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Elon University & AACU: 2025 Student Guide to Artificial Intelligence

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Elon University & AACU: 2025 Student Guide to Artificial Intelligence

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Student Guide to Artificial Intelligence

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Homepage - Student Guide to Artificial Intelligence

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Learn about Artificial Intelligence (AI) and how it’s transforming higher education. This guide explores what AI is, its applications, and how it’s shaping careers.

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Digital Education Council: Empowering Faculty to Experiment, Share and Learn: Advancing AI Literacy in Higher Education

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Digital Education Council: Empowering Faculty to Experiment, Share and Learn: Advancing AI Literacy in Higher Education

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Empowering Faculty to Experiment, Share and Learn: Advancing AI Literacy in Higher Education

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Carnegie Learning: The State of AI in Education 2025 (PK-12 National Study)

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Carnegie Learning: The State of AI in Education 2025 (PK-12 National Study)

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AI in Education Survey Report & Virtual Event | Carnegie Learning

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Our second annual AI in Education survey yielded some surprises! Find out how AI use has evolved for administrators and teachers over the past year.

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University of California-Irvine: AI Feedback and AI literacy 

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University of California-Irvine: AI Feedback and AI literacy 

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Generative AI represents a powerful tool for transforming how people teach and learn. The UCI is carrying out research and development to ensure that the disruptive power of generative AI is harnessed for beneficial ends.We view AI literacy as a vital component of digital literacy, encompassing understanding, accessing, prompting, corroborating, and incorporating AI-generated texts -- and we view these new forms of AI literacy as a key element of instruction for writing, programming, and STEM problem-solving. With funding from the National Science Foundation, UCI Beall Applied Innovation, and the Learning Agency, we are iteratively developing an instructional AI platform, Digital Learning Lab PapyrusAI, and researching its use in K-12 and college classrooms.

​

Human-Driven Generative AI Use

Human-Driven Generative AI Instructional Framework (Warschauer et al., 2023)

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Generative AI Changes What and How People Learn

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University of California-Davis: AIRR (Peer and AI Review + Reflection

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University of California-Davis: AIRR (Peer and AI Review + Reflection

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Peer & AI Review + Reflection (PAIRR) is a five-part curricular intervention: 1) Students discuss and reflect on short readings on AI. 2) They complete peer review of draft writing assignments. 3) They prompt an AI tool to review the same drafts, with instructor guidance on privacy settings. 4) They critically reflect on and assess both types of feedback, considering their goals and audience(s), and 5) They revise.

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The University of Texas at San Antonio: Founding Dean, College of AI, Cyber and Computing

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The University of Texas at San Antonio: Founding Dean, College of AI, Cyber and Computing

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Founding Dean, College of AI, Cyber and Computing - San Antonio, Texas job with The University of Texas at San Antonio | 3316319

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The University of Texas at San Antonio seeks a Founding Dean, College of AI, Cyber and Computing

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Ina Wanca, Chief Academic AI Officer at CUNY – Bronx EdTech Showcase

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Ina Wanca is a distinguished leader with a profound impact on AI, cybersecurity, and space innovation. She has pioneered two innovation labs, launched over 50 AI products, and established a cutting-edge space function at Mastercard. Her groundbreaking work includes creating the first AI workforce cybersecurity platform and conceptualizing the first space-NFT concepts, collectively generating $3.2 billion in value across various sectors.

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Digital Education Council: Global AI Faculty Survey 2025

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Digital Education Council: Global AI Faculty Survey 2025

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Digital Education Council Global AI Faculty Survey 2025

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Guides: Artificial Intelligence (Generative) Resources: Home

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Guides: Artificial Intelligence (Generative) Resources: Home

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AAC&U 2025: Leading Through Disruption: Higher Education Executives Assess AI’s Impacts on Teaching and Learning

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AAC&U 2025: Leading Through Disruption: Higher Education Executives Assess AI’s Impacts on Teaching and Learning

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Leading Through Disruption: Higher Education Executives… | AAC&U

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This report provides a comprehensive overview of the survey findings, outlines the challenges and opportunities of integrating AI into higher education…

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Empowering Educators: Operationalizing Age-Old Learning Principles Using AI

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Empowering Educators: Operationalizing Age-Old Learning Principles Using AI

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Empowering Educators: Operationalizing Age-Old Learning Principles Using AI

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This paper aims to provide a framework for educators to effectively navigate the complexities of artificial intelligence (AI) integration while maintaining the core principles of effective teaching and learning, specifically through the lenses of Dewey’s experiential learning, situated cognition, and distributed cognition. By examining these principles, we explore the essential role of the teacher in this context and the implications of ignoring AI. The integration of AI can enhance personalized learning experiences, facilitate adaptive learning systems, and support educators in fostering critical thinking and problem-solving skills among students. Additionally, we highlight the challenges and ethical concerns associated with AI use in education. We argue that AI should be viewed as a tool that enhances, rather than replaces, the role of educators, emphasizing the importance of maintaining the educator’s role in guiding and supporting student learning. This framework serves as a valuable resource for educators seeking to embrace AI’s potential while ensuring that teaching remains centered on student engagement and successfully achieving learning outcomes as we prepare the next generation to be an AI-ready workforce.

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Washington State University: AI Tools for Education and Resources for Learning About AI

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Washington State University: AI Tools for Education and Resources for Learning About AI

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AI Tools for Education and Resources for Learning About AI

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Overview

Bharat Anand, Vice Provost for Advances in Learning, and colleagues at VPAL, the Future of Media Lab, and the Harvard Teaching and Learning Consortium
When it comes to the future of education, virtually no recent technology has sparked as much debate as generative AI (GenAI) and large language models (LLMs). Some have seen this technology as destructive, with school districts from Los Angeles to New York initially banning its use, and others have touted its transformative impact and possibility of changing the game for educators and students alike.

Harvard has consistently tried to embrace new technology across our classrooms, residential and virtual. This past year was no different. In fall 2023, we introduced the Harvard AI Sandbox, enabling faculty to use LLMs in their classrooms while respecting copyright and data security policies.

Several faculty colleagues experimented with these tools in their classrooms during the semester. Here, we have surfaced the learnings from interviews with 30-odd faculty across Harvard, with short 3-7 minute videos, all answering three questions:

What is the challenge you were trying to address?

How did you use generative AI tools to tackle it?

What did you learn?

Our small team of faculty, students, and staff extracted from these a non-comprehensive answer through debate, discussion, and our own learning. I encourage you to do the same, perhaps with your peers or teaching teams, to learn about how these might be relevant for your own courses. Here are some of our initial thoughts:

1. GenAI tools have raised concerns about how they may compromise student assessments, promote academic dishonesty, and facilitate "lazy learning." Our faculty colleagues who experimented with these tools were not oblivious to these concerns; indeed, many share them. At the same time, what you'll see is how they were also looking to understand how GenAI tools can enhance the educational experience and build more vibrant classrooms.

2. Several colleagues are leveraging LLM features that everyone should keep in mind:

1. For Beyond text: visual aids and images, coding, analysis, games, simulations, and more.

2. Prompt design: There's an old saying: "garbage in, garbage out." The output of LLMs is only as good as the input, and it's essential to learn (and perhaps teach) how to write a prompt that works. This is highlighted through discussions on the critical role of deliberate prompt formulation, from having students iterate on their prompts through the course, to engaging students in debate on the ethics of AI use, to making advanced statistical concepts accessible to diverse learners. Our new System Prompt Library offers a range of effective prompts that can be used by educators.

3. Interrogate hallucinations: Errors arise not just because of algorithmic or data limitations but, importantly, because LLMs are fundamentally probabilistic. Faculty have found that errors can be reduced through detailed prompt engineering and balanced AI-human partnership.

3. Some consistent patterns and learnings emerge from how GenAI has been implemented for use by our colleagues:

1. Going beyond the simple question-and-answer interface: Sal Khan popularized the idea of using LLMs to ask questions of a student, not just answer them. Several faculty colleagues take this further, illustrating how LLMs can be used to simulate any persona you want, and to ask anything of them. Examples include simulating experts, peers, graders, course designers, and personal chatbots.

2. More than the "first draft": GenAI needn't compromise student creativity; in fact, it can augment it. Some colleagues are using it to help students refine project prototypes and polish final drafts.

3. Work alongside what you already have: Many faculty used LLMs to improve different (and sometimes mundane) aspects of existing teaching and learning "workflows," such as producing course materials, personalizing feedback, generating assignments, summarizing real-time student responses, and tutoring students.

4. Identify, and overcome, hidden or invisible barriers: Students and educators sometimes confront hidden prerequisites that present barriers for teaching and learning. GenAI can assist with overcoming these skill gaps: coding for a business class, foreign languages for research, art skills for building visual aids, and even building games for class engagement.

5. Reimagining the classroom: While we're still in the early days of GenAI, some of these examples already start to surface more profound questions: What does a class with GenAI at its core look like? Ultimately, what is the role of a teacher?

4. Questions around genAI's efficacy on learning arise: can we use GenAI tools-specifically tutor bots-to improve the way students learn? One faculty member created a tutor bot that answered questions like course staff. Beyond such research on students' interactions with genAI tools, it might be helpful to imagine how it can help you and your students now, in other ways as well: by increasing task efficiency, improving student engagement, increasing their confidence, or even improving learning outcomes.

5. The risks of LLMs present valid concerns. While popular debates often focus on "big picture" concerns like algorithmic biases, digital divides, and fake content, some faculty explore the risks at a micro scale, within our classrooms, such as hallucinations, failed reasoning, or superficial thinking, pushing students to understand these issues more deeply.

We hope this starts to give you a taste of the richness embedded in these videos. To start experimenting, request access to the Harvard AI Sandbox. As you think about what's relevant for your course, support exists across Harvard to help you and your team experiment as well.

Looking ahead, it is clear we will continue to learn. We will experiment. We will refine. And we will advance our understanding. In the next months, we'll continue to expand our catalog to include more innovations from Harvard faculty-please reach out to the Office of the Vice Provost for Advances in Learning (VPAL) via email if you would like to share your own experiences with colleagues across Harvard. We're deeply grateful to our colleagues for sharing their experiments and experiences, featured here in the first Harvard GenAI Library for Teaching and Learning.

Frequently asked questions

The following information offers advice for educators interested in using generative AI tools in their teaching and course preparation. As this technology is constantly evolving, this page will be updated frequently with new resources and advice.

Creating materials for courses-syllabi, lesson plans, assignments-takes time. Generative AI tools aren't just useful at broad, general prompts, but, as our colleagues have shown, they are useful in tackling the preparations before a student even arrives in the classroom:

Assignments: Reusing the same assignments across multiple years can be time efficient, but it creates challenges for assessments. Some faculty have explored how AI tools can help write, modify, or create question sets. The more information you put in about the structure and concepts you want it to use, the better it will be. And it can even make a rubric for it.

Course content: Classes often include large amounts of content for reading, from case studies to readings to slideshow text. Just a few sentences of a prompt using GenAI can generate summaries of relevant readings or videos you might want to include for students, brand new cases to discuss, and even what your slideshow for a lecture should include. Some faculty have gone a step further, inputting all the course materials in the materials that trained a teaching assistant chatbot. Hear what this faculty member learned from students' interactions with this "faculty copilot."

How to engage your students in the classroom is an age-old question. Some faculty have used GenAI's real-time thinking and range of outputs to help offer contemporary solutions, such as a content-generator, a data analyst, or a personal tutorbot.

Since LLMs can write essays, respond to readings, and finish problem sets, how can one not be concerned about misuse? For you and your students, addressing this concern means first making sure we know what GenAI can and can't do-then creating assessments that emphasize skills where AI tools fall short.

Here are some strategies faculty have found useful:

Human-based learning: Design tasks and assessments that require creativity, practical application of concepts, and critical thinking. For example, instead of asking your students to summarize perspectives on a given issue, you may ask them to critically analyze which perspective is most convincing to them and explain why; to relate their answers to class discussions; or to assess their peers' performance during a live problem-solving session.

Process-based assessments: Another approach is to test intermediate steps in the learning process, instead of just the final product. (It's easy to fudge your report card to your parents; it's harder to fudge not having gone to school for the past two months.) Testing evidence of original thinking, planning, peer-to-peer conversations, etc. can make relying on genAI less attractive.

Establishing norms: Emphasize original work and academic honesty, and at a minimum provide clear guidelines about the use of AI-generated content in assignments and assessments.

Here are the most important ones to keep in mind:

AI models can make mistakes: We've all had an incident (or two!) where a GenAI tool seems to have lost its mind, yielding garbled or entirely made-up answers. These are called AI hallucinations. It's tempting to think these will get eliminated over time as technology improves. But since LLMs are fundamentally probabilistic rather than deterministic, this may not be the case.

AI models can be biased: AI adopts the biases of the material and data it was trained on. Good AI use involves being aware of, checking for, and making efforts to correct such biases.

AI models can be misused: Of course, AI could be used to plagiarize assignments. Unless you are interested in grading robots, you should shift the kind of assignments you are providing students (see above) as well as enforce academic dhonesty policies.

GenAI's ability to meet learners where they are, both in terms of prior knowledge and learning progress, can increase students' understanding, and AI-powered educational games can increase student motivation and engagement, particularly in STEM courses. One fascinating study showed that when students tutored by AI are pitted against students taught in the traditional classroom setting, the AI-tutored students performed as well or better.

It is natural for instructors, particularly successful ones, to wonder: GenAI may be useful for the average educator. But my classes are great; why would I need it?

One way to think about this is in terms of the efficiency benefits of GenAI tools-they can save time, facilitate meaningful non-classroom learning experiences, and make classroom discussions more interactive. For example:

When using large language models (LLMs) in your classroom, it's essential to be aware of the University's guidelines designed to ensure responsible and effective use of these technologies and to refer to School-specific policies and resources. It is also important to remember that other existing policies, such as Harvard's Information Security Policy, Digital Accessibility Policy, and Intellectual Property Policy, also apply to GenAI and the use of LLMs.

Across Harvard, there's a strong emphasis on using LLMs ethically and in ways that uphold academic integrity. The use of generative AI must align with the principles of honesty, respect, and responsibility, ensuring that students' work remains original and reflective of their understanding and skills. In crafting a response to the use of LLMs in the classroom, it's crucial to strike a balance between leveraging these tools for educational enhancement and ensuring that they do not compromise educational objectives.

At the course level, Schools within Harvard allow for the customization of AI usage policies by individual instructors, provided these are clearly communicated. Each encourages innovative and thoughtful integration of AI in teaching and learning practices, including learning to use generative AI productively. Above all, students and faculty are encouraged to be transparent about the use of generative AI in academic work. This includes proper attribution when AI-generated content or assistance is utilized in the creation of academic materials. Consider co-creating course-specific norms around the use of generative AI with your students.

For any faculty who wish to simply explore the use of these tools, we encourage you to engage with peers and organizations at Harvard that are interested in these topics.

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2024 Creative AIJobs Report: Equipping Students and Early Career Seekers with Essential Skills

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2024 Creative AIJobs Report: Equipping Students and Early Career Seekers with Essential Skills

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2024 Creative AI Jobs Report - Global IT Research

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World Economic Forum: Future of Jobs Report 2025

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World Economic Forum: Future of Jobs Report 2025

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Learn how global trends like tech innovation and green transition will transform jobs, skills, and workforce strategies in The Future of Jobs Report 2025

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2025–26 Institute on AI, Pedagogy, and the Curriculum

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2025–26 Institute on AI, Pedagogy, and the Curriculum

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2025-26 Institute on AI, Pedagogy, and the Curriculum | AAC&U

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A VOICE AND A FORCE FOR LIBERAL EDUCATION. AAC&U advances the vitality and democratic purposes of undergraduate liberal education.

