Navigating GenAI: Implications for Teaching and Learning

Start by building essential knowledge and understanding the institutional landscape.

• Ground yourself in the basics: learn what GenAI is, how it works, and its potential in classrooms.
  • Explore: Foundations of Generative AI: Large Language Models
    This introductory guide from Harvard's metaLAB offers a clear, accessible overview of what generative AI is, how it works, and what educators should know.The metaLAB has also published a quick start guide for Getting Started with ChatGPT (PDF file)
  • Read: A Review of the Major Models: Frontier (M)LLMs, Deep Researchers, Canvas Tools, Image Generators, Video Generators, Stephan Bauschard
    This article provides an in-depth overview of the latest developments in AI tools and models as of 2025, focusing on how they're transforming education, research, and creative work. It explains the evolution of frontier AI models, which handle text, images, audio, and video, and act more like intelligent agents through tool use, planning, and memory. 
    
  • Watch: Wharton Interactive Crash Course: Practical AI for Instructors & Students: Part 1 of a 5-Part Series (Find the rest on YouTube)
    This five-part video series is designed for educators and students exploring AI in the classroom. Each part focuses on a different dimension of using GenAI effectively. 

• Familiarize yourself with available campus AI tools.
  • Explore: Licensed Generative AI Tools, Berkeley AI Hub
    This page lists AI tools that are approved for campus use, highlighting the data protection level (P1/P2/P3), and any usage restrictions.

• Review campus, departmental, and program GenAI policies.
  • Read: Understanding GenAI and Campus Expectations, UC Berkeley Center for Teaching and Learning
    This page highlights Berkeley’s 2025 Faculty Senate Working Group guidance: individual faculty are empowered to decide on incorporating or prohibiting GenAI in their courses, with arguments presented for both approaches to help inform course policies.
    
  • Read: Appropriate Use of Generative AI Tools, UC Berkeley Office of Ethics, Risks, and Compliance Services
    This advisory outlines responsible use of generative AI when working with different types of university data. It specifies which data protection levels (P1–P4) are allowed and spells out prohibited uses (like inputting student records, proprietary research, or using AI to complete academic work without instructor approval).
  • Read: UCB Guidelines for the Use of Generative AI and Permissible Use Cases, UC Berkeley People & Culture
    These guidelines address the use of AI in the operations of UC Berkeley (the “University”.)
  • Explore: Example of Departmental AI Policy: Berkeley Law Generative AI Policy

• Understand UC Berkeley's academic integrity policy.
  • Explore: Academic Integrity and Support, UC Berkeley International Office
    This page outlines examples of plagiarism and academic dishonesty–including GenAI misuse–and offers strategies and resources to avoid violations.
  • Explore: Academic Misconduct, UC Berkeley Center for Student Conduct
    This resource defines the types of academic misconduct recognized at Berkeley and explains students’ responsibilities under the Code of Student Conduct.
  • Explore: Graduate Student Academic Integrity, UC Berkeley Graduate Division
    This page explains Berkeley’s expectations for graduate students regarding scholarly research and writing, including responsible attribution, avoidance of plagiarism, and compliance with academic standards.

No matter how you plan to use (or not use) GenAI in your course, your students need clarity. Turn foundational knowledge into clear course guidelines.

• Draft or adapt your course GenAI and academic integrity statement, and add your policy to the syllabus or course site.

  • Read: Should You Add an AI Policy to Your Syllabus?, The Chronicle of Higher Education
    This article discusses the importance of establishing clear guidelines for the use of AI tools like ChatGPT in academic settings. Gannon emphasizes that, given the increasing prevalence of AI in education, instructors should thoughtfully consider how these tools align with their course objectives and academic integrity standards. He suggests that a well-crafted AI policy can help students understand acceptable uses of AI, promote ethical engagement with technology, and maintain the integrity of the learning process.
  • Read: Communicating Course Policies and Talking with Students, UC Berkeley Center for Teaching and Learning
    This resource helps instructors communicate clear, constructive course policies on generative AI. It outlines how to set expectations, foster transparency and academic integrity, and engage students in thoughtful dialogue about GenAI use. The page provides sample syllabus language for a range of approaches, from full integration to complete prohibition.
  • Read: Creating your course policy on AI, Stanford Teaching Commons 
    This guide encourages reflection on the purpose of an AI policy, offers example statements, and suggests including specifics such as applicable tools, conditions of use, consequences for non-compliance, and the rationale behind the policy. The guide emphasizes transparency and student support, aiming to align AI policies with course objectives and uphold academic integrity.
  • Explore: Example AI course policy statements, created by Lance Eaton
  • Practice: Worksheet for Creating Your AI Syllabus Statement (PDF file), Center for Teaching and Learning, Stanford.
    Draft your policy statement using this worksheet.

