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AI at Berry - Course Design Institute 2026

CDI 2026

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Designing AI Resilient Assignment s By Ashleigh Woods Nursing Faculty at Berry College
Questions
Whitney Jordan Adams, Assistant Professor of English, Rhetoric, and Writing Berry College CDI Tuesday, August 11 Teaching With and About AI: Practical Approaches for Any Discipline
Opening Activity: What Can AI Help Your Students Do Better? Involve Your Students Ask each student for one concrete example of how AI might improve their learning or work. Shift the Framing Move the conversation from policing cheating to building skills — AI is part of their information ecosystem. Your Role Teach students to use AI critically and evaluate its outputs — not just use it uncritically or avoid it entirely.
Questions Students Should Ask About Any AI Output 1 Who created this? What biases might the creator hold? What worldview is embedded in the model? 2 What assumptions are built in? What's taken for granted? What does the AI treat as neutral that isn't? 3 Whose voices are missing? Who isn't represented in the output? Which communities or perspectives are absent? 4 How accurate is it? What evidence supports these claims? Can students verify them with primary sources? 5 How should I cite it? What is my responsibility as a user of this tool and this output?
AI Literacy Across Disciplines Every field has a distinct entry point for teaching students to think critically about AI. History Compare AI-generated narratives with primary sources — where do they diverge? Biology Critique AI explanations of complex processes for accuracy and oversimplification. Business Evaluate AI market recommendations — whose interests do they serve? Rhetoric Analyze rhetorical choices in AI-generated text as a primary object of study. Education Examine how AI represents learning theories — which ones get centered?
"What is the best strategy for a company to increase profits?” AI might recommend: Raising prices Reducing labor costs Automating customer service Eliminating less profitable products Shareholder Higher profit Employees Job loss or increased workl oad Customers Higher prices or reduced se rvice
WORKSHOP DEEP DIVE Three Concrete Examples Rhetoric · Citation Justice · Accessible Communication
EXAMPLE 1 The Rhetoric of AI Have students generate both human and AI versions of an op-ed, argument, or advocacy statement on the same topic. • Analyze audience awareness, rhetorical appeals, and embedded biases • Identify missing perspectives and whose values are centered • Key insight: AI becomes an object of rhetorical analysis, not just a writing shortcut
Rhetoric Activity: What to Look For Tone Does the AI version sound more formal, neutral, or more persuasive than the human version? Why might that be? Evidence Which version cites sources? Which makes unsupported claims and presents them as fact? Audience Awareness Who does each version assume is reading? What cultural knowledge does it presuppose? Missing Voices What perspectives are absent from the AI output? Who would push back on these claims? Have students read both versions aloud and argue which is more persuasive and why.
EXAMPLE 2 Research Rabbit & Citation Justice Use AI research mapping tools to visualize scholarly conversations — then interrogate who's in the map. • Are women scholars cited? Scholars of color? International voices? • Examine the institutional power structures shaping the literature - Who gets to produce knowledge, publish research, and become widely cited? • Connects AI literacy, information literacy, and equity in a single exercise
Citation Justice: Discussion Questions Who gets cited in your field? And equally important…who's consistently missing from those citation lists? How does AI amplify or challenge existing citation patterns? Does it reproduce the canon, or can it surface underrepresented voices? What responsibility do students have? When using AI-generated bibliographies, are students accountable for who gets cited? How can AI help surface underrepresented voices? What prompts or strategies can redirect AI toward more equitable scholarship?
Which universities appear most frequently? Are most authors from the United States or Europe? Which journals dominate the conversation? Who receives research funding? Are scholars from smaller institutions represented? Are scholars from the Global South included? Which perspectives seem marginalized or absent? Questions to Ask Students:
EXAMPLE 3 AI for Accessible Communication Use AI to make your course materials work for every student, not just the ones who already speak academic language. • Simplify complex policies and rewrite instructions in student-friendly language • Generate FAQs and multiple alternative explanations of the same concept • Directly supports Universal Design for Learning and broader student success goals: UDL Guidelines When students understand the instructions, they can focus on the learning!
