AI Resources for Faculty
Explore teaching guidance, course design support, classroom use, and academic resources.
For the most current syllabus templates, visit the Office of the Provost site. Faculty are encouraged to add domain-specific modifications to these templates. As examples, computer science instructors may want to require or restrict code generators (e.g. Claude Code), and visual arts instructors may want to require or restrict image generators (e.g. DALL-E).
More broadly, every course syllabus must clearly state the course's AI Status (i.e., Fully Human-Centered, Human-Directed w/AI Assistance, or AI-Produced, Human-Guided):
Fully Human-Centered
- NO GenAI USE: GenAI is not permitted. Faculty should clearly address embedded AI tools, like grammar check.
- For example: baseline assessments, handwritten exams, anything else as determined by faculty/managers
Human-Directed with AI Assistance
- SOME GenAI USE: AI may be used as a basic search engine or "sounding board" to gather information or organize thoughts.
- GenAI may be used as a primary collaborator but the human acts as the editor.
- For example: writing edits, literature reviews, assisted research, drafting emails, writing basic code, creating basic visual assets to be used within a larger project
AI-Produced, Human-Guided
- SYSTEM-LED GenAI USE: AI may be used to perform the task with the human guiding or overseeing the process.
- For example: automation, prediction, generation of final product, data analysis
The Use of Generative Artificial Intelligence (AI)
In alignment with Hood College's broader AI policy, the Graduate School recognizes the evolving landscape of generative artificial intelligence (AI) tools and their increasing use in higher education. Certain uses of such tools may be suitable to support and enhance scholarly activities in certain disciplines or in specific courses, assignments and projects. At the same time, there are significant unresolved legal and ethical considerations about the use of these tools with respect to privacy, copyright, authorship and intellectual property that have direct academic integrity implications. Faculty and students are expected to maintain the highest standards of academic integrity and transparency in all scholarly activities, whether generative AI tools are used or not. Decisions, attribution and any guidance regarding the use of such AI tools rest with the course instructor and may vary according to the course activity within the context of a given discipline. Failure to comply with course AI policies/allowances, which includes improper citation, will result in consequences outlined in the Violations of Academic Conduct policy.
- Robert Kambic, Biology: I use AI methods (neural networks) in my research for automatic video tracking/pose estimation for human subjects. Students who do research with me learn how to use these tools.
- Lisa Algazi Marcus, Global Languages/Honors: Because students learn from formulating their thoughts and expressing their ideas, I have altered many of my assignments to make them more difficult to complete using AI. For example, instead of asking students to post reading responses in writing, I am asking them to post one-minute videos reacting to the readings. For my French language classes, I am now asking students to write short compositions during class time, using paper dictionaries, to avoid the use of online translation software. While such software can be useful for communicating in writing, using it does nothing for students' language proficiency, which improves through trying, and sometimes failing, to communicate in the target language. In all my classes, I value in-person human interaction that helps students learn the skills that employers want: criticial thinking, communication, and the ability to think on their feet.
- Jason Miller: My field is computer science. I created, trained, and evaluated AI models for four recent journal papers. I teach an AI course in which master's students build or fine tune image classifiers and language generators. Nevertheless, I believe commercial LLM services are detrimental to teaching and learning. AI certainly improves productivity; my students now write perfect term papers and give perfect slide presentations! That says students do not need AI training. In contrast, when I emphasize technology (Blackboard AI Conversation or ChatGPT or Google search or YouTube or TikTok) rather than the textbook for a learning module, most students fail the paper test. As Yale professor Meghan O’Rourke recently wrote in the NY Times, the technology we should teach our students to use well is called the book.
Heather Mitchell-Buck (English) - As Hood’s Digital Learning Coordinator, I’m always thinking about ways that technology can improve access and improve the ways that we teach and learn on our campus and in our world. We talk a lot in my classes about the prevalence of “AI” in our world. An important point on which all of us need to be clear - and one I emphasize with all of my students - is that not everything that is called “AI” is the same in terms of scope and mission. There are many effective and important uses of machine learning out there, and those are distinct from the LLMs (ChatGPT, Gemini, etc) and “generative AI” platforms that students are familiar with. Many of our students have deep concerns about the ethical and environmental costs of “AI” use as well as the ways that corporate investments in this sector have had negative impacts on the job outlook for college graduates around the country and around the world. To that end, the projects in my classes encourage students to cultivate their genuine human skills and abilities and to lean into the desire for authenticity that many people are feeling in response to the current push to “AI”-ify everything. Students really appreciate this approach; I think it’s important for this side of the conversation to be part of their education in digital literacy.
- Beth Kiester (Sociology/Social Work) I have asked students to use GenAI to create a paper of some sort. Then they must grade that paper using a rubric I provide with detailed explanations about why they are grading the way they are. Then they have to write a reflection paper about the use of AI. I have also allowed students to use GenAI to create images that represent a course concept. They must explain the prompt(s) they used to get to their final image. They must also explain why they feel the image is a good representation of the concept. I've also developed lectures on the pros and cons of Gen AI, acceptable and unacceptable use, ethical dilemmas, environmental concerns, and identity biases. Most recently, I have had my classes create course policies about how and when the use of GenAI is allowed and when it is not. I recognize GenAI isn’t going away so am trying to adapt and help students continue to learn important critical thinking skills but also the appropriateness of using these new tools.