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AI in Education - Sovorel Center for Teaching and Learning: Videos

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AI in Education - Sovorel Center for Teaching and Learning: Videos

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Learn about instructional technology such as AI, innovative teaching methodologies, and other emerging educational technologies that are shaping the future of higher education. Led by Brent A. Anders, PhD. (lecturer, author, presenter), our channel is dedicated to fostering a community of learners and critical thinkers who are passionate about exploring new educational frontiers. We invite you to join our community of inquiry and share your thoughts and ideas in the comments section so that we can learn together. Be sure to also check out the Sovorel Educational Blog for even more in-depth articles and insights on all things education. Don’t miss out on the latest updates and breakthroughs in the world of learning - hit that subscribe button and let’s embark on a journey of discovery together. Note that “Sovorel” means the art of learning, studying, reading, and remember, “Learning is for Life!”

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Google: Tools for Anyone to Create, Learn, Develop and Play with the Future of AI

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Google: Tools for Anyone to Create, Learn, Develop and Play with the Future of AI

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Labs.Google is Google’s home for the latest AI tools, technology and discourse.

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Contact North | Contact Nord Webinars - Free Webinars By World Experts & Innovators

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Contact North | Contact Nord Webinars - Free Webinars By World Experts & Innovators

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125 Webinars

65 Expert Presenters

19,650 Registrants
from 80+ Countries

How to Engage Silent Learners

Many of us learn best in silence and need time to reflect before saying or writing our thoughts. In synchronous online meetings (...

1:00 pm - 2:00 pm (Eastern Time)

How to Use Shared Online Videos, Podcasts and Webcasts to Engage Online Learners

The global disruption wrought by COVID-19 has given institutions, faculty and instructors an unexpected gift: the opportunity to...

10:00 a.m. - 11:00 a.m. (Eastern Time)

Value for Money: Should Online Education be Cheaper?

The COVID-19 outbreak led to a massive uptake in online education worldwide and rapidly formed or changed public opinions about...

11:00 a.m.- 12:00 p.m. (Eastern Time)

Hosts: Dr. Kyungmee Lee & Dr. Dietmar Kennepohl

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125 Webinars 65 Expert Presenters 19,650 Registrants from 80+ Countries How to Engage Silent Learners Many of us learn best in silence and need time to reflect before saying or writing our thoughts. In synchronous online meetings (...

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Top Hat: Webinars - Teaching, Learning & AI

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Top Hat: Webinars - Teaching, Learning & AI

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Webinars and Videos for Higher Education | Top Hat

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Find and browse a list of webinars and videos for the higher education space, looking to learn more about how to become a better educator, look no further.

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King's College London: Generative AI in Higher Education

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King's College London: Generative AI in Higher Education

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Generative AI in Higher Education - Online Course - FutureLearn

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Understand the capabilities and limitations of generative AI to cope with its challenges and harness its potential for education, with this online course from King’s College London.

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9 Point Action Plan: for Generative AI Integration into Education - Brent Anders

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9 Point Action Plan: for Generative AI Integration into Education - Brent Anders

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Brent A. Anders PhD. (Author), Anait Akopyan MA (Editor)

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9 Point Action Plan: for Generative AI Integration into Education

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9 Point Action Plan: for Generative AI Integration into Education [Anders PhD., Brent A., Akopyan MA, Anait] on Amazon.com. *FREE* shipping on qualifying offers. 9 Point Action Plan: for Generative AI Integration into Education

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Jefferson College: Becoming an Informed AI User

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Jefferson College: Becoming an Informed AI User

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LibGuides: Becoming an Informed AI User: Home

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This guide reviews important concepts about artificial intelligence (AI) that Jefferson College students should know, including helpful uses, limitations, and risks.

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University of New Orleans: AI Literacy Micro-credential Free for All Students

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University of New Orleans: AI Literacy Micro-credential Free for All Students

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University to Launch AI Literacy Micro-credential Free for All Students

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The University of New Orleans will launch the “Empowering AI Literacy” micro-credential, a free self-paced credential to help students navigate and succeed in today’s AI-driven world. The innovative offering focuses on AI literacy, not computer science or coding, to increase students’ understanding of the impact of artificial intelligence on daily life, education and work. It will teach students how to prompt generative AI tools ethically and effectively.“Whether they know it or not, our students interact with generative AI every single day,” said Meredith King, assistant director of the Center for Teaching Innovation. “Our students need to be able to use this technology ethically and responsibly, as well as efficiently. This credential is free for all currently enrolled UNO students and can be put onto social networking sites, such as LinkedIn. UNO is leading the way and giving our students an experience that translates beyond the classroom and into their futures.” The credential is fully online and designed to fit students’ schedules. Upon completion, students will earn a digital badge that can be showcased on LinkedIn and other professional platforms to highlight their mastery of AI literacy.In the course, students will learn the following: • The basics of AI, including its history and societal impact.• How to use generative AI tools effectively, ethically and responsibly.• Best practices for protecting data privacy and developing digital literacy.• The role of AI in shaping the future of work and how it applies to your field.The micro-credential includes five engaging units with video lectures, interactive activities and practical assignments. The units can be taken independently and students will earn a badge for each unit. After completing all five units and a final assessment, students will earn a completion badge. The materials will be made available to all students within UNO’s learning management system starting on Friday, January 17.

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Georgia State University: AI in Teaching and Learning Series

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Georgia State University: AI in Teaching and Learning Series

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This website is using a security service to protect itself from online attacks. The action you just performed triggered the security solution. There are several actions that could trigger this block including submitting a certain word or phrase, a SQL command or malformed data.

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 East Carolina University: Guide to Artificial Intelligence (AI) for Students

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 East Carolina University: Guide to Artificial Intelligence (AI) for Students

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Research Guides: A Guide to Artificial Intelligence (AI) for Students: Home

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Research Guides: A Guide to Artificial Intelligence (AI) for Students: Home

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Iona University: Introduction to AI for Faculty

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Iona University: Introduction to AI for Faculty

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"At the most basic level, a chatbot is a computer program that simulates and processes human conversation (either written or spoken), allowing humans to interact with digital devices as if they were communicating with a real person. Chatbots can be as simple as rudimentary programs that answer a simple query with a single-line response, or as sophisticated as digital assistants that learn and evolve to deliver increasing levels of personalization as they gather and process information."

Source: https://www.oracle.com/chatbots/what-is-a-chatbot/

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Research Guides: Introduction to Artificial Intelligence: Introduction to AI and ChatGPT

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Research Guides: Introduction to Artificial Intelligence: Introduction to AI and ChatGPT

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Northern Virginia Community College:  AI Tools & Resources

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Northern Virginia Community College:  AI Tools & Resources

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Rather than using AI to create your work from the ground up (your voice is important!), use AI to get feedback on your writing.

To ensure your writing conveys your intended points effectively:
"Summarize the three main points of my paper: [Provide your writing sample]"
If you need support getting started on writing your paper and aren't sure how to structure your writing:
"Act as a tutor for first-year undergraduate writing students. I am writing a 500 word persuasive essay based on [chosen topic], and I am focusing on [subtopic] and [subtopic]. Please give me an outline for my paper to help get me started."
If you need ideas for finding keywords to search in library databases, and finding where to search:
"Act as an expert librarian. I am trying to locate articles about [chosen topic]. Please give me keywords and 2-3 search strings to try, and tell me which databases I should search."
If you want broad feedback on your assignment and pointers for revision:
"Act as an expert academic editor. Provide feedback on the submitted writing, highlighting areas for improvement and suggesting ways to enhance the piece's overall quality: [Provide your writing sample]"
To locate any accidental uses of passive voice in your research project:
"Check my writing and highlight areas where I use passive voice: [Provide your writing sample]"

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LibGuides: AI Tools & Resources: For Students

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Please direct all questions or comments to kmentzer@nvcc.edu

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University of Manitoba: Generative AI Tools

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University of Manitoba: Generative AI Tools

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LibGuides: Artificial Intelligence: Generative AI Tools

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LibGuides: Artificial Intelligence: Generative AI Tools

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University of Southern Florida: AI Tools and Resources

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University of Southern Florida: AI Tools and Resources

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Andrew D. Beman-Cavallaro, MLIS, MA - USF Libraries

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Introduction to generative AI concepts and tools

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University of Portland: AI Tools and Resources

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University of Portland: AI Tools and Resources

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Library Guides: AI Tools and Resources: What is AI?

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Library Guides: AI Tools and Resources: What is AI?

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Upcoming webinars and events are provided below related to key topics such as teaching, learning, assessment, Artificial Intelligence (AI), instructional design, UDL, student success, and more.

Human-Centered AI: The Key to Effective Next-Gen Courses

Technology is transforming education, but it's the human element that truly drives learning. Join LearningMate, WCET, and higher ed leaders for this exploration of next-gen courses leveraging the power of AI to enhance the learning experience, not replace it. By combining the best of human ingenuity with cutting-edge technology, we can create:

Personalized Learning Paths: AI-powered tools can analyze student data to tailor instruction to individual needs.

Engaging Interactive Content: Immersive experiences that stimulate curiosity and critical thinking.

Efficient Administrative Tasks: Automate routine tasks to free up time for meaningful interactions.

Join us to explore how AI can be used to augment human capabilities and create a future of education where technology serves as a tool for empowerment, not a substitute for human connection.

Responsible AI in Higher Ed: Balancing Innovation and Sustainability

Over the past two years, higher education - like much of broader society in North America - has been captivated by AI and its potential to transform and improve outcomes. Many vendors developing AI products or integrating AI features into their offerings have committed to ethical principles or guidelines to steer their development. Although these ethical commitments are important, most fail to address the environmental impact of AI. This webinar explores why environmental considerations are often overlooked, how some organizations are working to mitigate the effects, and what higher education institutions can do to adopt AI responsibly.​ Explore how institutions can adopt AI responsibly while addressing its environmental impact. Gain a deeper understanding of sustainable practices and strategies to mitigate AI's energy consumption and emissions. Presented by Glenda Morgan, an EdTech market analyst.

Case Study: Using Generative AI to Analyze Continuing Education Participant Feedback

There is general recognition that participant feedback provides indispensable insights that can be used by instructors, administrators, and staff to enhance teaching materials and improve the overall learner experience in programs. Processing and analyzing this feedback from relatively small sample sizes is a task that can be reasonably accomplished by many people in an organization.

But what happens when a large data set is pulled together? How can a team that does not have a qualitative expert on staff nor desire to engage in the time it would take to perform a formal analysis of the data proceed? You leverage the power of Generative AI and Large Language models.

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Upcoming webinars and events are provided below related to key topics such as teaching, learning, assessment, Artificial Intelligence (AI), instructional design, UDL, student success, and more. Technology is transforming education, but it's the human element that truly drives learning.

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University of North Carolina, Chapel Hill: Faculty and student fellowships, and staff awards

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University of North Carolina, Chapel Hill: Faculty and student fellowships, and staff awards

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Faculty and student fellowships, and staff awards - AI Acceleration

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Faculty fellowships The AI faculty fellowships are a way to support academic staff who contribute to the advancement of AI scholarship, research and education at the University. Student AI fellowships Provides funding for students with AI related expertise to be inserted into projects lacking technical expertise. Students will be vetted by the program team and […]

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Reminder Faculty AI Mini-Grant Applications Due 12/2

By Jenna Linskens, November 25, 2024

The Center for Instructional Design and Educational Technologies, in partnership with the Center for Faculty Excellence, is pleased to announce AI Mini-Grants for Course Integration to faculty for the Spring 2025 semester.

Stipends will be awarded to faculty as an incentive to develop student-facing instructional units that integrate AI into existing courses. Six AI Mini-Grants have been awarded for Fall 2024 courses and another round of six will be awarded for Spring 2025.

Please visit the Artificial Intelligence Mini-Grants page for more information and to apply for a Spring 2025 award.
*** Due date for Spring 2025 applications is Monday, December 2, 2024, 5:00 PM ***
Please direct questions to Marilyn Dispensa, Sr. Instructional Designer in the Center for Instructional Design and Educational Technology.

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Reminder Faculty AI Mini-Grant Applications Due 12/2 | Ithaca College

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The Center for Instructional Design and Educational Technologies, in partnership with the Center for Faculty Excellence, is pleased to announce AI Mini-Grants for Course Integration to faculty for the Spring 2025 semester.Stipends will be awarded to faculty as an incentive to develop student-facing instructional units that integrate AI into existing courses. Six AI Mini-Grants have been awarded for Fall 2024 courses and another round of six will be awarded for Spring 2025.Please visit the Artificial Intelligence Mini-Grants page for more information and to apply for a Spring 2025 award.*** Due date for Spring 2025 applications is Monday, December 2, 2024, 5:00 PM *** Please direct questions to Marilyn Dispensa, Sr. Instructional Designer in the Center for Instructional Design and Educational Technology.

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Duke University: Artificial Intelligence Policies: Guidelines and Considerations

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Duke University: Artificial Intelligence Policies: Guidelines and Considerations

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Duke Learning Innovation & Lifetime Education

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Wondering if there is a specific Duke policy regarding AI generated content? You have the discretion to define how, if, and when generative AI may be used in your courses. However, the Duke Community Standard has been updated to include the unauthorized use of generative AI as a form of cheating. Plus, the Office of Undergraduate Education offers a syllabus language menu that identifies considerations for writing an AI policy. (NetID login required).

Draft your own AI policy

All instructors should update their syllabi to include guidance on the use of generative AI in their class. We encourage faculty to thoughtfully consider their stance on AI use. In this shift in higher education and the rapidly changing AI market, standardized, one-size-fits-all, AI policies are not sustainable in the long term. They may also not account for the varying stances instructors will take regarding AI use in their classrooms. Furthermore, because generative AI is becoming more ubiquitous, you'll need to consider your personal stance on AI in your own work, as well as in your classrooms. Establishing an AI policy for your class allows you to have meaningful discussions with students on this topic. Being specific about how AI is or isn't allowed makes the rules clear for students and faculty if there are academic integrity violations as well.

The following guidelines for developing an AI policy for your syllabus include examples of generative AI policies from instructors, universities, and centers of teaching and learning. For the most part, they have been curated from a crowd-sourced document that we encourage you to explore on your own to find AI policies developed by instructors in your field and represent your level of comfort with the use of AI. Other sources for sample policies are cited in the text itself.

Do your homework

Kevin Gannon (Queens College in Charlotte) argues in an article titled "Should I Write an AI Policy" (NetID login required) that instructors should start with research into the topic before writing their policy. He offers a list for instructors of varied sources that provide a primer on the mechanics of generative AI, pros and cons of AI use, and a grounding in how generative AI can be incorporated into teaching.

We encourage you to try at least one generative AI tool. A good way to start exploring is to enter the prompts that you give students for an assignment into the AI tool, and see what the tool returns. It is important to learn how to write effective prompts and also explore existing prompt ideas. Keep an open and curious mindset when considering whether such tools could be helpful to some or all of your students.