Accessibility Activity: Try It Yourself Ask AI Request three different explanations Revise Materials Update teaching resources using insights Choose Concept Pick one challenging syllabus topic Evaluate Compare versions for struggling students The goal isn't to outsource your teaching , it's to use AI as a drafting partner that helps you reach more students more effectively.
In your third project, you will be asked to take a site of public memory around Berry College (on campus or in town), in a surrounding town, or in your home community, and deliver a presentation that discusses what the site shows about what the site is attempting to convey to a general public audience. This project asks you to do a type of close, rhetorical reading of the site and analyze any “text,” be it discursive (relating to language) or non-discursive (not relating to language). You will then illustrate how this public memory attempts to create community (or not) for the people of Berry College or the town. The presentation will be about six to seven minutes in length. PowerPoint or Adobe Express Webpage are two suggested programs you can use to complete this presentation. Original Prompt: Project Three: The Local Public Memories Project ENG 201 C: Rhetoric and Community
Option 1: Simple and Direct Choose a site of public memory near Berry College, in a nearby town, or in your hometown. Create a 6-7 minute presentation that explains what the site communicates to the public and how it helps build (or does not build) a sense of community. Analyze both the words and visual elements that shape the site's message. Option 2: Student-Friendly For this project, you'll explore a monument, memorial, museum, historic marker, or other site of public memory. Using close rhetorical analysis, you'll examine how the site tells a story, what message it sends, and how that message affects the people and communities connected to it. Present your findings in a 6-7 minute presentation using PowerPoint or Adobe Express Webpage.
Option 3: Checklist/Bullet-Point List • Select a site of public memory. • Examine its language, images, symbols, and design. • Analyze the message the site communicates to the public. • Discuss how the site creates, shapes, or challenges community identity. • Present your analysis in a 6 -7 minute presentation. • Use Adobe Express Webpage or a program of your choice to create your project.
At the core of our special issue is our belief that academic disciplines advance through robust dissoi logoi. For better and worse, AI has gained a foothold in how we engage with each other. Thus, it will be increasingly important for scholars in the field to be able to understand how AI technologies model language, thereby affect how we use language, and thereby raise new sites of research and methods for researching rhetoric. Rhetoric of/with AI: Rhetoric Society Quarterly (Volume 54, 2024) Rhetoric of/with AI
FROM PROMPT TO PRACTICE: CREATING INTERACTIVE LEARNING EXPERIENCES WITH AI Eunie Shin Assistant Professor of Management Berry College CDI August 2026
Opening Question : Mentimeter What do you wish your students had more opportunities to practice or experience, but that’s hard to do regularly in class? Go to www.menti.com Enter the code: 5872 9148 Or use QR code
What if AI helped students DO something, rather than simply produce something? Not: “Ask AI receive answer.” → Instead: 1 Choose Students decide how to respond. 2 Interact The AI responds in context. 3 Revise Students try another strategy. 4 Reflect They explain what worked and why.
How I Use AI for Interactive Learning Experiences Role-plays Teaching Assistant Prompt Generation Compare AI Responses Gen AI Syllabus Quest Interview Simulator Learning Games Vibe Codin g Live Student Responses AI Thematic Summaries Interactiv e Pollin g Interactive Avatars Voice & Dubbing Voice & Audio AI
Why Do We Like Games?  We know what we’re trying to accomplish  We see right away what worked  We get to make choices  We can see progress  We can try again Have you ever wished you could create a game or app? I don’t know how to code at all!
What is Vibe Coding?  Describe what you want in everyday language, and AI helps build the app or website for you.
