Faculty Use

Teaching

Generative AI can also be used to enhance and support teaching. Here are some of the many ways that instructors can incorporate generative AI tools into their teaching:

  • Write student learning objectives
  • Create syllabus outlines
  • Write syllabus policy statements, including about use of AI
  • Draft lesson plans and outlines
  • Write lecture notes and slides
  • Create graphics (e.g., tables, graphs, flow charts, and diagrams)
  • Generate responses to common student questions or emails
  • Create student feedback forms
  • Generate feedback comments to create a comment bank for assignments
  • Create test questions
  • Create multiple-choice question answer options
  • Write rubrics for grading
  • Write study materials for students
  • Generate FAQs with explanations for concepts
  • Develop classroom activities and exercises
  • Generate discussion prompts or questions for classes
  • Generate role playing scenarios and simulations
  • Create practice questions for quizzes or tests
  • Create sample problems
  • Create assignments
  • Write assignment instructions
  • Create step-by-step guides and checklists for student projects
  • Create examples for students to analyze and critique
  • Provide high-quality examples as models

Sources

Cornell University Center for Learning Innovation Generative Artificial Intelligence

Cornell University Center for Teaching Innovation Cornell University Committee Report: Generative Artificial Intelligence for Education and Pedagogy

University of Pittsburgh University Center for Teaching and Learning Generative AI: Teaching with Generative AI

University of Southern California Center for Teaching Excellence AI Tools for Course Design

Portland State University OAI+ Generative AI: A Teaching and Learning Primer

Mollick, E., and Mollick, L. (2023) Student Use Cases for AI

Research

Faculty can also use generative AI as an aid in their own research. For example, they can ask AI to help them do the following:

  • Summarize written material
  • Brainstorm ideas
  • Develop a work plan with a timeline
  • Develop and refine research questions
  • Create an outline
  • Critique a draft
  • Edit and proofread a draft
  • Create presentations

Several universities have developed recommendations and guidelines for Generative AI use in research. They specify acceptable and unacceptable applications and emphasize the need for transparency about its use as well as caution regarding its limitations. Concern cited involve accuracy or bias and issues involving authorship and intellectual property rights such as copyright and data privacy.

Sources

University of Michigan Institute for Data Science Using Generative AI for Scientific Research

Brown University Help Center Generative AI as a Research Tool

University of North Carolina Office of the Provost Generative AI Usage Guidance

University of Kentucky ADVANCE Recommendations on the Use of Generative AI in Research and Scholarly Activity

Gen AI Prompts

In the context of generative AI, prompts refer to the information or questions entered into a Generative AI tool in order to get a response. The characteristics of the input influences the quality of the information received in the output. Prompt engineering is the process of refining a generative AI prompt to improve its accuracy and effectiveness.

Harvard University Information Technology Getting Started with Prompts
This post provides a guide for how to generate better prompts. It lists considerations such as being specific, specifying how output is to be presented, providing examples, addressing tone and audience, and giving feedback.

University of Michigan Generative AI Resources Prompt Literacy in Academics
This entry also lists parameters of effective prompts, including being specific and detailed, using iterative refinement, tailoring to your audience, pointing out mistakes, referencing examples, avoiding confusing terms, and requesting alternative outputs.

Montana State University Center for Faculty Excellence How to Write Effective Prompts
This entry lists the following recommendations for writing effective prompts:

  • Be as specific as possible about the topic and contextualize it with audience, tone, and/or timeframe.
  • Use an iterative approach to refine the output for more useful information.
  • Add an action or task for generative AI to complete: Ask generative AI to summarize, outline, list, plan, compare, predict.
  • Set parameters: Word count, exclusions, text with subheadings, paragraphs etc.
  • Avoid Bias: Bias occurs due to people’s preferences, prejudices, and stereotypes and can emerge as a result of how you phrase your prompts. If you ask a question in a leading way, it will produce a biased answer.

MIT Sloan School of Management Teaching & Learning Technologies Effective Prompts for AI
For getting the best results, this site recommends providing context, being specific, and building on the conversation. It points out three limitations of using prompts with generative AI and lists references.

Open AI Prompt Engineering
This site provides six strategies for getting better results with prompts (a) use clear instructions, (b) provide reference texts, (c) split complex tasks into simpler subtasks, (d) give the model time to “think”, (e) use external tools, and (f) test changes systematically. It also provides specific tactics for each strategy.

Teach for Tomorrow AI for Education
This site offers webinars on demand, a prompt library, and other resources, including effective prompting for educators and the five “S” model for teachers.

Ivan Allen College of Liberal Arts Georgia Tech University Prompt Engineering
This article provides examples of creating prompts using three approaches: the rhetorical approach, the C.R.E.A.T.E. framework, and the structured approach to prompt engineering.

Jake Siegel The Art of the Prompt
This is a PowerPoint Presentation on “how to get the best out of generative AI.” It states principles for creating prompts and gives examples of their use.