Share the rationale behind your policy

As you define your individualized AI syllabus statement, your reasoning should be grounded in the intellectual work of the course, your discipline and your understanding of critical thought. Some of the questions you might ask yourself are: What will students lose (or gain) by using generative AI in your course? What do you want students to understand about AI and their intellectual development? We encourage you to explain the rationale for your policies with your students and open a conversation about AI with them. Below are three policy examples that detail the instructors' thinking behind their AI policy.

In a policy example from Joel Gladd (University of Western Idaho) he mentions two guiding principles in a course that will allow the use of AI: "1) Cognitive dimension: Working with AI should not reduce your ability to think clearly. We will practice using AI to facilitate-rather than hinder-learning. 2) Ethical dimension: Students using AI should be transparent about their use and make sure it aligns with academic integrity."

Lis Horowitz (Salem State University) shares a practical reason behind a zero tolerance policy for generative AI in their writing course. "Since writing, analytical, and critical thinking skills are part of the learning outcomes of this course, all writing assignments should be prepared by the student. Developing strong competencies in this area will prepare you for a competitive workplace. Therefore, AI-generated submissions are not permitted and will be treated as plagiarism."

By defining the idea of integrity, Megan McNamara (UC Santa Cruz) points out what is at stake when we talk about academic honesty and personal growth. As she states, "Integrity - other people's perception of your word as true - is one of the most valuable assets you can cultivate in life. Being attentive to integrity in academic settings allows others to trust that you have completed work for which you are taking credit." Her course allows students to use AI in limited ways and this rationale sets the foundation for this use.

Support AI literacy

Although students may already use generative AI, it does not mean that they understand the limitations of the tool or how to use it properly.

For example, generative AI is a brand-new source for information and the rules for citation and the general use of AI are still under formation. If you explain to students how to cite content generated from AI sources it reduces the cognitive load of students unsure of how to act within the Duke Community Standard and raise their awareness of what is at stake when interacting to AI content. Most academic style guides have already formulated citation practices for generative AI. Monash University has curated a list of the various AI citation formats.

You have the option to personalize your approach to citations. Some educators are instructing students to submit a transcript of the conversation with generative AI as an appendix to their written work. Another alternative might be a reflective piece as a companion to an assignment, as Pam Harland (Plymouth State University) has done by providing guiding questions for students: "What was your prompt?" "Did you revise the AI model's original output for your submission?" "Did you ask follow-up questions?" "What did you learn?"

Another aspect of AI literacy is understanding the ethical use of AI and its limitations. When students have information about the hallucinations, bias, and inaccuracies of generative AI, it underscores why AI is not a shortcut to good results. Ethan Mollick (Harvard's Wharton School) frames it this way, "[d]on't trust anything it says. If it gives you a number or fact, assume it is wrong unless you either know the answer or can check in with another source. You will be responsible for any errors or omissions provided by the tool. It works best for topics you understand." The library at University of Northwestern St. Paul has a guide for students with an overview of AI's shortcomings, plus information on how to verify sources and double check AI responses.

Define acceptable use

If you decide to allow generative AI as a tool for learning in your courses, clarify for your students the circumstances in which AI is allowable. Kim Sydow Cambell (University of Texas) offers an example policy that expands upon the tasks that students can ask AI to perform:

"Because the effective use of Artificial Intelligence (AI) tools is increasingly important to the work of technical communicators, their use is sometimes required or allowed in course assignments. AI tools can support a content creator during all phases of their work:

pre-writing: before content is created, writers can use some tools to research topics, collect genre samples, brainstorm ideas, craft outlines, etc.

drafting: some tools support the generation of content

revising: after content is generated, many tools aid writers in identifying and altering style/tone, spelling, punctuation, grammar, etc."

From Howard University of Law, Howard Bruckner explains to students what tasks are acceptable and underscores the students' responsibilities for ethical use. "Generative AI tools can be invaluable for generating ideas, identifying sources, synthesizing text, and starting to understand what is essential about a topic. But YOU must guide, verify and craft your work product; do not just cut and paste without understanding."

You may discover that if you allow students to engage with generative AI, specific guidelines may need to accompany each assignment.

Explore the continuum of policies

Below are policy examples from the University of Delaware's Center for Teaching and Assessment of Learning, which distill the four basic approaches that instructors can take in their syllabi. We invite you to consider them as starting points in your exploration of what your AI policy will be.
Use prohibited
Students are not allowed to use advanced automated tools (artificial intelligence or machine learning tools such as ChatGPT or Dall-E 2) on assignments in this course. Each student is expected to complete each assignment without substantive assistance from others, including automated tools.
Use only with prior permission
Students are allowed to use advanced automated tools (artificial intelligence or machine learning tools such as ChatGPT or Dall-E 2) on assignments in this course if instructor permission is obtained in advance. Unless given permission to use those tools, each student is expected to complete each assignment without substantive assistance from others, including automated tools.
Use only with acknowledgement
Students are allowed to use advanced automated tools (artificial intelligence or machine learning tools such as ChatGPT or Dall-E 2) on assignments in this course if that use is properly documented and credited. For example, text generated using ChatGPT-3 should include a citation such as: "Chat-GPT-3. (YYYY, Month DD of query). "Text of your query." Generated using OpenAI. https://chat.openai.com/" Material generated using other tools should follow a similar citation convention.
Use is freely permitted with no acknowledgement
Students are allowed to use advanced automated tools (artificial intelligence or machine learning tools such as ChatGPT or Dall-E 2) on assignments in this course; no special documentation or citation is required.

About AI detection software

We don't recommend AI detection software as a part of your AI policy for three main reasons.

1. The products are unreliable. Research on AI detection software from MIT highlights the false positive and negative rates. OpenAI (the company behind ChatGPT) withdrew its own detection software due to the software's unreliability.

2. Detection software is biased against certain segments of learners, for example non-native speakers, as research from Stanford shows.

3. As AI changes, detection software cannot keep up.

If you decide to use detection software, share that information with your students ahead of time. Results from the software should not be the only measure of whether students have cheated. Students can be encouraged to use detection software prior to handing in work to check for originality (although they should be warned of the limitations as well).

Another option is to craft a policy that warns students they will need to speak with you and defend their work if plagiarism is suspected. As Liza Long (College of Western Idaho) explains "[i]f I suspect that you have used ChatGPT, and you have not included the required citation and reflection, then you will need to meet with me either in person or through Zoom to talk about the assignment. This conversation will include knowledge checks for course content."

If you'd like to discuss your AI policy in more depth, please reach out to learninginnovation@duke.edu. You can also explore our central resource on AI in education.

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Artificial Intelligence Policies: Guidelines and Considerations - Duke Learning Innovation & Lifetime Education

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Updated: January 24, 2024 Wondering if there is a specific Duke policy regarding AI generated content? You have the discretion to define how, if, and when generative AI may be ...

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US Department of Education: Artificial Intelligence (AI) Guidance

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US Department of Education: Artificial Intelligence (AI) Guidance

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Learn more about federal Artificial Intelligence (AI) guidance, innovation, and risk management, and find an inventory of ED’s AI use-cases.

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University of Southern Florida: AI Tools and Resources

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University of Southern Florida: AI Tools and Resources

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Andrew D. Beman-Cavallaro, MLIS, MA - USF Libraries

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LibGuides: AI Tools and Resources: Tools for Research

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Introduction to generative AI concepts and tools

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The University of Arizona: Student Guide to ChatGPT - Which AI tool for your task?

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The University of Arizona: Student Guide to ChatGPT - Which AI tool for your task?

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LibGuides: Student Guide to ChatGPT: Which AI tool for your task?

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LibGuides: Student Guide to ChatGPT: Which AI tool for your task?

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Texas Tech University: Artificial Intelligence Tools for Detection, Research and Writing

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Texas Tech University: Artificial Intelligence Tools for Detection, Research and Writing

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Guides: Artificial Intelligence Tools for Detection, Research and Writing: AI Detection

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Generative AI Related Writing and Research Tools Co-Owned and Co-Curated by Brian Quinn and Erin Burns List of links for detecting AI generated text and images

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Moraine Valley Community College: Toolkit and Resources: AI in Education

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Moraine Valley Community College: Toolkit and Resources: AI in Education

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Toolkit and Resources: AI in Education - Moraine Valley Center for Teaching & Learning

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Welcome to the CTL’s Comprehensive Toolkit on AI in Education This guide serves as your primer on integrating Artificial Intelligence (AI) and generative AI technologies, like ChatGPT, into the academic […]

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University of North Carolina, Chapel Hill: Artificial Intelligence and Generative AI for Media & Journalism: AI Literacy Resources

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University of North Carolina, Chapel Hill: Artificial Intelligence and Generative AI for Media & Journalism: AI Literacy Resources

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LibGuides: Artificial Intelligence and Generative AI for Media & Journalism: AI Literacy Resources

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LibGuides: Artificial Intelligence and Generative AI for Media & Journalism: AI Literacy Resources

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Emory University: Artificial Intelligence (AI)

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Emory University: Artificial Intelligence (AI)

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Research Guides: Artificial Intelligence (AI) at Emory: Ethics and AI

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Research Guides: Artificial Intelligence (AI) at Emory: Ethics and AI

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University of Memphis: Artificial Intelligence in Higher Education Recommendations & Guides

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University of Memphis: Artificial Intelligence in Higher Education Recommendations & Guides

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Research Guides: Artificial Intelligence in Higher Education: Home

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This guide aims to provide a comprehensive resource for students, faculty, and researchers on the transformative potential, ethical considerations, and practical applications of AI in higher education.

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Modesto Junior College: Faculty Guide to AI Literacy in the Age of ChatGPT

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Modesto Junior College: Faculty Guide to AI Literacy in the Age of ChatGPT

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Sample Syllabus Statements

Since generative artificial intelligence (AI) tools are still quite new to higher education (e.g., ChatGPT, Elicit, QuillBot), many students may be unaware of what is allowed or not allowed in a particular course. Since there is no college policy on AI use, the rules might differ from one course to the next.

Instructors can help to dispel any ambiguity or uncertainty by clearly communicating with students. Consider, for example:

Including a statement in your syllabus that outlines whether (or not) and how AI tools can be used in your course. See examples below.

Having conversations as a class about appropriate and inappropriate uses of AI tools in the course or disciplinary context.

Asking students to sign and adhere to an "honor statement" or code of conduct based on key course/institutional policies.

Constructing a "group agreements" document with your class that can be amended and referred back to throughout the semester.

Sharing examples from your discipline of how inappropriate use of AI led to negative consequences.

Sharing examples of how generative AI tools are changing your discipline or creating new opportunities for innovation.

Clarifying learning outcomes in the course so that students understand which essential skills they need to be able to demonstrate without the use of AI.

Attribution: "Syllabus Statements" by Camosun College Library is licensed under CC BY-SA 4.0

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Research Guides: AI Literacy in the Age of ChatGPT: ChatGPT and Pedagogy

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Faculty can use this guide to explore issues surrounding teaching and generative artificial intelligence

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Macalester College: AI Literacy and Critical Thinking

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Macalester College: AI Literacy and Critical Thinking

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All Guides: AI Literacy and Critical Thinking: Faculty

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Learn more about AI, how it works, and the challenges and ethical implications of using it.

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University of La Verne: List of Institutions with AI guidelines

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University of La Verne: List of Institutions with AI guidelines

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Subject Guides: Artificial Intelligence Faculty Committee: List of Institutions with AI guidelines

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Subject Guides: Artificial Intelligence Faculty Committee: List of Institutions with AI guidelines

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St. John's University: Artificial Intelligence (AI) Policies, Guidelines & Resources

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St. John's University: Artificial Intelligence (AI) Policies, Guidelines & Resources

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Artificial Intelligence (AI) Policies, Guidelines & Resources

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This page provides updates and comprehensive resources on using artificial intelligence (AI) at St. John’s University. The University has developed a workplace policy, specific guidelines, training for instructors, students, and employees, and other resources to foster awareness about the proper use of AI in administrative and academic activities.

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University of Notre Dame: Artificial Intelligence (AI): Usage, Policies, and Resources

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University of Notre Dame: Artificial Intelligence (AI): Usage, Policies, and Resources

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Contents of this page
What is Generative AI (GenAI)?
What is Google Gemini?
What else should I know about AI as I get started?
AI Workshops
Data Privacy
Responsible Use
Additional Resources
What is Generative AI (GenAI)?

Generative artificial intelligence (GenAI) is a type of Artificial Intelligence (AI) that can create new content, such as text, images, music, and videos. It uses machine learning models to analyze large amounts of data and learn patterns to generate new content.

In the College of Arts & Letters, we have access to multiple GenAI tools.

1. Google Gemini - currently available to all ND faculty and staff; most likely to be released to students sometime during the Spring or Summer 2025 semester (TBD). Google Gemini isintegrated into the existing Google Workspace suite, and access is available through the existing Notre Dame single sign-on.

2. Magai - currently available to all A&L faculty by requesting a license from the Office of Digital Strategy via this Google Form. Magai provides access to 26 GenAI models, including multiple versions of Claude, Gemini, GPT, Grok, Llama, and others.

What is Google Gemini?

Google Gemini App is an advanced AI assistant that can help you with a variety of tasks, such as answering questions, writing, planning, and even creating images. It's designed to understand and respond to different types of information, like text, images, and audio, making it a versatile tool for both personal and professional use. Think of it as a smart helper that can assist you with many of your daily activities, making them easier and more efficient. Some may think of it as the Google version of ChatGPT.

You may use the following data in Google Gemini:

Public data

Sensitive data, including FERPA data

You may not use highly-sensitive date in Google Gemini, such as:
Full AI Policies and Guidelines

HIPAA information

Banking information (credit cards, back account numbers)

Social Security numbers

Driver's License numbers

What else should I know about AI as I get started?

GenAI continues to evolve in quality and appropriateness of responses. However, how it responds to any individual prompt is difficult to predict and needs to be checked through experimentation. The quality of the output depends on the type of work requested and how it is requested. THESE SYSTEMS MAKE MISTAKES.

Because the systems are based on statistical patterns and cannot be perfectly predicted, the outputs must always be evaluated and accepted or modified by appropriately proficient humans.

Even the AI experts who created these GenAI models continue to be surprised by some of their behaviors.

Content generated primarily by these systems cannot currently be copyrighted since a machine cannot be given a copyright.

Different AI-based products vary on how they use and share your data. Make sure you understand the data use agreement for any version of any product you use. Free products often default to using your data to train future models with possible very negative privacy issues.

AI Workshops

Arts & Letters Computing (ALCO) is offering Zoom-based, hands-on " Getting Started with Google Gemini" workshops. There's no need to register in advance; just click the Zoom link to join at the scheduled time.

Friday, February 7, 9:30am - 10:15am: Zoom link

Friday, February 7, 11:00am - 11:45am: Zoom link

Tuesday, February 11, 9:30am - 10:15am: Zoom link

Wednesday, February 12, 1:15pm - 2:00pm: Zoom link

More to come ...

Data Privacy

Our ND-licensed version of Google Gemini includes a protected environment for our data. This means that data that we use in Gemini will not be used to train or further enhance AI tools or algorithms. Our data remains protected and kept safe using the same safeguards used for GMail and Google Drive.

Our license with Magai does not offer the same data protections. You may use only public data in Magai; you may not use sensitive data in Magai. We have had no negative incidents with Magai, and it has passed ND IT security approval but it is best practice to avoid sensitive and personal information in a third party application such as Magai.