What is Vibe Coding? “Create an interactive syllabus game where students answer questions, move through different sections, and receive a completion code at the end.” Idea What should students do? Prompt Describe the activity Prototype AI drafts the app Test Find what breaks Revise Tighten rules & wording Provide GenAI with your course materials and goals, then ask it to create a detailed build prompt you can refine before using it in an app-building platform.
Vibe Coding Example 1: Syllabus Quest https://ethics-quest-hub.base44.app
Vibe Coding Example 1: Syllabus Quest https://ethics-quest-hub.base44.app
Vibe Coding Example 2: Win As Much As You Can https://win-strategy-lab.base44.app
Vibe Coding Example 3: Interview Simulator https://ai-prep-pro.base44.app
Vibe Coding Application If you could build one simple app, game, or interactive activity for your students, what would you create?  Simulation: practice a real-world scenario or decision  Interactive case: students choose what to do next and see consequences  Review game: course concepts, exam prep, vocabulary  Quest or scavenger hunt: syllabus, orientation, course content  Decision tree: work through a problem step by step  Role-play practice: conversations, interviews, negotiation  Interactive timeline/map: history, processes, events, locations  Self-assessment tool: students answer questions and receive customized feedback Think about something you already teach that could become more interactive!
AI as a Practice Partner Students may understand what they should do…but can they actually say it?  Difficult conversations  Ethical concerns  Negotiation  Giving and receiving feedback  Conflict  Speaking up to authority Negotiation responding under pressure Public speaking trying an opening or Q&A Interviews answering difficult questions Teacher education classroom scenario practice Leadership feedback and conflict conversations Ethics speaking up when values conflict
Gen AI Example 1: AI as a Role-Play Partner Create a custom AI agent that:  takes on a specific character or role  responds dynamically to what the student says  creates realistic pushback or follow-up questions  provides feedback after the interaction
Gen AI Example 1: AI as a Role-Play Partner Academic Integrity Scenario: You believe something happening in an academic setting raises an integrity concern. You need to speak up to someone who may disagree with you or have an incentive to continue. Student goal: Practice how to voice the concern effectively - not simply identify what is ethically wrong.
Gen AI Example 1: AI as a Role-Play Partner GVV COMPLETION RECEIPT GVV role-play complete. You successfully worked through a difficult conversation and practiced turning your values into action.  Case: Academic Integrity Agent role: Taylor Meaningful role-play completed: Yes Student communicated a values-based concern: Yes Student responded to resistance: Yes Student proposed a request, alternative, or next step: Yes  A strength you demonstrated: You consistently acknowledged Taylor's pressures and perspective while still clearly explaining why you were uncomfortable using or sharing the prohibited manual. That combination of empathy and firmness made your message more persuasive.  How your response became stronger: You moved beyond simply refusing the file to proposing practical alternatives—a study group, encouraging Taylor not to share the manual, and suggesting a conversation with the professor only if the problem continued.  One idea to carry forward: Continue pairing your ethical concerns with realistic alternatives. People are often more willing to change when they have another workable option instead of just hearing "don't do it."  Completion code: GVV-AI-4837
VR Roleplay Simulation
Gen AI Example 2: Can AI Make Ethical Decisions? When AI does the analysis, who makes the decision? What students do:  Receive the same ethical dilemma  Ask different GenAI tools to analyze it  Compare the responses in a shared Google Doc  Identify differences in values, assumptions, and recommendations  Write a short reflection on what they think about the AI’s response
Gen AI Example 2: Can AI Make Ethical Decisions? Stealing Medicine  Prompt students copy: A man’s father is dying from a rare disease. A pharmacist has developed a drug that could save him, but the price is extremely high. The man cannot afford it, and the pharmacist refuses to lower the price. The man considers stealing the drug. Is stealing morally justified in this case? Why or why not? Which ethical theory best supports your reasoning? Same dilemma. Different AI. Different user. Different answer?