• Explore students’ perspectives on GenAI to understand their experiences, concerns, and hopes.
  • Read: Student perspectives on creative pedagogy: Considerations for the Age of AI, Sabrina Habib, Thomas Vogel, Evelyn Thorne 
    This article explores the impact of creative pedagogy on students in higher education, emphasizing the importance of creativity as a teachable skill in the age of AI. It highlights three themes: building confidence, mastering creative processes, and applying creativity practically. The findings suggest that integrating creativity-focused pedagogy prepares students for complex challenges in an AI-driven world.
  • Read: Student Perspectives on the Use of Generative Artificial Intelligence Technologies in Higher Education, International Journal for Educational Integrity
    This article explores student perspectives on GenAI technologies, focusing on their use, attitudes, and implications for academic integrity policies. Conducted at the University of Liverpool, the study found that most students are aware of GenAI tools like ChatGPT, with mixed opinions on their academic use. While supportive of GenAI for grammar and minor assistance, students generally disapprove of its use for complete assignments. The findings emphasize the need for clear, inclusive university policies that balance educational integrity with equitable access to emerging technologies.
  • Watch: Students’ Perspectives on Using AI, Educause

• Discuss expectations and guidelines with your students in class.
  • Read: Holding That Difficult AI Conversation With Learners, Karen Ferreira-Meyers
    This resource guides educators in facilitating nuanced classroom discussions about GenAI, helping instructors address student fears, correct misconceptions, and promote critical technological literacy. It offers a dialogic framework centered on transparency, ethical reasoning, and collaborative inquiry so learners can move from seeing AI as either magical or threatening to engaging with it thoughtfully.

Learn what AI detection tools are, why they often deliver false results, and how misuse can create equity and trust issues.

• Explore: AI Detection Tools, Sacred Heart University
  This resource offers a list of AI detection tools, such as AI Writing Check, GPTZero, and TurnItIn's AI Writing Detection Tool, along with a collection of articles on AI detection in academic settings. It provides links to both tools and articles, making it a comprehensive resource for exploring AI detection options and insights.
• Read: Availability of Turnitin Artificial Intelligence Detection for UC Berkeley, RTL
  These pages offer an overview of Turnitin's AI writing detection feature, released on April 4, 2023, designed to identify text generated by AI tools like ChatGPT. UC Berkeley has currently opted out of enabling this feature for instructors, pending a thorough review to assess its privacy, security, accessibility, and overall functionality. 

• Read: GPT Detectors Are Biased Against Non-native English Writers, Weixin Liang, et. al.
  This article examines the bias inherent in AI-generated text detectors, particularly against non-native English speakers. The authors found that these tools frequently misclassify non-native writing as AI-generated due to linguistic simplicity, while often failing to identify genuine AI content. The study highlights the risks of unfair discrimination in academic and evaluative settings and advocates for developing more inclusive and robust detection methods. Recommendations include enhancing linguistic diversity in non-native samples and reevaluating the reliance on measures like text perplexity, which disproportionately impact non-native speakers.

• Read: Post-Apocalyptic Education, Ethan Mollik 
  This resource offers an in-depth analysis of the challenges AI poses to traditional educational methods, particularly concerning homework and assessments. It examines the widespread use of AI among students, the difficulties in detecting AI-generated work, and the potential negative impacts on genuine learning. The article advocates for reimagining educational practices to integrate AI effectively, emphasizing the importance of fostering critical thinking and authentic engagement in the learning process.

• Read: How Can Educators Respond to Students Presenting AI-generated Content as their Own?, Open AI
  This resource from Open AI offers guidance for educators on addressing instances where students submit AI-generated content as their own. It discusses the limitations of AI detection tools, recommends encouraging students to share their AI interactions to promote accountability, and emphasizes the importance of fostering AI literacy among students.

As GenAI tools evolve, it’s worth reconsidering how students demonstrate learning, and you might need to update coursework to reflect new opportunities and challenges brought by GenAI.

• Review: Bloom’s Taxonomy Revised with AI Included
• Read: Rethinking Assessment Strategies in the Age of Artificial Intelligence (AI), Charles Sturt University
  This guide encourages educators to move beyond traditional testing methods, recommending authentic, adaptive assessments that center critical thinking, relevance, and learning resilience in the GenAI era. 
• Read: Assignment Makeovers in the AI Age: Essay Edition, Derek BruffIn
  This resource examines the necessity of redesigning essay assignments in response to the rise of AI text generation tools.