Responsible Use

Notre Dame encourages safe exploration and use of generative AI tools to further our teaching, learning, research, and other pursuits. Keep these guidelines in mind:

Work within current University policies.

Protect confidential, copyrighted, and personal data.

Any AI tool used with institutional data must follow approval processes.

Routinely revisit specific usage policies.

Act ethically with AI.

You are 100% responsible for the output you use.

Be transparent and document usage of AI.

When in doubt, reach out.

Additional Resources
Google Gemini
AI@ND is the central hub for AI information at ND. You can learn about upcoming Get to Know AI sessions, the ND AI Forum, and other events. You can find ways to participate in the AI Community of Practice Group or the AI Developer Interest Group. You can also learn more about the Generative AI Task Force (GAIT) and the AI Innovation Council, and find many other AI-related resources.

AI@ND also provides a great Google Gemini App page to help you get started.
Get to Know AI Notre Dame Learning AI for Teaching and Learning Teaching in the Age of AI
A&L Office of Digital Strategy
Official Statement Regarding Generative AI The Honor Code
The College recently created the Office of Digital Strategy to support the evolution of the College's use of digital technologies, including generative AI. John Behrens, the director, provides workshops and consultations on generative AI for departments, small groups, or individuals. In addition, he leads a student research group that tracks the latest developments in the application of AI and will be hosting a monthly webinar series on ThinkND. John also consults with each of the groups mentioned below. Please email John ( jbehrens@nd.edu) if you have any requests or suggestions about addressing the challenges or opportunities of generative AI, increasing communication and collaboration, or want to join an affinity group.

In collaboration with faculty from around the University (including Nathaniel Myers and Whitney James from the Writing Center and Katie Walden from American Studies), Notre Dame Learning is sponsoring a series of workshops and presentations throughout the semester. They also have a web page of instructionally related resources including links within and outside of Notre Dame. The resource page gives some examples of how you might word your syllabus to address working with generative AI.

Office of Academic Standards

During the Spring of 2023, the Director of the Office of Academic Standards, Ardea Russo, convened a group of technologists, learning specialists, and faculty from across campus to discuss the implications of generative AI (primarily ChatGPT) which produced an Official Statement Regarding Generative AI as well as AI Recommendations for Instructors. We recommend you read these two documents. The committee included a broad range of inputs from our faculty and from across the University.

The Office of Academic Standards has released a statement to students about generative AI on https://honorcode.nd.edu/ that includes the following text:

"With this in mind, remember that representing work that you did not produce as your own, including work generated or materially modified by AI, constitutes academic dishonesty. Use of generative AI in a way that violates an instructor's articulated policy, or using it to complete coursework in a way not expressly permitted by the faculty member, will be considered a violation of the Honor Code."

Please remember that Ardea ( Ardea.C.Russo.23@nd.edu) can be contacted for any concerns related to academic dishonesty regardless of whether it is related to generative AI or not.

We want to emphasize that the honor code is based on the idea of violating "an instructor's articulated policy, or using it to complete coursework in a way not expressly permitted by the faculty member". This means it is important for faculty to think about the range of possible uses of the technologies in completing class assignments. Text-based generative AI such as ChatGPT, Bing, Claude, Gemini, Llamma2, and others are used for a wide range of activities such as web search, summarization of text, evaluation and editing of text, and brainstorming or background research. The more clearly you delineate what is acceptable and not, the easier it will be to agree on what is appropriate and what is not.

Related Links

Google Gemini App - Overview (ServiceNow)

Google Gemini App (AI@ND)

Policy Related Resources

Categories

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Marketing Communications: Web | University of Notre Dame

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Artificial Intelligence (AI): Usage, Policies, and Resources

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Resources, guides, and key information for Art & Letters faculty and staff

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Virginia Tech: Associate Director of Artificial Intelligence (AI) for Social Impact at the Sanghani Center for Artificial Intelligence and Data Analytics

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Virginia Tech: Associate Director of Artificial Intelligence (AI) for Social Impact at the Sanghani Center for Artificial Intelligence and Data Analytics

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Sanmay Das joins Sanghani Center at Innovation Campus to lead AI for social impact focus

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One current collaborative project aims at understanding the ways algorithmic techniques for prioritization and resource allocation can best be used for societal benefit by local government and nongovernmental organizations to support vulnerable populations, such as people experiencing homelessness or at high risk of eviction.

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Stony Brook University: Search for Director of AI

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Stony Brook University: Search for Director of AI

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Required Qualifications (as evidenced by an attached resume):
Master's degree (foreign equivalent or higher) in a relevant field. Five (5) years of full-time successful management experience in increasingly responsible positions. Three (3) years of experience with AI technologies, such as natural language processing, machine learning, or data analytics. Proven track record of managing technology-driven projects.

Preferred Qualifications:
Teaching and mentoring experience in the use of AI tools. Experience with interdisciplinary collaboration. Contributions to open-source repositories. Strong understanding of ethical standards and data privacy laws. Proven track record of managing technology-driven projects in a library or academic setting.

Brief Description of Duties:
The Director of Artificial Intelligence for Libraries will spearhead our AI transformation, bringing deep technical expertise in several AI domains such as machine learning, natural language processing, and data analytics to lead strategic initiatives integrating AI technologies across all library operations. This position demands hands-on experience developing and implementing AI solutions, combining technical innovation with academic leadership. Working closely with library staff, faculty, and IT teams, the director will develop and implement sustainable AI solutions that address the evolving needs of our academic community. The incumbent must possess strong leadership and interpersonal skills with the ability to work collaboratively across diverse teams. The incumbent must possess excellent written and verbal communication skills for effectively conveying technical concepts to non-technical audiences. The successful incumbent must possess a commitment to diversity, equity, and inclusion with a commitment to responsible AI use and compliance in academic settings in technology use and deployment.

Strategic Leadership:
Develop and implement a strategic vision for AI initiatives within the libraries that align with institutional goals. Develop policies and procedures to guide AI initiatives and ensure their alignment with Stony Brook, New York State, and federal guidelines. Foster an AI-driven culture across all library operations.

Collaboration & Outreach:
Collaborate with the library-based Director of Innovation to oversee the building of the AI lab and incorporate AI capabilities in future labs. Liaise with the newly formed AI Innovation Institute (AI3) at Stony Brook University, a new initiative focused on advancing artificial intelligence research, innovation, and interdisciplinary collaboration to address real-world challenges for additional funding opportunities and Work with faculty, researchers, and students to support AI-based research and foster partnerships across campus.

Ethical AI Practices and Governance:
Champion ethical and transparent uses of AI in library settings, focusing on privacy, equity, and accessibility. Develop policies and governance around AI usage and interface with broader University, SUNY, State, and US policies.

Innovation in Services:
Identify opportunities to enhance library services through AI, including optimizing discovery services, research support, procurement, etc.

Project Management:
Lead AI-focused projects and ensure cross-campus system integration with AI apps/agents. Manage multiple projects, ensuring goals are met on time and within budget.

Training & Education:
Develop training programs to build AI literacy among library staff and users, empowering them to use AI tools effectively and ethically.

Evaluation & Assessment:
Continuously evaluate the impact of AI initiatives and recommend improvements based on user needs and industry best practices.

Other duties or projects as assigned as appropriate to rank and departmental mission.

Special Notes:
This is a full-time appointment. FLSA Exempt position, not eligible for the overtime provisions of the FLSA. Minimum salary threshold must be met to maintain FLSA exemption.
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Salary: $120,000 - $143,800
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Jobs in higher education. Faculty and administrative positions at colleges and universities. Updated daily. Free to job seekers.

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University of Texas - El Paso: First Associate Vice President for Scientific Computing and Artificial Intelligence

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University of Texas - El Paso: First Associate Vice President for Scientific Computing and Artificial Intelligence

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UTEP Appoints First Associate Vice President for Scientific Computing and AI

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EL PASO, Texas (Jan. 8, 2025) — The University of Texas at El Paso has named Salamah Salamah, Ph.D., as its new Associate Vice President for Scientific Computing and Artificial Intelligence (AI). A prominent leader in computing and cybersecurity, Salamah will play a pivotal role in advancing UTEP’s strategic research initiatives and developing its computing infrastructure to support innovation.

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University of Wisconsin Madison: FERPA & AI

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University of Wisconsin Madison: FERPA & AI

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Stanford University: Report Outlines Stanford Principles for Use of AI

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Stanford University: Report Outlines Stanford Principles for Use of AI

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As artificial intelligence (AI) continues to reshape education, research, and administration at Stanford, a new report from the university's AI at Stanford Advisory Committee calls for balancing innovation with responsibility and alignment with the university's key values.

Underscoring both the opportunities and risks of AI, the "AI at Stanford" report sets forth guiding principles to encourage experimentation and creativity while addressing challenges such as plagiarism, authorship, and ethical use.

"The growth of AI technologies has huge implications for higher education, from the classroom to the research lab," said Provost Jenny Martinez. "The possibilities are incredibly exciting, and I'm confident Stanford will continue to be a leader in this area. As we support advances in this technology, it's crucial to assess how AI is being used at Stanford today, consider how it may be used in the future, and identify any policy gaps that may exist. I'm grateful for the advisory committee's thoughtful and thorough work, and the guidance it has provided in advancing the responsible use of AI at Stanford."

In March, the provost charged the AI at Stanford Advisory Committee to evaluate the role of AI in administration, education, and research, and to identify what's needed to use AI responsibly at the university.

Various university offices and committees will consider and take on recommendations from the report, and the committee chair will provide a presentation to the Faculty Senate in the winter quarter. The committee, made up of 10 faculty and staff members from various campus units, will continue to meet to address future issues related to AI use at Stanford.

Balancing experimentation with principles

While the committee acknowledged legitimate concerns about AI, it sought to avoid rigid policies that might deter the technology's potential benefits. "We wanted to first encourage experimentation in safe spaces to learn what it can do and how it might help us pursue our mission," said Committee Chair Russ Altman. "But then we also wanted to establish clear 'hot button' areas where people should proceed with an abundance of caution."

The report highlights potential policy gaps for the university, noting that many situations and challenges can't be anticipated, and provides general principles to guide AI usage at the university, such as requiring human oversight and ethical considerations in all AI usage.

"There should always be professionalism and personal responsibility. Whenever somebody uses AI, even if the AI does some work, they need to take responsibility for the output, and if there's mistakes, it's on them," said Altman, the Kenneth Fong Professor and professor of bioengineering, of genetics, of medicine, of biomedical data science, and senior fellow at the Stanford Institute for Human-Centered Artificial Intelligence.

People should resist lapsing into AI exceptionalism- assuming that existing laws, regulations, and university policies aren't applicable to AI, according to the report. "It seems seductively capable," Altman said, "and so people let their guard down and use it in ways that suggest they are forgetting what it is and how it works."

As a guiding principle, the report recommends an "AI golden rule": use AI with others as you would want them to use AI with you. For example, would you want AI to be used to review your proposal? This assessment would be based on individual judgments, evolving community norms, and combined with other principles to inform AI use.

Education

One primary area the committee examined is how AI affects education. Students have already adopted AI technologies such as ChatGPT, meaning the Honor Code and individual classroom policies may need to be revisited, the committee noted.

At the same time, many faculty aren't experienced with AI and are unaware of how they can use it, said Dan Schwartz, committee member and dean of the Graduate School of Education (GSE).

"Students have been exploring it much more than the faculty, and that's why it's important to find ways to educate the faculty, which I think is also true on the research side," Schwartz said. "The question is slowly changing from what are our students going to cheat with, to a more sophisticated question of what counts as cheating, how they can use AI in their work, and how to make it part of the assignment."

To help faculty navigate these questions, the committee recommends frameworks that can be tailored to different classroom needs. "It was something that students as much as faculty wanted so they can understand what's permissible and productive," Schwartz said.

The GSE has already created the AI Tinkery, part of the Stanford Accelerator for Learning, to provide a collaborative space for educators to explore the possibilities of AI.

Research

In research, AI raises complex challenges, including the question of whether AI can or should be credited as an author on publications. Other concerns include the use of AI in reviewing and writing proposals, training AI on student work, using data for AI research, addressing potential copyright violations in LLM outputs, and detecting fraudulent behavior.

For example, the use of AI detectors is already leading to a higher volume of plagiarism allegations, including spurious ones, which creates huge burdens on the offices that handle research misconduct. The university's misconduct policy and rules for investigating allegations may also need to be updated in accordance with new federal policy.

Many of these issues emerged from conversations with those who work in research administration, Altman said.

Researchers should also be reminded or made aware of potential risks in AI use and updated as legal risk profile changes, the report says. The committee also encourages the university to consider ways to expand computing resources to ensure Stanford remains a leader in the productive use of these technologies.

Administration

Regarding AI use in university administration processes, the committee found several areas that may require more guidance and additional policies, such as hiring, performance reviews, admissions, communications, and surveillance. The report also included recommendations on education and training for use of sensitive data, a streamlined procurement process for AI systems, and letters of recommendation.

The committee acknowledges that not all AI uses have been fully identified. "We were very aware that we couldn't uncover all uses of AI on campus, and this is what led us to articulate the guiding principles that we hope are useful for folks evaluating new AI opportunities to see if there are any red flags," Altman said. "In the end, these principles are probably more useful, and general purpose, than the specific issues we surfaced, which may or may not remain issues over the next few years."

The committee is just one facet of the university's ongoing incorporation of AI into its everyday work, which also includes University IT resources like the Stanford AI Playground where staff, students, and faculty can access a range of AI tools. At the same time, on the research side, faculty across the university are pushing the frontiers of knowledge in the development and use of AI across a wide variety of disciplines, supported by programs like the Stanford Institute for Human-Centered Artificial Intelligence and Stanford Data Science as well as the new Marlowe, Stanford's newest high-performance computing cluster.

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Report outlines Stanford principles for use of AI

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The AI at Stanford Advisory Committee's report includes recommendations for AI use in the university's administration, education, and research.

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Syracuse University: Inaugural Assistant Vice President for Enterprise Data and Artificial Intelligence

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Syracuse University: Inaugural Assistant Vice President for Enterprise Data and Artificial Intelligence

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Andrew Joncas Appointed as Inaugural Assistant Vice President for Enterprise Data and Artificial Intelligence

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Information Technology Services (ITS) has announced the appointment of Andrew Joncas as the division’s first assistant vice president for enterprise data an…

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Belmont University: Executive Director, Belmont Data & AI Collaborative

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Belmont University: Executive Director, Belmont Data & AI Collaborative

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Belmont University has named Dr. Michael "Jeff" Donahoo executive director of the Belmont Data & AI Collaborative , marking the transformation of the former Belmont Data Collaborative to include artificial intelligence alongside its data science initiatives.

Joining from Baylor University, where he served as professor of computer science and co-creator of its interdisciplinary cybersecurity program, Donahoo brings more than 25 years of experience in computer science education and research. His expertise spans networking, cybersecurity and computer systems design.

"Data and AI offer powerful opportunities to magnify impact in every domain," said Donahoo. "The BDAIC focuses on contributing to Belmont's remarkable efforts through collaboration and equipping students, faculty and staff to innovate, inspire and drive the future."

Donahoo's career includes serving as deputy executive director of the International Collegiate Programming Contest (ICPC) and director of research and development at the Central Texas Cyber Range. A prolific author and researcher, Donahoo has published numerous peer-reviewed articles and co-authored several books in the Morgan-Kaufmann Practical Guide series. His recognition includes multiple teaching awards at Baylor University, along with significant research funding throughout his career.