Gen AI Example 2: Can AI Make Ethical Decisions? Student AI Model AI Decision Ethical Reasoning Student Reaction Student A Perplexity Stealing is justified Considered utilitarianism, Kantian ethics, virtue ethics, and multiple perspectives; ultimately prioritized saving a life over property rights “I liked that it approached it from an academic point of view and seemed very unemotional.” Student B Copilot Stealing is justified Primarily utilitarian reasoning, while also presenting other ethical frameworks “It wasn’t very direct. I had to tell it to make one decision instead of giving me multiple frameworks.” Student C ChatGPT Stealing is morally justified Utilitarianism: saving a life outweighs the harm caused by taking someone else’s property “I was a little surprised at how willing it was to break the law.” Student D Gemini Stealing is justified Natural rights / right to life, with utilitarian reasoning “This was the answer I expected.” Student E GenAI Stealing is not justified Kantian / duty-based reasoning: theft violates a moral duty and property rights, even when the intended outcome is good “I can understand the reasoning, but I’m not sure I agree that following the rule should outweigh saving a life.”
AI Beyond Text: Voice, Video & Avatars 1. Gen AI: Create the script “Write a short introduction for Eunie Shin to introduce herself to her Organizational Creativity class.” 2. ElevenLabs: Generate the voice Paste the script generate AI → speech/audio 3. Adobe Character Animator: Bring it to life Choose an avatar add the audio → → gestures/animation export video →
Where could you take this next? Think back to the learning experience you wished your students could have more often. Could AI help you create:  more opportunities to practice?  something more interactive?  faster or more individualized feedback?  new ways for students to participate?  a space to experiment and try again? Start small. Experiment. And have fun with it!
Questions?
C o u r s e D e v e l o p m e n t I n s ti t u t e : A u g u s t 2 0 2 6 Building Textbooks with AI Michael Papazian • Department of Religion and Philosophy • Berry College
TH E P ROB L E M Good course materials are hard to find 1 Off-the-shelf texts don't fit Published textbooks rarely match your syllabus, your examples, or your slide sequence. Plus, they’re really expensive. 2 Producing your own text takes time You can have a lot of content but putting it together in a format that is professional is daunting. 3 Content needs to be organized Years of lecture notes and slides hold real content, but they’re compressed and built for presentation, not for independent student reading. Building Better Textbooks with AI | Michael Papazian, Berry College 2
TH E ME TH O D A repeatable, four-step workflow 01 SOURCE Start from material you already trust: lecture slides, handouts, past exam and review-question documents. ➜ 02 UPLOAD Put all the material together by chapter and ask to have it compiled in a coherent and clear format that 18 - 22 year old college students can relate to. ➜ 03 DRAFT Apply a fixed house style: consistent colors, box types, and section structure across every chapter. ➜ 04 VERIFY Check carefully for any errors or content that doesn’t quite match your class presentations. Building Better Textbooks with AI | Michael Papazian, Berry College 3
STEP 1 & 2 — SO U RC E & EXTR AC T Every fact in the chapter traces back to a source you already used Nothing in the chapter is drawn from the AI's general knowledge of logic. Every fallacy, case, and example came from material already used in class. 5 lecture slide decks (fallacies, ad hominem, cognitive biases, fallacy bingo review) A comprehensive fallacy term list (course glossary document) A document of real student review questions from a prior exam A worked data breakdown (Simpson's paradox) built for the course Source → Chapter 5 slide decks + 3 supporting documents becomes 1 coherent, 20-page chapter with a full pedagogical apparatus: definitions, examples, exercises, and answer keys Building Better Textbooks with AI | Michael Papazian, Berry College 4
STEP 3 — DR AF T A fixed house style does the heavy lifting The same color-coded box system runs through every chapter, in every course — so independently-built chapters read as one book. Definition Consistent icon, color, and placement in every chapter Example Consistent icon, color, and placement in every chapter Key Insight Consistent icon, color, and placement in every chapter Caution Consistent icon, color, and placement in every chapter Side Note Consistent icon, color, and placement in every chapter Common Confusion Consistent icon, color, and placement in every chapter Building Better Textbooks with AI | Michael Papazian, Berry College 5