• Read: A Framework for Designing Assignments in the Age of AI, Harvard College Writing Program
  This guide offers strategies for designing assignments that align with your learning goals while addressing GenAI use. It includes guiding questions, assignment redesign tips, and practical classroom ideas to foster critical thinking, originality, and meaningful student engagement in the AI era.

• Read: Using AI to Implement Effective Teaching Strategies in Classrooms: Five Strategies, Including Prompts, Ethan R. Mollick & Lilach Mollick
  This paper explores how GenAI tools, like ChatGPT, can support evidence-based teaching strategies to enhance learning. It highlights five strategies: providing varied examples and explanations, addressing misconceptions, employing frequent low-stakes testing, assessing student learning, and practicing distributed learning. The paper argues that AI can help educators implement these strategies efficiently, serving as a "force multiplier," while cautioning that instructor oversight is essential to ensure accuracy and relevance in AI-generated materials.

• Explore: AI Resistant Assignments, Washington University
  This guide offers strategies for designing coursework that isn’t easily completed by GenAI. It encourages instructors to think through how AI might respond to assignments and thoughtfully structure tasks that encourage original student thinking.

Ready for more? Here’s the space to challenge, reflect, and connect with what’s tricky about GenAI.

• Explore: "AI & Ethics" slide deck, Torrey Trust
  This presentation examines the intersection of artificial intelligence (AI) and ethics, focusing on the implications of AI in educational contexts. It discusses ethical considerations, potential biases in AI systems, and the responsibilities of educators in integrating AI technologies into teaching and learning. The presentation aims to inform educators about the ethical challenges associated with AI and to promote thoughtful and responsible use of AI tools in education.
• Watch: How AI Can Be Biased & What Can We Do About it?, UC Berkeley People & Culture
• Read: When AI Gets It Wrong: Addressing AI Hallucinations and Bias, MIT Teaching & Learning Technologies.
  This resource examines the challenges of generative AI systems producing biased or inaccurate content. It highlights issues such as AI-generated images and text that perpetuate gender and racial stereotypes, as well as instances where AI tools fabricate data—a phenomenon known as "hallucination." The article attributes these problems to the nature of AI training data, which often includes societal biases and inaccuracies, and to the design of AI models that prioritize generating plausible content over verifying truthfulness. To mitigate these issues, the article recommends critically evaluating AI outputs, understanding the limitations of AI technologies, and fostering open discussions about the ethical implications of AI in educational settings.

• Read: Generative Artificial Intelligence and Copyright Law, Congressional Research Service
  This document examines how generative AI technologies challenge traditional copyright principles. It explores issues of authorship, copyrightability of AI-generated works, and potential infringement in the training and output of generative AI systems. The report highlights ongoing legal cases, decisions, and debates surrounding whether AI outputs can be copyrighted, who owns such copyrights, and how AI training processes may or may not constitute fair use. It also considers legislative and judicial approaches to addressing these unresolved questions in the context of evolving AI capabilities.

• Read: Measuring the Environmental Impacts of Artificial Intelligence Compute and Applications, Organization for Economic Cooperation and Development.
  This article explores the sustainability challenges and opportunities associated with AI technology. It distinguishes between the direct environmental impacts of AI systems, such as energy consumption and greenhouse gas emissions during production, operation, and disposal, and indirect impacts, including both positive and negative effects of AI applications. The report emphasizes the need for standardized measurement frameworks, improved data collection, and policy efforts to mitigate environmental damage while leveraging AI to address sustainability challenges. 

• Approaches to Addressing Student AI Engagement this Fall, August 11, 1:00 p.m.
  Join this session to explore strategies for communicating your expectations around generative AI use in your course. We will discuss common concerns, explore different approaches, and leave with a plan for shaping the classroom culture you want this fall.
• Teaching Peer Review: Helping Students Recognize Their Value in the GenAI Era, August 13, 1:00 p.m.
  Join this session to access a ready-to-use bCourses module that teaches students how to give and receive peer feedback. Learn how peer review can build community, reduce GenAI reliance, foster collaboration, and help students develop essential skills like critical thinking, communication, and self-assessment.
• How AI Literacy Can and Will Impact Academic Integrity, August 19, 1:00 p.m.
  Join this session to explore how fostering AI literacy and clearly communicating the purpose of assignments can reduce academic integrity concerns. Learn strategies to engage students by connecting assessments to their goals and experiences, while promoting critical understanding of generative AI’s workings and impact.