In his role as executive director, Donahoo will lead the Collaborative's strategic initiatives and partnerships, oversee the development of data and AI education programs and work with stakeholders across campus and the broader Nashville community to advance the University's vision for data innovation.

As organizations increasingly rely on artificial intelligence and data science, universities must evolve their approach to education and research. Situated in one of the nation's fastest-growing tech hubs, Belmont is uniquely positioned to leverage regional strengths in health care innovation and entrepreneurship. From 2017 to 2022, tech jobs in Middle Tennessee , surpassing overall job growth in the region by 7%.

This dynamic growth, combined with AI-related industries contributing more than $15 trillion to the global economy in 2023, underscores the importance of Belmont's expanded initiative in AI and data science. The University is adapting to meet community needs by preparing graduates to lead responsibly in this rapidly changing landscape.

"At Belmont, we are empowering students to lead in a world where data and artificial intelligence are fundamentally changing how we work and solve problems," said Dr. Erich Baker, vice provost for research & strategic initiatives and professor of computer science. "Our graduates will not just understand these technologies; they'll know how to harness them responsibly to drive innovation and create positive change."

The Collaborative will serve as Belmont's central hub for data and AI education, leading a comprehensive university-wide strategy that combines research partnerships, industry collaboration and initiatives in digital innovation and transformation.

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New Executive Director for Data and AI Initiative

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Belmont University appoints Dr. Jeff Donahoo to lead expanded Data & AI Collaborative, bringing expertise in cybersecurity and computer science to advance AI education and research.

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Artificial intelligence offers an opportunity and an imperative for enhanced critical-thinking skills.

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Boston University: AI and Education Initiative 2024 Faculty Grant Award Recipients

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Boston University: AI and Education Initiative 2024 Faculty Grant Award Recipients

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The AI and Education Initiative Faculty Research Grants program provides $15,000 to support faculty-led research on artificial intelligence and education. The mission is to evolve and advance Boston University's research in AI and education, accelerating research for future funding and broader impact.

Congratulations to our AI and Education Initiative 2024 Faculty Grant Award Recipients.

To learn more about the AI and Education Initiative, visit the website or email Naomi Caselli, director of the AI and Education Initiative, at nkc@bu.edu.

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AI and Education Initiative 2024 Faculty Grant Award Recipients

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The AI and Education Initiative Faculty Research Grants program provides $15,000 to support faculty-led research on artificial intelligence and education. The mission is to evolve and advance Boston University's research in AI and education, accelerating research for future funding and broader impact. Congratulations to our AI and Education Initiative 2024 Faculty Grant Award Recipients.

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The AI faculty fellowships provide support for faculty who have an interest in advancing GenAI scholarship, research and education at the University. The fellowships are for a period of one year, max, and cover four domains of activity (see below). Applicants must provide a budget with their application along with a letter of support from […]

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Scaffold or Crutch? Examining College Students’ (2024)

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Scaffold or Crutch? Examining College Students’ (2024)

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Use and Views of Generative AI Tools for STEM

Education

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Scaffold or Crutch? Examining College Students’

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The New Rules of AI for Student Success | White Paper

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Explore five essential rules for using AI in higher education to improve student outcomes and enhance human support.

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Duke University: AI Policies & Guidelines

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Duke University: AI Policies & Guidelines

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LibGuides: DKU AI Literacy: Policies & Guidelines

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Introduce Artificial Intelligence resources, tools, and ethics for the DKU community.

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EDUCAUSE: Must-Have Competencies and Skills in Our New AI World: A Synthesis for Educational Reform

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EDUCAUSE: Must-Have Competencies and Skills in Our New AI World: A Synthesis for Educational Reform

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The transformative impact of artificial intelligence on educational systems calls for a comprehensive reform to prepare future generations for an AI-integrated world.

Credit: Gannvector / Shutterstock.com © 2024

From its emerging stages as a theoretical concept to its current status as a transformative force, artificial intelligence (AI) has seen a remarkable evolution. The trajectory of AI's advancement-from simple algorithms to sophisticated machine learning models capable of outperforming human expertise in specific tasks-heralds a future in which AI's role is central to every aspect of our lives. The implications for future generations are profound: a shift in job structures, the emergence of new industries, and the overhaul of existing societal norms.

The longstanding call for educational transformation is now culminating with the advent of AI, as it amplifies the need for a shift from rote learning and static knowledge to agility, creativity, and ethical reasoning. The urgency to integrate AI competencies into education is about preparing students not just to adapt to inevitable changes but to lead the charge in shaping an AI-augmented world. It's about equipping them to ask the right questions, innovate responsibly, and navigate the ethical quandaries that come with such power.

A New Model for a New Reality

The new reality that we all must come to terms with is that AI is now everywhere, it is here to stay, and it will be in everything as it is woven into the fabric of our daily lives. Our educational systems must pivot from preparing students for the world as it is to empowering them to succeed in the world as it will be with the rise of modern AI. I propose a tripartite model of competencies and skills integral to thriving in an AI-driven world: intelligent design skills, intelligent human skills, and intelligent data skills (see figure 1). This framework advocates for a comprehensive educational paradigm shift, preparing individuals to navigate the complex interplay of human and AI interactions across various dimensions of society. It sets the stage for not only responding to the AI revolution but anticipating its trajectory, ensuring that the next generation is ready to harness AI's potential for the greater good. The competencies included in this model are not merely additive but should become the bedrock of education in a society where technology and humanity converge. They are the pillars upon which a new AI world is being built-a world in which education should not merely react to technological shifts but actively shape them.

Figure 1. Competencies and Skills Needed for the New AI World

Credit: ©2022 Fawzi BenMessaoud

Intelligent Design Skills: The Creative Synthesis

The first sector of the model articulates intelligent design skills, which represent the creative harmony between human aspiration and technological feasibility. They empower individuals to craft solutions where form meets function and functionality, embedding user-centric principles into the heart of AI solutions and emphasizing the imperative for creative and design thinking in the AI milieu. The competencies within this sector include:

Instrumental and Critical Digital Competence: A profound literacy in digital tools and a discerning approach to digital content and ability to effectively use technology are indispensable. This competence underlines the necessity for individuals to discern and manipulate digital resources innovatively and responsibly within AI paradigms.

Logic and Mind Mapping Competence: The facility for logical structuration and conceptual cartography is vital for the effective design and interpretation of AI systems. This skill set enables individuals to chart and comprehend the logical flow of ideas and systems, which is also central to the construction of algorithms and the delineation of complex workflows.

Systems Competence: An understanding of systemic interdependencies is a requisite for the coherent design of AI architectures. This competence ensures the creation of integrated AI solutions that factor in the multifarious components within a system, ensuring coherent and holistic design approaches.

Creative Design and UI/UX Skills: The craft of designing interfaces that are both intuitive and responsive to user needs emphasizes the centrality of human experience in the AI milieu. This skill entails the ability to create user-centric interfaces that are intuitive and accessible, underscoring the importance of empathy in design and aligning AI systems with human needs and experiences.

Intelligent Human Skills: The Ethical Imperative

This second facet of the model describes intelligent human skills, which are the quintessence of the humane within the digital realm. Reflective, critical thinking and adaptability are not luxuries but necessities, equipping individuals to partner with AI, ensuring technologies are wielded with wisdom and sensitivity. Intelligent human skills focus on personal competencies that are uniquely human and may be beyond AI's capability to replicate. These include:

Assessment and Decision Competence: Shrewdness for critical evaluation and decision-making is a crucial skill for steering AI development. This competence enables individuals to make judicious choices that harmonize with ethical standards and strategic objectives. This skill is essential for guiding AI development and integration within various sectors.

Ethical Competence: In an AI-centric world, the capacity for ethical judgment stands as a safeguard against the potential misuse of technology. This competence is indispensable for ensuring that AI is developed and used responsibly, adhering to moral principles and ensuring that AI systems operate within the bounds of societal values and norms.

Learning Competence: Given the rapid evolution of AI, an enduring commitment to learning and adaptability is paramount, ensuring that individuals remain abreast of technological advancements and their applications. This competence facilitates perpetual intellectual growth and the agile adoption of new AI advancements.

Reflective Competence: The aptitude for introspection and critical analysis is pivotal. This skill entails the capacity for self-reflection and critical thinking and empowers individuals to contemplate the far-reaching consequences and broader implications of AI and its integration into daily life, fostering a culture of mindful engagement with technology.

Prompt Engineering: Also described as intelligent prompting, this skill transcends mere technical proficiency, rising to the nuanced crafting of strategic questions and the formulation of prompts for AI interaction, especially within linguistic models, to elicit the most accurate, relevant, and useful responses. This skill merges creativity with a sophisticated understanding of AI's interpretative capabilities. The development of this skill is essential for professionals across various sectors where AI interaction is prevalent, including technology, education, creative industries, and customer service, among others. As AI technologies become more integrated into daily life and work, the ability to communicate effectively with these systems becomes a critical component of digital literacy.

Intelligent Data Skills: The Analytical Cornerstone

The third segment, intelligent data skills, covers new literacies and highlights the importance of data-centric competencies in leveraging AI. In a data-drenched landscape, the ability to interpret, analyze, and apply data transcends traditional academic boundaries. These skills enable individuals to transform data into decisions, driving innovation and uncovering insights within vast information streams. They are now foundational in this data-driven landscape and include:

Data Veracity Competence: The ability to verify the accuracy and truthfulness of data is critical in an ecosystem in which AI's output quality is inextricably tied to data integrity. Given AI's reliance on quality data for effective decision-making, this skill ensures the reliability and accuracy of AI-generated insights.

Data Digestion Competence: The proficiency in assimilating and elucidating vast datasets is critical for translating data into coherent narratives that can inform AI applications. This skill involves processing and interpreting large volumes of data, making it understandable and actionable for AI systems.

Data Visualization Competence: The artistry of rendering data into visually impactful representations is crucial for distilling and communicating complex data-derived conclusions. This skill is also crucial for communicating insights gleaned from AI analyses.

Data Prepping and Curation Competence: This skill entails the judicious stewardship of data, preserving its relevance and ensuring its utility and quality over time for ongoing and future AI initiatives.

Synthesis for Educational Reform

In this model, educational reform is conceptualized as a bridge between human intelligence and AI. This educational reform underlines the criticality of competencies that enable individuals to innovate and lead in an AI-integrated reality. The model isn't merely a response to change; it's an invitation to shape the future proactively, instilling in learners a blend of creative thought, data proficiency, and ethical judgment. It envisages a curriculum that pivots from static knowledge to dynamic wisdom, preparing students to contribute actively to AI's responsible evolution.

Educational Reform for an AI-Integrated Future

At the heart of our rapidly evolving world lies the potent and promising synergy between humans and AI, and the role of colleges and universities is pivotal in shaping an AI-integrated future. This calls for an educational reform that is nimble, innovative, and far sighted, moving beyond traditions to forge proactive leaders who can skillfully harness AI for the advancement of society. Integral to this reformation is the cultivation of the tripartite competencies-intelligent human skills, intelligent data skills, and intelligent design skills-seamlessly woven into curricular and co-curricular experiences. These competencies are vital in equipping students with an ethical framework, critical thinking, and problem-solving abilities, empowering them to become agile creators and ethical stewards in a world where AI partners in every human endeavor.

Building on this, institutions must rise to the challenge of developing AI and digital competencies across disciplines, fostering curiosity, resilience, empathy, and adaptability. Courses and assessments must evolve to harness AI's potential for personalized learning experiences that are equitable, addressing individual student needs and maximizing outcomes. By integrating AI tools, faculty can enhance teaching, liberating their time for high-value educational practices and fostering student success. Furthermore, AI-powered resources can democratize education, reducing costs and bridging the digital divide, while AI-driven career guidance systems can align educational pathways with the workforce demands of tomorrow.

Yet the full realization of these opportunities hinges on addressing the challenges AI presents, including mitigating algorithmic biases and safeguarding data privacy and security. The transformative education that anticipates these challenges prepares students not merely to participate in the world as it evolves but to actively shape its progression. Thus, by committing to an educational overhaul that champions the convergence of human insight and AI, we craft a legacy of learning, robust and resonant with the needs of the future.

Anticipatory Curriculum Design for Empowering Competence in AI

In this educational landscape shaped by AI's omnipresence, anticipatory curriculum design emerges as a strategic imperative for higher education. Colleges and universities have the task of infusing the competencies of human, data, and design skills into the curriculum, essential skills for thriving in an AI-centric society. This curriculum must ignite students' curiosity, bolster adaptability, and instill a robust understanding of AI's scope and boundaries.

Curriculum designers should integrate intelligent human skills to nurture critical thinking, ethical reasoning, and reflective competencies that AI cannot replicate. Intelligent data skills must be emphasized to enable learners to effectively interpret and utilize data, while intelligent design skills should be cultivated to foster creativity and innovation in AI applications. These competencies must become the bedrock of course development, ensuring that students become not only proficient in technology but also conscientious creators and stewards of AI.

Colleges and universities should align course objectives with these core competencies, incorporating AI tools that enhance personalized instruction and student engagement. Well-structured teaching/learning activities that discourage misuse and invite students to reflect on their learning process should be not simply encouraged but rather expected. To support this, AI's role in tutoring and academic assistance should be leveraged to provide personalized feedback and adaptive learning pathways, especially in high-enrollment courses. By doing so, educational institutions will not only uphold academic integrity but also prepare students to leverage technology ethically and creatively. Through such anticipatory curricular design that proactively integrates these competencies, students will be well equipped to navigate and lead in the AI-augmented landscape. They will emerge as ethical users and innovative drivers of technology, poised for success in a future where human intelligence synergizes with AI for societal progress.

AI in education is something teachers, students, and administrators should not be terrified by. It shouldn't be seen as mystifying, nor should users allow themselves to be simplified or disqualified by it. AI should not displace or devalue human teaching and learning competences and know-how. On the contrary, AI in education should be seen as an opportunity to enhance and enrich the human teaching and learning prowess and potential, to foster creativity and innovation, and to empower learners and educators with new tools and resources. AI in education should augment and complement their aptitude and expertise, to personalize and optimize the learning experience, and to support lifelong learning and development. AI in education should be a national priority and a collaborative effort among all stakeholders, to ensure that AI is designed and deployed in an ethical, equitable, and inclusive way that respects the diversity and dignity of all learners and educators and that promotes the common good and social justice. AI in education should be about the production of AI, not just the consumption of AI, meaning that learners and educators should have the opportunity to learn about AI, to participate in its creation and evaluation, and to shape its impact and direction.

The time is ripe for educators, policymakers, and institutions to forge a new path. Let us unite to architect an educational system that is as intelligent, adaptable, and ethical as the AI it aims to harness. Together we must cultivate a curriculum that not only integrates AI but anticipates its evolutionary path, ensuring our students become the vanguard of innovation. This is a call to action: to embrace the convergence of human insight and AI, to nurture a future where technology amplifies humanity. The moment is now, to commit to an overhaul that will echo through the annals of our time, shaping a legacy of learning that is truly fit for the future we envision.

Fawzi BenMessaoud is AI Program Director at Indiana University Indianapolis.

