LibGuides: Generative AI & Higher Ed: Instructor Resources

Teaching Resources

The resources below are intended to help instructors discuss AI with students and teach them about ethical AI use.

AI & Information Literacy Canvas Module: A 1-2 hour module explaining how AI works, the risks of using AI, and how to evaluate AI answers for accuracy and bias.
DePaul University's Guide to Teaching AI: A comprehensive guide to AI in higher education that includes assignment and activity ideas.
University of Virginia's Generative AI in Teaching Guide: Subject specific guides for leveraging AI tools and mitigating risks in teaching and instruction.
Guide for Integrating AI Considerations into Courses: A step by step guide for getting familiar with AI and assessing how AI would interact with your assignments.
Designing Assignments to Integrate and Engage AI: Strategies for implementing AI in assignment design.
Ethical Framework for AI in Education: a framework proposed by the Institute Ethical AI in Education that seeks to enable all learners to benefit from AI in education, while also protecting against the known risks this technology presents.
Northwestern University Heuristic for Designing Learning Experiences with Generative AI
MIT Guide to Teaching AI

Syllabus and Policy Resources

Drafting Syllabi Policies for AI Generative Tools: A multidisciplinary collection of syllabi policies created by instructors at other institutions.
A Collection of university and college AI policies and websites
Sample AI Course Policies from University of Oregon
"Should You Add an AI Policy to Your Syllabus?" Chronicle of Higher Education (Kevin Gannon, 7/31/23)

AI Literacy Resources

Introduction to AI Literacy Moodle Module: A Moodle course module developed by Rush University that covers four categories of AI Literacy: Awareness of AI, AI Capabilities, Knowledge of AI Models, and Critical Thinking.
- Form to request editable access to AI Literacy Moodle Module
Framework for AI Literacy created by Melanie Hibbert, Elana Altman, Tristan Shippen and Melissa Wright
AI Literacy Resource Hackathon: This project developed by Carnegie Mellon University includes a variety of open educational resources related to AI literacy including fliers, prompts, and lesson plans.
Barnard College Center for Engaged Pedagogy Instructor Resources for AI: Includes recommendations representing ongoing research into generative AI and its implications in the higher education classroom, with ideas for classroom activities, assignment design, and academic honesty and ethical considerations.

ABC's of AI Decision Making

The questions below were developed by Courtney Plotts and Lorna Gonzalez and are designed to help faculty and staff in higher education navigate AI use and decision making. Some questions are intended for personal reflection, while others look at broader educational contexts. Plotts and Gonzalez employed a culturally aware perspective to this framework to address issues of bias in AI technologies.

Application

Has the AI application been thoroughly assessed for potential biases?
Compared to the accessibility and efficiency benefits, are the biases in the AI application acceptable or concerning?
Are these biases causing harm or inequity in the outcomes of the output or recommendations of the AI?
Are adequate steps being taken to mitigate biases and ensure fairness in the output of the AI?
Might marginalized or underrepresented groups be disproportionately affected by any biases in the AI application?
Does the AI application contribute to a more equitable and inclusive environment, or does it inadvertently reinforce existing biases?

Benefits versus Biases

How critical is the application of the AI software for the current needs, and does it significantly enhance individual productivity or the user's experience and intended goals?
Has the AI software been thoroughly evaluated for potential biases and the impact of the AI on decision-making?
Could alternative AI solutions achieve similar benefits while minimizing biases?
What are the ethical implications of using AI software that may contribute to biases or negative impacts on certain groups or individuals?
Does the application of the AI software align with the leader's personal values and ethical standards, or should the leader's beliefs about AI and biases be reassessed?
Does the application of the AI software align with the stated values and ethical standards of the institution?

Content and Context

In considering the use of AI for production tasks, have specific processes or tasks been identified that can be automated to increase efficiency?
Is the AI tool suitable for providing accurate explanations and insights in areas that might be challenging to grasp?
Is the output of the AI reliable and trustworthy in terms of ensuring the quality of the final product or result?
Are there scenarios in which AI can help optimize resource allocation, such as scheduling, resource utilization, or cost management?
How can AI be leveraged to provide personalized recommendations for equitable skill development and continuous improvement?

Published in "Creating a Culture Around AI: Thoughts and Decision-Making" EduCause (Plotts and Gonzalez, 4/22/24)

Determining AI Use in Classes

Recommendations

Generative AI is changing rapidly, so feel free to contact us with suggestions or updates for this guide. You can also contact us to request librarian-led programming on Generative AI that explores ethical uses for generative AI and its limitations. Contact us at libref@beloit.edu.