and Students: 5 videos created by Ethan and Lilach Mollick from the Wharton School of the University of Pennsylvania

Temple’s Survival Guide to AI and Teaching

TeachOnline.CA: Resource hub about Generative AI in higher education 

University of Michigan’s Book Guide for Chatbot Assignments: 60 assignment examples with prompts 

University of North Carolina Chapel Hill Generative AI Resources

UT Health Science Center Policy on Acceptable Use of Generative AI written by the Office of CyberSecurity

UT Health Science Center ITS Generative AI information page


AI Guide by Harvard University

Alqurashi, E., & Zaylea, J. (2023). Survival guide to A.I. and teaching pt.1: What is generative A.I.?. Center for the Advancement of Teaching, Temple University.

Bhattacharya, K., Bhattacharya, A.S., Bhattacharya, N., Yagnik, V.D., Garg, P., & Kumar, S. (2023). ChatGPT in surgical practice: A new kid on the block. Indian Journal of Surgery, 85, 1346-1349. 

Bowen, J., & Watson, C.E. (2024). Teaching with AI: A Practical Guide to a New Era of Human Learning. Johns Hopkins University Press. 

Temple’s Survival Guide to AI and Teaching

Vargas-Murillo, A.R., de la Asuncion Pari-Bedoya, I.N.M., & Guevara-Soto, F.J. (2023). Challenges and opportunities of AI-assisted learning: A systematic literature review of the impact of ChatGPT usage in higher education. International Journal of Learning, Teaching and Educational Research, 22(7). 122-135. (I have this article as a PDF)

10 examples of assignments


May 7, 2024