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must-have competencies and skills in our new ai world: a synthesis for educational reform

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Must-Have Competencies and Skills in Our New AI World: A Synthesis for Educational Reform

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The transformative impact of artificial intelligence on educational systems calls for a comprehensive reform to prepare future generations for an AI-i

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Duke University: DKU AI Literacy: Getting Started (Students & Faculty)

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Duke University: DKU AI Literacy: Getting Started (Students & Faculty)

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LibGuides: DKU AI Literacy: Getting Started

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Introduce Artificial Intelligence resources, tools, and ethics for the DKU community.

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The College of William & Mary: Generative AI: Supporting AI Literacy, Research, and Publishing (Students & Faculty)

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The College of William & Mary: Generative AI: Supporting AI Literacy, Research, and Publishing (Students & Faculty)

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Research Guides: Generative AI: Supporting AI Literacy, Research, and Publishing: Home

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Research Guides: Generative AI: Supporting AI Literacy, Research, and Publishing: Home

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Icahn School of Medicine at Mt. Sinai: Artificial Intelligence (AI) in Learning and Discovery: AI Literacy & Competencies (Students & Faculty)

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Icahn School of Medicine at Mt. Sinai: Artificial Intelligence (AI) in Learning and Discovery: AI Literacy & Competencies (Students & Faculty)

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Levy Library Guides: Artificial Intelligence (AI) in Learning and Discovery: AI Literacy & Competencies

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Levy Library Guides: Artificial Intelligence (AI) in Learning and Discovery: AI Literacy & Competencies

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GALILEO@UGA Subject Guides: AI Literacy : What is AI?

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GALILEO@UGA Subject Guides: AI Literacy : What is AI?

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Oregon State University: Promoting Students’ AI Literacy

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Oregon State University: Promoting Students’ AI Literacy

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Promoting students' AI literacy

Why AI literacy?

Students will need to develop a skill set for using and interacting productively and ethically with AI tools, for personal, school-related, and work-related reasons. Some technical disciplines may decide to strategically integrate these skills into their curricula to help prepare students for rapidly changing workforce needs. In other disciplines, teaching students how to use AI may not be explicitly necessary as part of the established program or course learning outcomes, for example; but faculty may wish to help students develop their skill set in a way that prepares them to be informed students, engaged citizens, and effective members of their chosen profession. Incorporating AI literacy into diverse courses may be expedient in much the same way that many faculty have integrated critical thinking and digital literacy skills previously. (Faculty or disciplinary groups may decide that encouraging AI use leads to a loss of learning - a perspective we are not focusing on here.)

AI literacy frameworks

AI researchers and scholars have already posited frameworks for teaching this skill set, which Laupichler, et. al (2023) point out is often termed AI literacy. They describe AI literacy as: "the ability to understand, use, monitor, and critically reflect on AI applications without necessarily being able to develop AI models themselves." Conceptualized in this way, AI literacy is a broad set of skills that is not confined to technical disciplines. Laupichler, et. al., also provide a helpful overview and comparison of recent studies and frameworks related to AI literacy that we recommend as a starting point for any faculty wishing to know more about teaching AI skill development.

Of important note: the studies and frameworks included in that literature review predate the release of ChatGPT in November 2022. We anticipate that these frameworks will be revisited and revised to account for the now widely-available generative AI tools, as well as in light of the rapid and ongoing advancements in these tools. However, the frameworks provide a useful point of departure for those thinking about how to incorporate AI literacy into their courses.

Take, for example, the four categories of skills that Ng, et. al. (2021) describe:

These categories highlight different discrete skills that could be introduced and advanced in meaningful ways within higher education courses.

Addressing AI literacy

Faculty need not delve deeply into AI literacy development to help students navigate with these new technologies. All courses would, in fact, benefit from even the lightest-touch approach to AI ethics where faculty explicitly address how AI can/can't and should/shouldn't be used in that particular course. Faculty might also offer an open invitation to discuss further with the class how and why those guidelines have been selected and what they mean in the context of activities and assignments in the course.

For faculty who may choose to allow the use of AI tools in the course, providing students structured guidance and resources about how to use them could help to further equity in the course since some students may have more familiarity with and access to AI tools than others. For example, in a course that includes an individually-produced term paper, and where students are allowed to use AI tools to generate and evaluate potential topics, faculty might provide an effective example of how to ask an AI tool to help, ideally situating explanation in the context of what would be appropriate and ethical in that discipline or profession.

Further reading on AI literacy and integration

Carvalho, L., Martinez-Maldonado, R., Tsai, Y., Markauskaite, L., & De Laat, M. (2022). How can we design for learning in an AI world?. Computers and Education: Artificial Intelligence 3.

Mollick, E. & Mollick, L. (12 June 2023). Assigning AI: Seven approaches for students, with prompts. SSRN.

Pomerlau, M. (2023). Integrating AI into college writing and communication courses. Tech Style.

Southworth, J., Migliaccio, K., Glover, J., Glover, J., Reed, D., McCarty, C., Brendemuhl, J., Thomas, A. (2023). Developing a model for AI Across the curriculum: Transforming the higher education landscape via innovation in AI literacy. Computers and Artificial Intelligence 4.

The University of Sydney. (2023). AI in education. [Note: Self-paced Canvas course created by students for students.]

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Oregon State Ecampus offers 110+ accredited online degrees, undergraduate and graduate, including business, computer science, natural resources and fisheries.

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University of Oregon: Artificial Intelligence Resource Guide

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University of Oregon: Artificial Intelligence Resource Guide

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Intelligence

Resource Guide

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Instructors are experimenting with a variety of ways to include use of GenAI systems in their courses. The Teaching and Generative AI resource provides ideas, including examples from UO instructors, on how to:

Promote analysis and critical thinking

Assist research and brainstorming

Contribute to writing and revision

Facilitate icebreakers

Mitigate use of GenAI

Explore GenAI Teaching Ideas

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Instructors are experimenting with a variety of ways to include use of GenAI systems in their courses.

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Elon University & AAC&U: AI-U/v1.0: A Student Guide to Navigating College in the Artificial Intelligence Era

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Elon University & AAC&U: AI-U/v1.0: A Student Guide to Navigating College in the Artificial Intelligence Era

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Student Guide to Artificial Intelligence

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Homepage - Student Guide to Artificial Intelligence

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Learn about Artificial Intelligence (AI) and how it’s transforming higher education. This guide explores what AI is, its applications, and how it’s shaping careers.

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Belleview University: Student Guide to AI

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Belleview University: Student Guide to AI

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Stay curious and remember that your voice matters!

Know the Rules and Understand the Tools

Is generative AI allowed?

Policies will be different from program to program, course to course, and even assignment to assignment, so always take the time to find out 1) if using generative AI is allowed, and 2) how using generative AI is allowed.

Check the syllabus for guidance.

Check assignment instructions for guidance.

If you aren't sure, ask your instructor!

If generative AI is allowed, use it responsibly.

Follow all assignment instructions and ask questions. Make sure you follow instructions for how AI usage is allowed.

Learn about a generative AI tool before you use it.

Consider what you are learning and how generative AI can support your learning process.

Evaluate and verify any material created using generative AI. Remember, you are accountable for what you include in your assignments.

Be transparent about your use of generative AI and include attribution.

Keep your focus on your learning. Can you explain all concepts and topics without the use of generative AI?

AI Tool Provided by Bellevue University

AI and Career Development

Consider and explore how industries you work in or are interested in working in are using AI. What do you need to learn about AI to be prepared?

Common AI Terminology

Artificial Intelligence (AI): A computer that can learn from experience, solve problems, and make decisions on its own.

Big Data: Massive collections of information or data that AI uses to learn and make decisions.

Generative Pre-trained Transformer (GPT): Used to answer questions and generate text and graphics in response to a prompt.

Machine Learning (ML): Allows computers to learn from data.

Natural Language Processing (NLP): Helps computers understand, interpret, and generate human language.

Prompts: Textual inputs (e.g., questions, instructions) that you enter into ChatGPT to get responses.

Additional Topics to Consider

Accuracy and Accountability

Generative AI may not be accurate and may hallucinate sources. Make sure to verify any claims made or sources provided by generative AI. Remember, you are accountable for what you include in your assignments.

Data Privacy

If you use an AI tool, have you reviewed and considered how your data is being protected? Have you reviewed if or how your data is being used?

Ethics

Academic integrity is an essential part of academic excellence. As a student you are accountable to PS 1901 Student Code of Conduct. If you are not sure if your AI usage is ethical, please ask! We are here to help you learn and succeed!

Additional ethics considerations:

Copyright concerns about what information is used to train generative AI and who owns what is produced.

Digital divide concerns regarding what access to AI costs and the quality of free versus paid access to generative AI tools.

Environmental concerns around the resources required to power AI.

Misinformation and bias concerns around the content created using generative AI.

Stay curious! Explore responsibly, and ask questions when in doubt.

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Know how to use AI responsibly and understand your course or instructor policies regarding use of generative AI. Students are accountable for academic honesty.

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This report describes an ideal future for generative AI in higher education, drawing on the insights of a small panel of teaching and learning higher education experts, focusing on a 10-year timescale.

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use of artificial intelligence in higher education

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impact of artificial intelligence on teaching and learning in higher education

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This page provides resources regarding the use of AI in higher education.

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EAB: 3 Types of Faculty AI Policies Your Institution Needs to Have

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EAB: 3 Types of Faculty AI Policies Your Institution Needs to Have

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3 types of faculty AI policies your institution needs to have | EAB

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This blog helps provosts develop faculty AI policies that clearly outline how to engage with AI in their curricular and teaching practice.

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Florida A&M University (FAMU): Artificial Intelligence (AI) Advisory Council and a Carnegie Research 1 (R1) Task Force

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Florida A&M University (FAMU): Artificial Intelligence (AI) Advisory Council and a Carnegie Research 1 (R1) Task Force

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FAMU Provost Watson Establishes AI Council and R1 Task Force to Strengthen Research, Innovation, and Student Success

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In a decisive step toward advancing Florida A&M University’s (FAMU) strategic priorities, Provost Allyson L. Watson has established an Artificial Intelligence (AI) Advisory Council and a Carnegie Research 1 (R1) Task Force. Both initiatives underscore FAMU’s commitment to preparing students for emerging workforce demands and to positioning the University as a leader in high-impact research.

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University of Nebraska System: University of Nebraska launches AI-focused task force, seeks community input

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University of Nebraska System: University of Nebraska launches AI-focused task force, seeks community input

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University of Nebraska launches AI-focused task force, seeks community input • Nebraska Examiner

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The University of Nebraska has launched a systemwide artificial intelligence task force and seeks input to enhance and understand AI use.

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Artificial Intelligence in Education – Wonderful Treasure Trove of Resources

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Artificial Intelligence in Education – Wonderful Treasure Trove of Resources

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UNESCO: AI Competency Framework for Students

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UNESCO: AI Competency Framework for Students

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This publication aims to help educators integrating artificial intelligence learning objectives into official school curricula to prepare students to be responsible and creative citizens in the era of AI.

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UNESCO: AI competency framework for Teachers

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UNESCO: AI competency framework for Teachers

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Guiding teachers on artificial intelligence (AI) use and misuse in education, this publication defines the knowledge, skills, and values teachers must master in the age of AI.

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EdTech Insiders: AI Instructional Materials

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EdTech Insiders: AI Instructional Materials

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AI can craft written or multimodal materials such as text, videos, quizzes, interactives, games or simulations personalized to student needs, making learning engaging, accessible, and curriculum-aligned.

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Understanding AI Literacy [Framework]. Stanford Teaching Commons.

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Understanding AI Literacy [Framework]. Stanford Teaching Commons.

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A framework that identifies and organizes skills and knowledge you and students can use to navigate the opportunities and challenges of generative AI.

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MIT: AI Hub for Generative AI for Teaching & Learning

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MIT: AI Hub for Generative AI for Teaching & Learning

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MIT Sloan Teaching & Learning Technologies

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Teaching with Generative AI Resource Hub - MIT Sloan Teaching & Learning Technologies

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Explore our Teaching with Generative AI Resource Hub to unlock AI’s potential for enhancing teaching and learning at MIT Sloan.

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MIT Sloan Teaching & Learning Technologies

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MIT Sloan Teaching & Learning Technologies

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MIT Sloan Teaching & Learning Technologies

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Homepage - MIT Sloan Teaching & Learning Technologies

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We connect MIT Sloan to research-driven best practices, resources, and trainings in instructional technology and design. Join our community.

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Washington University in St. Louis: Generative AI Teaching Activities: Online Repository

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Washington University in St. Louis: Generative AI Teaching Activities: Online Repository

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Generative AI Teaching Activities: Online Repository - Center for Teaching and Learning

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Explore the CTL’s online repository of teaching activities contributed by WashU instructors to help students to engage critically with generative AI.

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Eastern Florida State Community College: Artificial Intelligence in the Classroom

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Eastern Florida State Community College: Artificial Intelligence in the Classroom

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LibGuides: Artificial Intelligence in the Classroom: Other Uses of AI in Higher Education

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This Research Guide discusses artificial intelligence, and specifically chatbots: What they are, how they are seen in the higher-education classroom, and the academic-integrity issues arising from student use of AI tools in the classroom What are some other ways that AI is being used in the higher-ed classroom / institution?

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University of North Dakota: AI Assignment Library

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University of North Dakota: AI Assignment Library

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UND faculty created the materials in this AI Assignment Library in the context of ChatGPT and other generative AI's immediate impact on higher education. Faculty who submitted their assignments did an intensive workshop on generative AI and the information landscape which informed their assignment design. Then faculty colleagues peer-reviewed each other's work in an assignment charrette. Assignment authors revised their assignment informed by that feedback. Users are invited to search the assignment library for ideas using disciplines, course level, or student learning outcomes. All assignments are designed to advance student learning in the context of the new information environment created by generative AI.

