This collection of resources is meant to support faculty who are interested in learning more about and responding to generative artificial intelligence (genAI) technology in the classroom.
We are happy to add additional resources here and would love your feedback. For any comments or suggestions please email Lauren Mitchell Nahas (lnahas@santarosa.edu).
Introductory Resources: What is Generative AI?
The first step to responding to generative AI in your classroom is to understand how these technologies work and what they are capable of. Browse the resources below to get a basic introduction to generative AI.
- The video to the right gives a brief but thorough overview of how technologies like ChatGPT actually work.
- Introduction to AI for Teachers and Students, by Ethan Mollick (Faculty Director of Wharton Interactive) and Lilach Mollick (Director of Pedagogy), Wharton School, University of Pennsylvania
- This YouTube playlist is a great place to start. The Mollich's are considered two of the key voices on AI and higher ed.
- What is Generative AI, University of Pittsburg
- A quick overview, discussion of limitations and capabilities, and a list of different generative AI tools.
- Key Terms:
- A Very Gentle Introduction to Large Language Models without the Hype, Medium — In-depth (but reasonably short) definitions of key AI terminology for folks without a Computer Science background. Plus, helpful visuals. Covers large language models, machine learning, neural networks, etc.
- The Ultimate AI Glossary — Quick definitions of a wider range of AI terms, concepts, and phenomena.
Infographic text of "What is my position on AI use."
Responses to Generative AI in the Classroom
The resources below provide ideas and methods to modify assessments or use alternative assessment methods in response to generative AI.
- Embrace the Bot: Designing Writing Assignments in the Face of AI, Faculty Focus — Presents three different responses to generative AI, geared mainly towards writing assignments.
- ChatGPT Comes to CUNY Writing Classes, CUNY Graduate Center News — Writing instructors who incorporated generative AI into their courses share their experiences and takeaways.
- Learning That Matters Resources — Resources and ideas from the authors of Learning That Matters: A Field Guide to Course Design for Transformative Education
- Equitable Grading Strategies: Finding new ways to think about assessment, @ONE — A four-week course that guides participants in exploring alternative grading strategies.
- Mastering Assignment Makeovers to Enhance Instruction, Dr. Derek Bruff — This presentation focuses on shifting to authentic assessment and provides resources and examples.
- Assessment Ideas Factory, University of Queensland — A database of assessment ideas.
Syllabus Policies and Strategies to Support Academic Integrity
- 10 Tips to Increase Academic Integrity, UC San Diego, Academic Integrity Office — This resource provides "common-sense" strategies that often get overlooked.
- Generative AI in the Syllabus, Dr. Tamara Tate, UC Irvine, Department of Education — A guide to creating your course policy, with examples.
- Sample Syllabus Policy Statements, University of Texas at Austin, Center for Teaching and Learning
- Crafting Your GenAI & AI Policy: A Guide for Instructors, UC San Diego, Academic Integrity Office — A very comprehensive "choose your own adventure" resource that covers generative AI basics, revising SLOs, revising and securing assessments, and policy creation.
- AI & Authentic Assessment: Towards a Coherent Approach, SRJC's PDA Spring 2024 — This workshop briefly covers AI syllabus policies and focuses on examples of authentic assessments and EdTech tools as a means to encourage academic integrity.
Generative AI Detection Tools
Currently, SRJC currently has a license for Turnitin's AI detection tool. However, AI detection tools have been found to produce false-positives. Most colleges advise that AI detection tools should not be relied upon as the only form of evidence of academic dishonestly. Of the three example policies on AI detection, the first suggests additional factors that should be considered in addition to a positive AI detection results. The second and third are examples of policies that do no recommend the use of AI detection tools.
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Addressing Artificial Intelligence, Washington University in St. Louis
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Statement about AI Detection Tools, University of Pittsburg
- Statement on Turnitin's AI Detection Tool, UC Berkeley's Research, Teaching and Learning Services
Deeper Conversations
The following resources discuss the impact of generative AI more broadly. Additional suggestions for this section are welcome.
- How to Talk to Faculty about AI without Starting WWIII, Daniel Stamford
- Offers thoughtful questions that can be helpful for departmental or college-wide discussions.
- What might ChatGPT mean for higher education?, Future Trends Forum
- A panel discussion with academics from various disciplines considering the impact of generative AI broadly.
- How AI is Impacting Higher Education, Teaching Higher Ed
- An interview Cynthia Alby, author of Learning that Matters: A Field Guide to Course Design for Transformative Education
- Is A.I. the Problem? Or Are We?, The Ezra Klein Show
- An interview with Bryan Christian, author of The Alignment Problem, which discusses the key technical and moral questions of AI.
- An interview with Bryan Christian, author of The Alignment Problem, which discusses the key technical and moral questions of AI.