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For examples of faculty use cases, visit University of South Florida
From machine learning to natural language processing, our faculty experts are at the forefront of cutting-edge AI research. Here are a few of our faculty experts engaged in AI with their research, teaching and consulting endeavors:
- George B. Delaplaine Jr. School of Business
David Gurzick, Ph.D.
Teaches AI-related badges and coursework, consults on AI projects and named a top five AI developer by CIOR magazine.
- Computer Science & Information Technology
The faculty members listed below teach AI-related courses and are actively involved in AI research.
Shahinur Alam, Ph.D.
Aijuan Dong, Ph.D.
Carol Jim, Ph.D.
Randy Johnson, Ph.D.
Jiang Li, Ph.D.
Jason Miller, Ph.D.
Ahmed Salem, Ph.D.
Cheng Qian, Ph.D.
- Education
Marisel Torres-Crespo, Ph.D.
Teaches AI-related coursework and leads faculty AI training workshops
- AI Related Research Grants
- Building a Regional AI Community Through Collaborative Research and Traineeship with Lawrence Berkeley National Laboratory (DE-SC0025718), Department of Energy, $150K (PI: Aijuan Dong, Co-PI: Cheng Qian)
- PI, National Science Foundation (NSF) Grant, “Collaborative Research: IUSE: EDU: Curriculum Development for Edge Artificial Intelligence with Hands-on Laboratory,” $95K, (Cheng Qian)
The following free resources can help faculty, staff, and students build practical AI skills. No LinkedIn Learning account is required. Some Microsoft resources may require signing in with your institutional Microsoft account, and available features may vary based on licensing.
Start Here: AI and Copilot Basics
| Resource | What It Does | Best For |
|---|---|---|
| Get Started with Microsoft 365 Copilot Chat | Introduces Copilot Chat, how to access it, when to use web/work grounding, and how to keep data safe. | Faculty, staff, students |
| Start Your AI Journey with Microsoft 365 Copilot Chat | Step-by-step Copilot activities for writing, summarizing, organizing, researching, and communicating. | Beginners |
| Craft Effective Prompts for Microsoft 365 Copilot | Teaches how to write clearer prompts and get better results from Copilot. | Everyone |
| Microsoft Copilot Prompt Gallery | Provides ready-to-use prompts by task, app, and work function. | Everyone |
| OpenAI Academy | Free learning hub with AI literacy videos, workshops, and practical training. | Everyone |
| Anthropic Courses | Free AI fluency and Claude courses, including tracks for students, educators, builders, and professionals. | Everyone |
Campus Resources
| Resource | What It Does | Best For |
|---|---|---|
| Tidball Center for Teaching and Learning | Connects faculty with teaching support, professional development, instructional guidance, and campus-based resources for effective teaching and learning. | Faculty, instructional staff |
| Instructors' Guide to Generative AI | Provides Hood-specific guidance for instructors exploring generative AI, including teaching considerations, responsible use, and academic integrity support. | Faculty, instructors |
Faculty Specific
| Resource | What It Does | Best For |
|---|---|---|
| Human Wisdom for the Age of AI: Teacher's Guide Learning Modules | Free Elon University teaching modules connected to the Student Guide to Artificial Intelligence, helping instructors lead conversations about AI, human skills, ethics, and learning. | Faculty, first-year seminars, advisors |
| AI Fluency for Educators | Free course on applying AI fluency to teaching, course design, and institutional strategy. | Faculty, instructional designers |
| Vanderbilt Faculty AI Toolkit | Offers teaching checklists, syllabus guidance, class prep prompts, tool comparisons, and discipline-specific guides. | Faculty |
| Vanderbilt Course Design and Teaching Practices | Helps faculty connect AI use to learning goals, active learning, scaffolding, and assessment design. | Faculty, instructional designers |
| Google AI Educator Series | Free micro-trainings for K-12 and higher education educators, developed with ISTE+ASCD. | Faculty, teacher education |
| UNESCO AI Competency Framework for Teachers | Framework for responsible AI knowledge, skills, values, and teacher development. | Faculty development, academic leaders |
| EDUCAUSE AI Events and Trainings | Higher-ed AI training on teaching, instructional design, staff work, and leadership. | Faculty, instructional staff, leaders |
These resources are provided for learning and exploration. Do not enter protected student information, confidential institutional data, personnel records, or sensitive personal information into any AI tool unless it has been approved by the institution for that type of data.
- Keynote Presentation: AI With Purpose
- Prompt Library
- Workshop 1: Assessment Redesign and Academic Integrity
- Workshop 2: Daily Workflow with Co-Pilot
- Workshop 3: Chatbots for Student Success
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