Submissions from 2024

Using Generative AI in Professional Writing, Renee Cardarelle

Submissions from 2023

Optimization of a Bioreactor, Ali Alshami

Sociology Final Project/Presentation, Allyssa Baumbach

AI and Concerns on Bias and Correctness in Engineering, Stacy Bjorgaard

Partner Discussion using an EHR and ChatGPT, Anne Bodensteiner

SIOP Lesson Plan Analysis, Hyonsuk Cho

Is ChatGPT good at establishing validity?, Travis Clark

Exploring Childhood Psychological Disorders through Chat GPT: Writing Fictional Vignettes from a Parent's Perspective, Virginia Clinton-Lisell

Using ChatGPT to Enhance Law School Assessments, Nikola Datzov

Geopolitics of Outer Space, Francisco Del Canto Viterale

Annotated Bibliography Assignment for an Art History Class, Nicole Derenne

Can Artificial Intelligence, specifically Large Language Models (LLMs), enhance human emotional intelligence responses in a small team work environment?, Jason Evans

Selection of materials for a nuclear rocket engine, Marcos Fernandez-Tous

In-class Debate on ChatGPT, Chris Gable

Doctor of Nursing Practice Transformative Leadership AI assignment, Elizabeth Gotay

Using AI for Diagnosis and Treatment Plan, Andrea Guthridge

A & P Informational Literacy, Amanda Haage

Laboratory Project 2 Temporary Surcharge Fill: Compaction Test, I-Hsuan Ho

Family Theory Framework and Case Analysis using AI Tools, Yi-Ping Hsieh

Generative AI-Assisted Pathway Analysis and Interpretation of RNA-Seq Experiment Data, Junguk Hur

Generative AI in Medical Laboratory Science, Shannon Jongeward

Using Generative AI in the Classroom: Fact-Checking ChatGPT as Part of a Capstone Project, Alison Kelly

Promoting Personal Agency in Nursing Students' Ability to Evaluate Evidence, Kaitlyn Kelly

Humans Emulating Machines: Mimicking Predictive Text Algorithms, Gabe Kilzer

Generative Text AI: towards a personal ethics of use, Merie Kirby

Exploring Potential Impact of AI on Social Work Practice, Barbara Kitko

Informal Writing Assignment for HON 101, Hamzat Koriko

Public Health AI Assignment, Amber Lyon-Colbert

AI Costume Design Assignment, Kylie McDonald

Prison Visitation Policy and Procedure Guide, Meghan Mitchell

Sociological Debate Using AI, Sandra Moritz

What does ChatGPT know about toponyms when looking at maps in GEOG 161?, Douglas C. Munski

Topic Proposal Assignment Sheet, Emily Cherry Oliver

Summarizing Tribal Histories Using ChatGPT, Cynthia Prescott

Integrated Health/Physical Education Lesson Plan, Mike Rerick

What are the ethics of AI in relation to the NASW Code of Ethics?, Lea Saga

Organizing a Class Discussion, Patrick Schultz

Find the Distance to the Moon, Dean Smith

Guidelines for Conducting CBPR in American Indian and Alaska Native Communities and the use of Artificial Intelligence, Julie Smith- Yliniemi

Transformed Writing: AI Applications, Brooke Solberg

Introduction to using generative AI in research literature review for graduate students, Joseph Vacek

Checking ChatGPT for Accuracy, Carolyn Williams

Is AI an Actor?, Emily Wirkus

Leadership Paper, Raquel Zeidlik

Chatting as Brainstorming: Drafting Research Questions with Generative AI in an Introductory Composition Course, Jessica Zerr

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UND faculty created the materials in this AI Assignment Library in the context of ChatGPT and other generative AI's immediate impact on higher education. Faculty who submitted their assignments did an intensive workshop on generative AI and the information landscape which informed their assignment design.

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Middlesex Community College AI-Powered Education Toolkit

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Introducing MCC EduTools, an innovative AI-powered web application designed exclusively for Middlesex Community College. This comprehensive toolkit empowers educators with a suite of cutting-edge features to streamline course creation and enhance student engagement.

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Contact North/Contact Nord: Four Personal Digital Assistants (AI Tutor Pro; AI Pathfinder Pro; AI Teaching Assistant Pro; AI Trades Explorer Pro)

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Contact North/Contact Nord: Four Personal Digital Assistants (AI Tutor Pro; AI Pathfinder Pro; AI Teaching Assistant Pro; AI Trades Explorer Pro)

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Available in English or French | 100% FREE | Your Privacy is Protected

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Q&A: Being a University’s First Chief AI Officer

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Q&A: Being a University’s First Chief AI Officer

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Inside Higher Ed | Higher Education News, Events and Jobs

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Q&A: Tackling the role of a university’s first AI officer

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Mark Daley, CAIO of Western University in Canada, answers questions about his groundbreaking new role.

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Utah Valley University: Faculty Senate and OTL’s Generative AI Resources (AI initiatives)

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Utah Valley University: Faculty Senate and OTL’s Generative AI Resources (AI initiatives)

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Faculty Senate and OTL’s Generative AI Resources | Office of Teaching and Learning | Utah Valley University

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A collection of generative AI resources.

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Indiana University: A.I. Task Force: AI Taskforce & Final Report

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Indiana University: A.I. Task Force: AI Taskforce & Final Report

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A.I. Taskforce: Committees: University Faculty Council: Indiana University

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James Madison University: Task Force on AI & Preliminary Report

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James Madison University: Task Force on AI & Preliminary Report

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Task Force on Artificial Intelligence (AI)

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Task Force on Artificial Intelligence (AI)

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Rochester Institute of Technology: AI Task Force & Final Report

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Rochester Institute of Technology: AI Task Force & Final Report

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AI Task Force at RIT | Artificial Intelligence

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The AI Task Force at RIT was formed to help the university examine important questions and arrive at recommendations for shared solutions, best practices, and ethical approaches that we can carry forward within our institution and as a higher education leader.

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Wisconsin: Governor's Task Force on Workforce and Artificial Intelligence Advisory Action Plan

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Wisconsin: Governor's Task Force on Workforce and Artificial Intelligence Advisory Action Plan

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Overview

Artificial Intelligence (AI) technologies are profoundly shaping the nature of work, altering the skills workers need for success, changing the competitive landscape for employers, and forcing educational and workforce development systems to overhaul their offerings in order to sustain a thriving Wisconsin economy. Already, Wisconsin employers and educational institutions are implementing AI applications in fields ranging from manufacturing and health care to transportation, agriculture, and the sciences.

At the same time, the rise of generative AI offers the potential to advance equity and economic opportunity for the people of Wisconsin. To help harness these technologies and strengthen Wisconsin's workforce for the 21st century and beyond, Gov. Tony Evers signed Executive Order #211, creating the Governor's Task Force on Workforce and Artificial Intelligence.

The task force is expected to serve as a crucial mechanism to adapt and equip a workforce capable of capitalizing on this transformation. The task force is chaired by the secretary of the Department of Workforce Development or a designee with additional leadership from the secretary of the Department of Administration or a designee and the secretary of the Wisconsin Economic Development Corp. or a designee.

Task Force Membership

Other task force members to be appointed by the governor include:

A representative from the University of Wisconsin System,

A representative from the Wisconsin Technical College System, and

Other individuals including members from state and local government and individuals representing the business community, the education community, organized labor, the technology industry, and other leaders from impacted workforce sectors and industries.

Task Force Members
Task Force Charge

The Governor's Task Force on Workforce and Artificial Intelligence is charged with gathering and analyzing information to produce an advisory action plan for the governor. The action plan is expected to:

Identify the current state of generative AI's impact on Wisconsin's labor market,

Develop informed predictions regarding its opportunities and impact for the near term and into the future,

Identify how these workforce opportunities and impacts may touch Wisconsin's key industries, occupations, and foundational skillsets,

Explore initiatives to advance equity and economic opportunity in the face of these changes, and

Based on these findings, recommend policy directions and investments related to workforce development and educational systems to capitalize on the AI transformation.

Action Plan and Public Input

While the action plan will focus on potential policies and investments for the coming three to five years, the strategic directions it establishes may have far-reaching implications for workers, employers, job seekers, and economic development. To assure that Wisconsin communities continue to thrive - with an economy that works for everyone - the task force will provide opportunities for public engagement and input as its work progresses.
Task Force Objectives

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Governor's Task Force on Workforce and Artificial Intelligence

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Artificial Intelligence (AI) technologies promise to profoundly shape the nature of work, altering the skills workers need for success, changing the competitive landscape for employers, and forcing educational and workforce development systems to overhaul their offerings in order to sustain a thriving Wisconsin economy.

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Utah Valley University AI Task Force: Charge & Updates 

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Utah Valley University AI Task Force: Charge & Updates 

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AI Task Force | Academic Affairs | Utah Valley University

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University of Pittsburg: Generative AI Resources for Faculty

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University of Pittsburg: Generative AI Resources for Faculty

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Generative AI Resources for Faculty – University Center for Teaching and Learning

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Welcome to the Teaching Center’s collection of faculty resources for generative AI. Tools like ChatGPT, Dall-E, Google Bard, and many others are now (and will continue to be) fixtures in our teaching and learning work and in our daily lives.

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Utah Tech University: Generative AI Tools: Guidelines for Teaching and Learning

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Utah Tech University: Generative AI Tools: Guidelines for Teaching and Learning

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Center for Teaching & Learning

The ChatGPT Task Force recommends the general guidelines stated below

In March 2023, the Provost established the ChatGPT Task Force to provide guidelines for the appropriate use of ChatGPT and other generative AI platforms in academic classes and assignments. The task force strongly recommends that faculty members follow the guidelines below to help students understand what is expected of them regarding using generative AI tools in the courses you teach.

Become familiar with the capabilities and failings of the technology with respect to your discipline.

Decide on appropriate use of the technology for assigned tasks and assignments.

Update assigned tasks, assessments, and pedagogy to ensure student experiences will best reflect the course, program, and university learning outcomes.

Clearly communicate appropriate and inappropriate use to students; include the reasons for your decisions relating to learning outcomes. This should include a clear statement on your syllabus that contains the following:

When AI is appropriate (list specific assignments and activities)

When AI is not appropriate (list specific assignments and activities)

How AI can be used (summarizing, idea generation, paraphrasing, etc.)

How to cite the use of AI in assignments (footnotes, APA, supporting documents, etc.)

Consequences for violating the assignment or course AI policy (F on assignment, etc.

Talk with your students about generative AI. Discuss opportunities for AI to contribute to your discipline. How will these tools support advancements in your field (medicine, science, art, music, humanities, health, and more)? Discuss the ethical issues and limitations of AI.

Periodically repeat these steps as the technology develops.

This webpage provides additional information and guidelines below for faculty members regarding how to integrate generative AI tools in your courses and assignments to achieve exceptional student learning and success. Please note that these guidelines are interim and will most likely be updated and revised as we continue to explore and understand the possibilities and challenges of these tools.

Sample Syllabus Statements and Department Statements Regarding Generative AI and ChatGPT

"It is expected that students will adhere to generally accepted standards of academic honesty, including but not limited to refraining from cheating, plagiarizing, misrepresenting one's work, and/or inappropriately collaborating. This includes the use of generative AI tools that has not been cited or documented or authorized. Students will also be expected to adhere to the prescribed professional and ethical standards of the profession/discipline for which the student is preparing. Any student who engages in academic dishonesty or who violates the professional and ethical standards for the profession/discipline for which the student is preparing, may be subject to academic sanctions as per Utah Tech's The Code of Student Rights and Responsibilities" (Eaton, n.d.)

"You may use AI programs e.g. ChatGPT to help generate ideas and brainstorm. However, you should note that the material generated by these programs may be inaccurate, incomplete, or otherwise problematic. Beware that use may also stifle your own independent thinking and creativity. You may not submit any work generated by an AI program as your own. If you include material generated by an AI program, it should be cited like any other reference material (with due consideration for the quality of the reference, which may be poor). Any plagiarism or other form of cheating will be dealt with severely under relevant university policies" (Eaton, n.d.).

"It is expected that students will adhere to generally accepted standards of academic honesty, including but not limited to refraining from cheating, plagiarizing, misrepresenting one's work, and/or inappropriately collaborating. This includes the use of generative AI tools that has not been cited or use documented or authorized. Students will also be expected to adhere to the prescribed professional and ethical standards of the profession/discipline for which the student is preparing. Any student who engages in academic dishonesty or who violates the professional and ethical standards for the profession/discipline for which the student is preparing, may be subject to academic sanctions as per the University Student Code" (University of Utah, n.d.).

"The introduction of new communication technologies often generates and increases anxiety. When composing on computers was introduced, people continued to worry about the new tools of writing. Spell check, Grammarly, email, and computers in the classroom, for example, were criticized for taking away people's ability to spell, remember grammar lessons, or focus in class. Now we consider not just writing, but all of these tools to be helpful if not necessary ways of interacting with language and each other. When people learn to use writing and its tools effectively, writing becomes a powerful instrument for composition and for learning. Consistently focusing on invention strategies, drafting, and revision will complicate students' interactions with such tools as ChatGPT and help them learn how and when to use them. We understand the campus community's concerns about the misuse and abuse of AI tools, and we pledge to work with our colleagues to address them. However, we recognize the opportunity that these new tools offer in terms of teaching and learning. The Department of Writing and Rhetoric Studies reaffirms that teaching writing in all its modalities means engaging students in the writing process by helping them see writing as invention, as intervention, as transformation-in a word, as learning. We teach students not just how to write, but when to write, for what audience, with what purpose, and yes, with which tools. We teach students to consider genre, audience, and purpose and to respect the social and linguistic diversity embedded and circulated in our own department and across the curriculum. We see writing as an integral part of student success in all university contexts and classes that teach and require written texts. Learning to write requires the development of critical tools that help students problematize the structures and the force of writing itself. We teach students how to critically engage with the tools of writing, such as ChatGPT, and their social and pragmatic implications. The Department of Writing and Rhetoric Studies at the University of Utah creates a space for students to gain facility with writing technologies while they learn to understand the implications, promise, power, and responsibility of using such tools" (University of Utah, n.d.).

"During our class, we may use AI Writing tools such as ChatGPT. You will be informed as to when, where, and how these tools are permitted to be used, along with guidance for attribution. Any use outside of this permission constitutes a violation of Bryant's Academic Honesty Policy" (Bryant University, n.d.).

"We recognize that there are a variety of AI programs available to assist writers. AI programs are not a replacement for human creativity, originality, and critical thinking. Writing is a craft that you must develop over time to develop your own individual voice as a writer. However, within limited circumstances, and with proper attribution, AI programs may be used as a tool" (Bryant University, n.d.).

"AI Writing tools such as ChatGPT are welcome in this class, provided that you cite when and how you use the tool. You will be provided with examples of how to cite your use of this tool in your writing" (Bryant University, n.d.).

"ChatGPT will be integrated into the curriculum of this course, specifically in the writing and research components. This will allow students to improve their writing and research skills by receiving feedback and generating summaries" (ChatGPT, personal communication, April 21, 2023).

"ChatGPT will be used in various ways throughout the course, such as generating text summaries, providing feedback on writing assignments, and aiding in research projects" (ChatGPT, personal communication, April 21, 2023).

What are Generative AI Tools, such as ChatGPT?

"Artificial intelligence (AI) is 'the capability of a machine to imitate intelligent human behavior' (Artificial Intelligence, 2011). Advancements in AI have transformed the way we live, including how we teach and learn. Think about some examples of AI-assisted technology you might encounter in education today, including calculators, automated grading tools, text editors, transcription programs, and assistive technology. You may even remember the first iterations of some of these technologies and the conversations about benefits and challenges that followed.

Generative AI applications can generate content, rather than merely analyze existing data, by utilizing Large Language Model (LLM) technology. Many of these applications function as AI-powered chatbots-in other words, users submit a prompt and content is generated in real time in response to that prompt.

One of the more widely known and discussed AI-powered chatbots is ChatGPT. Developed by tech company OpenAI, its large language model was trained using very large datasets, codes, and texts, and it pulls from all this data to generate responses. Using predictive technology, it can "create or revise written products of all kinds, including essays, computer code, lesson plans, poems, reports, and letters" (University of Toronto, n.d.). It's likely OpenAI is also utilizing user prompts and ChatGPT responses to train the model as the company collects data from users and continues to modify and improve the tool.

While ChatGPT is well-known, it is far from the only generative AI system. In fact, the range of AI tools available is expanding on an almost weekly basis as companies develop their own versions. Educators may be primarily focused on AI's ability to generate text, but it is worth noting that ChatGPT and many other AI applications can also create code, images, music, and other media" (The Ohio State University, n.d.).

For a big picture overview of generative AI tools and ChatGPT, click on the link below to access a 29-minute course in Pluralsight ( instructions on how to login to Pluralsight)
ChatGPT and Generative AI: The Big Picture
Some additional examples of generative AI applications include:

Are students using these generative AI tools? Yes, many students have been exploring and using these tools to support completion of their coursework.

Potential Benefits

Generative AI tools can have several benefits in higher education. They can help design and organize course materials, personalize course material based on students' knowledge gaps, skills, generate original text, images, and sound by responding to prompts, etc.. These tools can also lead to more personalized and efficient learning experiences and increased accessibility to information (Perplexity.ai, personal communication, April 21, 2023). Below are four potential benefits.

"Provides learners a tool for generating rough drafts, outlines, and brainstorming notes. Generative AI applications like ChatGPT can assist students during the earliest stages of the writing process, auto-generating text for learners who are either stymied by writer's block or stuck during the brainstorming process. When prompted, these systems can produce reams of raw content (of varying levels of quality and accuracy) that students can further evaluate, interrogate, and research. Using AI tools in this fashion can help students during the difficult preliminary stages of the composition process, creating a workable path toward their own inquiries and investigations (Gero, 2022; Krause, 2022; Weissman, 2023).

Summarizes and clarifies longer or potentially difficult texts. AI chatbots can also condense and summarize longer texts with only moderate error, potentially aiding students during the reading and research process. They may help in clarifying and explaining daunting or challenging texts in simple, digestible language. This function might potentially help learners (especially English language learners) gain a deeper comprehension of dense academic materials by making obscure prose and concepts more approachable and accessible (Anson and Straume, 2022; Warner, 2022). ​

Assists learners with automated grammatical assistance and language acquisition. When prompted, generative AI applications like ChatGPT can provide direct and immediate automated assistance for students struggling with grammar, mechanics, and syntax. They can identify, explain, and even correct basic grammatical mistakes. Additionally, AI language systems can function as a fluent conversation partner for informal language practice. This might be of particular benefit for English language learners and multilingual students who are still learning the basic mechanics of writing in English (Warner, 2022).

Promotes wider classroom discussion around rhetoric, style, and AI literacy. Generative AI applications also provide an avenue for discussing various facets of rhetoric, authorship, and academic integrity with students. They can function as the focal point of a broader conversation about the ethical questions posed by AI language systems, especially as their continued use and development alters our understanding of plagiarism and cheating. Using generative AI, we can help students develop their own style, skill, and voice as authors, particularly when we ask them to review and discuss their work in contrast to machine-generated texts (Fyfe, 2022; Grobe, 2023; Anson and Straume, 2022)" (The Ohio State University, n.d.).

Current Limitations

It is important to carefully consider the limitations of generative AI tools as you integrate them in your courses. These tools are constantly learning and evolving but, as of the date of this document, some limitations include the items below.

"Generative AI applications use predictive algorithms to generate text based on user input. It replicates, but cannot replace, human agency and expression. Despite their relative fluency and adaptability, they cannot comprehend the meaning behind their words or exhibit human-like levels of critical thinking. This disconnect sometimes leads to text that sounds stilted, makes insubstantial claims, and lacks the subtle intricacy of human expression. AI can also commit rhetorical errors with relative frequency, pepper its texts with meaningless filler phrases, and over-rely on certain writing formulas. For instance, ChatGPT has a strong preference for five paragraph essays with short, three-sentence paragraphs and often overuses single word modifiers and transitions (Grober, 2023; University of Central Florida, 2023). Because of the way AI operates, below are some primary limitations.

Generates incomplete, inaccurate, or false information. Although they draw from vast datasets of text, AI-powered chatbots remain limited to the information available to them at the time of their training. In other words, they cannot access or consult with external sources of information, nor can they self-correct or fill knowledge gaps with correct information. For example, ChatGPT often punctuates its responses with obvious fabrications, failing to maintain accuracy when tasked with generating knowledge outside its dataset. Users can also prompt ChatGPT to churn out obvious misinformation and nonsense, making it generate "garbage output" that is presented credibly and uncritically. In particular, it struggles when prompted to generate text about current events or recent developments, particularly on anything that has occurred after 2021 (Fyfe, 2022; Schatten, 2022; Grobe, 2023).

Includes plagiarized text without proper attribution. Generative AI's understanding of American academic integrity and copyright standards is virtually nonexistent. Texts generated by language models have consistently committed frequent and flagrant acts of plagiarism, from direct, word-for-word plagiarism to misrepresenting others' ideas as their own (Tutella, 2023).

Reiterates biases and is prone to discriminatory, non-inclusive language. Generative AI applications can sometimes employ biased or discriminatory language, repeat extreme or controversial viewpoints, or slip into explicit racism, sexism, homophobia, transphobia, and so on. Even when safeguards are added to filter out some of the more extreme or discriminatory positions, AI language systems are still prone to generating text that reinforces certain stereotypes, biases, and belief systems (Hutson, 2021)" (The Ohio State University, n.d.).

Integrating AI in Teaching

For over two millennia, scholars and teachers have been wary of emerging technologies that might reduce students' ability to learn and create. Even Plato opposed the relatively new invention of writing, claiming it would prevent students from memorizing and understanding content (Fowler, 1925). This suspicion has continued in modern times with educators resisting the advent of typewriters, word processors, home computers, calculators, and even the Internet. But in time, these technologies have become commonplace, and it is now hard to imagine a classroom or curriculum without them. With this history in mind, the ChatGPT Task Force encourages faculty members to embrace the latest emerging technology, generative AI. In integrating these new learning technologies, it is wise to engage in dialogue around their advantages and implications for teaching and learning. Each section below offers suggestions for supporting your students to develop knowledge and skills around AI while maintaining an evidence-based lens on instruction.

Align to Learning Goals and Outcomes

When trying to decide on the adoption of any new learning technology or teaching strategy, begin by reflecting on course goals and learning outcomes. Then decide whether integrating or allowing the technology in your course can enhance learning and support specific assessments and activities (Wiggins & McTigue, 2005). Activities and assignments designed to support students' self-directed learning or develop their skills in leveraging the latest technologies for professional practice could potentially require different approaches to AI than those focused on fostering creativity or reflective practice.

Reflecting on your course goals prior to deciding if and how to integrate generative AI technology will help you align your learning objectives, assessments and course activities to acheive exceptional student learning and success. Activities and assignments that scaffold the process of learning, as opposed to those that assess the product of learning (e.g., student-developed artifacts such as written assignments, code, or media), may be well-suited to the integration of generative AI applications. When using potentially transformative technologies such as generative AI in your course, strive to create learning experiences that enable students to practice what Bloom (1956) considers, "... the more complex classes of intellectual abilities and skills," such as applying, analyzing, evaluating, and creating.

In the table below developed by the Teaching and Learning Resource Center at Ohio State University (The Ohio State University, n.d.), consider how the use of generative AI in each learning activity supports the example learning outcome.

Learning Outcome

AI-Supported Learning Activity

In Nursing, students should be able to summarize research behind evidence-based practice.

Students work in groups to examine and critique AI output of a literature summary vs. human-based summaries and consider the implications for how they inform a specific clinical practice scenario.

In Sociology, students must be able to examine literature reviews to establish the background for proposed research.

Using relevant disciplinary databases and Google Scholar, students track down the citations (students might need some guidance here) in an AI-generated literature review to evaluate 1) whether the citations exist and 2) how relevant they are to the proposed research.

In a Biology lab experience, students must be able to articulate valid experimental methods that contribute something novel to scientific knowledge.

Putting themselves in the position of scientific peer reviewers, students evaluate and critique AI output of a methods statement vs. human-based statement for validity and for how it articulates its contribution to the science.

In an Academic English Writing Program course, multilingual and international students must identify rhetorical patterns in a range of genres in American academic contexts.

Students use AI to generate three different passages paraphrasing a key source for a paper making an argument, note patterns among the different passages (how the passages represent the author's points, what is emphasized, their accuracy, critique potential bias in point of view or language), and in an annotation, choose which passage is most useful for their argument and explain how they would revise it for their paper.

Active Learning
"AI-supported learning activities are a great opportunity to use active learning strategies to foster engagement and create a student-centered experience. Active learning can be broadly described as "any instructional method that engages students in the learning process" (Prince, 2004). Recent meta-analyses have established its value both in terms of student learning (Freeman et al., 2014) and equity (Theobald et al., 2020). You might intersperse small-scale activities like Think-Pair-Share and polling during lecture, reference AI for low-stakes brainstorming or Writing-to-Learn activities, or plan more structured and time-intensive activities that utilize AI output such as case studies, student-led discussions, debates, and peer review" (The Ohio State University, n.d.)

Course Design
"Consider utilizing ChatGPT and other AI tools explicitly. After experimenting with ChatGPT you may decide that you want to incorporate exercises where students are explicitly encouraged to interact with ChatGPT.

Examples:

Ask students to use ChatGPT and "fact check" the response provided by finding primary and secondary sources to back up the information provided.

Ask students to generate a first draft using ChatGPT then keep track changes in a document to refine/edit.

Reflecting upon prompt engineering-use prompting logic used by students to generate information and then provide a different prompt to help guide revision. Showcase that small changes can lead to major differences in output!

The University of Wisconsin, Madison provides some examples for how to integrate AI into the writing process in your classroom (University of Wisconsin-Madison, n.d.).

Adapt or create assignments that are not easily completed using AI. Be more explicit about having students provide references for assignments, use a social annotation tool like Hypothes.is or Perusall, utilize comments, Microsoft Word Track Changes or Google Docs Suggesting mode for individual or group annotation, have students complete written assignments in class, ask students to connect learning to their personal experiences and/or current events. Support students in developing oral communication skills by providing more opportunities for in-class presentations (or during discussion sections).

Require students to make a connection to class discussions. Prompt students to explicitly reference in-class discussions, lecture material and course readings in their homework assignments in addition to using generative AI tools to help with their homework assignment" (University of California, Los Angeles. (n.d.).

Communicate with your students about AI

It is very important to clearly communicate appropriate and inappropriate use of generative AI tools to your students. Be transparent concerning the reasons for your decisions relating to learning outcomes. Have open conversations discussing generative AI tools and give some examples of how these tools are being used in education and the workplace generally. Below are additional ideas to encourage communication with your students.

"Discuss opportunities for AI to contribute positively to your discipline.

Discuss the potential. Many of our students will go on to become leaders at organizations that utilize and/or develop new AI technologies. How will these tools support advancements in your field (medicine, science, art, music, humanities, health, and more)?

Prepare students for the future when they will work and interact with AI. This technology is likely to develop and become embedded in many parts of our lives. Preparing students to thoughtfully engage with it, co-create with it and be curious about and know how to interact with other technological developments as they occur.

Seize the opportunity to center the importance of critical thinking and digital literacy. Students will have the opportunity in the future to break the cycle of spreading disinformation, lack of journalistic integrity in news, and elevating accurate and factual research and scholarship. Emphasize the importance of digital literacy, research, and writing skills with students; connect students to library resources for research and writing. As educators, we have an obligation to help guide our students through many types of literacy, including digital media and AI literacy.

Lean in to talking to your students about how learning happens (deep learning occurs when learners reflect on their learning process and patterns). Talk with students about how they learn and how course assignments contribute to their learning. Learning happens when actively engaging with the course material, through conversations and dialogue leading to deepening conceptual understanding.

Discuss the ethical issues and limitations of AI.

Facilitate discussions with your students on the impacts of spreading disinformation or biased information, lack of regulation of companies that develop these technologies, and other dangers. While students will likely still continue to use ChatGPT and other tools like it, it is crucial that our community has this shared understanding of both dangers and opportunities.

Our nation has yet to catch up to the regulation needed to prevent the potential for tremendous harm when false or biased information is taken as fact. Our community must continue to explore the value and innovation that can come from AI while simultaneously contributing to the dialog about these potential harms.

Ensure equity and accessibility concerns are addressed. As with any emerging technology, ChatGPT may not always be accessible by individuals with disabilities. As the technology evolves, there may be a cost to using it, so continuing to revisit your learning goals and activities with respect to access is a critical equity issue" (University of California, Los Angeles. (n.d.).

"Cultivate an environment in your course in which students will feel comfortable approaching you if they need more direct support from you, their peers, or a campus resource to successfully complete an assignment. To take steps toward cultivating this environment, you might include a question about generative AI on your introductory course survey to understand your students' potential interest and concerns about the tool" (Barnard College, n.d.).

References and Further Reading

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Anson, C., and Straume, I. (2022). Amazement and trepidation: Implications of AI-based natural language production for the teaching of writing. Journal of Academic Writing, 12(1), 1-9. https://doi.org/10.18552/joaw.v12i1.820

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Bean. J. (2011). Engaging ideas: The professor's guide to integrating writing, critical thinking, and active learning in the classroom. Jossey-Bass.

Barnard College. (n.d.). Generative AI & the College Classroom. Retrieved April 21, 2023 from https://cep.barnard.edu/generative-ai-college-classroom

Bloom, B.S., Engelhart, M. D., Furst, E. J., Hill, W. H., & Krathwohl, D. R. (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive domain. New York: David McKay Company.

Bryant University. (n.d.). Sample Syllabus Statements Regarding AI and ChatGPT. Retrieved April 21, 2023 from https://cte.bryant.edu/sample-syllabus-statements-regarding-ai-and-chat-gpt%EF%BF%BC/

Caines, A. (2023, January 27). ChatGPT and good intentions in higher ed. Is a Liminal Space. Retrieved March 1, 2023, from https://autumm.edtech.fm/2022/12/29/chatgpt-and-good-intentions-in-higher-ed/

Carvalho, L., Martinez-Maldonado, R., Tsai, Y. S., Markauskaite, L., & de Laat, M. (2022). How can we design for learning in an AI world? Computers and Education: Artificial Intelligence, 3. https://doi.org/10.1016/j.caeai.2022.100053

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Generative AI Tools for Teaching and Learning | Center for Teaching & Learning | Utah Tech University

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Center for Teaching & Learning In March 2023, the Provost established the ChatGPT Task Force to provide guidelines for the appropriate use of ChatGPT and other generative AI platforms in academic classes and assignments. The task force strongly recommends that faculty members follow the guidelines below to help students understand what is expected of them regarding using generative AI tools in the courses you teach.

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University of Illinois System: Generative AI Guidance for Students

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University of Illinois System: Generative AI Guidance for Students

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Oklahoma State University: Leveraging AI Tools Responsibly: Strategies for University Students

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Oklahoma State University: Leveraging AI Tools Responsibly: Strategies for University Students

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Student Artificial Intelligence Support - Oklahoma State University

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Artificial Intelligence (AI) tools, such as ChatGPT, Google Bard, or Microsoft Bing, can be valuable resources for university students, assisting with research, writing, and learning. However, it is crucial to utilize these tools ethically and responsibly. The following strategies will support students in making the most of AI tools while maintaining academic integrity and ethical conduct. Each of the 10 sections have an accompanying video linked at the top of its respective section.

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University of Southern California: AI Tools for Student Assignments

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University of Southern California: AI Tools for Student Assignments

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This resource provides a brief introduction to AI generators with considerations and examples of how these tools can be incorporated into assignments to advance student learning.
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AI tools for student assignments - USC Center for Excellence in Teaching

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This resource provides a brief introduction to AI generators with considerations and examples of how these tools can be incorporated into assignments to advance student learning.

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Pennsylvania Training and Technical Assistance Network (PaTTAN): AI Toolkit for Students & Teachers

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Pennsylvania Training and Technical Assistance Network (PaTTAN): AI Toolkit for Students & Teachers