CAS E STU DY Chapter 3: Fallacies and Cognitive Biases PHI 152: Critical Thinking (Foundations 4a) Two topics, one chapter Informal fallacies of relevance and presumption — ad hominem, appeals to emotion, begging the question, false dichotomy, and more Cognitive biases from behavioral economics — Kahneman & Tversky: anchoring, loss aversion, the endowment effect, sunk cost I request a Word document so I can edit it. I later upload it on Canvas as a PDF. Building Better Textbooks with AI | Michael Papazian, Berry College 7
R ESU LTS What the finished chapter actually contains 20 pages 17 numbered sections 25 definition boxes 11 worked examples 6 student-confusion boxes 12 exercise sets, each with a full answer key Building Better Textbooks with AI | Michael Papazian, Berry College 8
SH OW, D ON ' T TE L L Sample pages from the finished chapter Title page Simpson's paradox worked example Building Better Textbooks with AI | Michael Papazian, Berry College 9 Ad hominem comparison table
TH E D I STI N C TI V E STEP It answers the actual questions your students asked A document of real student review questions — submitted before an exam — is fed directly into the drafting process, so the chapter addresses genuine points of confusion, not generic ones. “Isn't the sunk cost fallacy just human behavior?” Chapter has a dedicated box explaining the normative vs. descriptive distinction — directly responding to the objection. “Can you go over the difference between ‘raises’ and ‘begs’ the question again?” Chapter includes a section distinguishing the colloquial and technical senses of the phrase. “What's the difference between genetic fallacy and guilt by association?” A dedicated ‘Common Confusion’ box gives a direct, side-by-side answer. Building Better Textbooks with AI | Michael Papazian, Berry College 6
H ONEST ASS ESS MEN T What AI is genuinely good at here Consistent formatting Applying one visual and structural template across many chapters without manual reformatting. Fast first-draft exercises Generating full exercise sets and gradeable answer keys — historically one of the slowest parts of writing a textbook. (The answer key for the formal logic chapter was 90% accurate. A very motivated and bright student in the class discovered the errors.) Synthesizing scattered sources Merging multiple slide decks from different weeks into one coherent narrative. Incorporating specific feedback Folding a review-question document directly into the content, not just producing generic material. Building Better Textbooks with AI | Michael Papazian, Berry College 11
H ONEST ASS ESS MEN T What still requires the instructor 1 Subject-matter accuracy — every chapter needs a careful faculty read-through before it reaches students. 2 Pedagogical judgment — deciding what's worth emphasizing and how much nuance a given course actually needs. 3 Curating source material — output quality tracks the quality and completeness of what's fed in. 4 Copyright and institutional review — images, quotations, and third-party examples need the same scrutiny as in any traditionally-authored text. Building Better Textbooks with AI | Michael Papazian, Berry College 12
A NOTE O N PR AC TI C E Academic integrity, intellectual property, and confidentiality I let students know from the beginning that the text was produced with Claude. All the documents I upload are my own. I don’t use any other authors’ textbooks or exercises taken from another book. No students are identified nor is any student-written material (e.g., tests, papers) uploaded. The only exceptions are the student questions (which are anonymous). The text is free and available to anyone who wants it. I have no interest in receiving compensation or making a profit. Building Better Textbooks with AI | Michael Papazian, Berry College 13
Questions & Discussion Tooling • Cost • Institutional policy • Academic integrity Building Better Textbooks with AI | Michael Papazian, Berry College 17
Gen AI Research Aggregators The next phase of research? Phil Schaller: Reference Services Librarian
Librarians, YAY! Who am I and what can I do for you? • Reference Services Librarian • Guide your students on Information Literacy, where to find research, and properly cite sources • Create and provide research instruction sessions for your class • Research Guide for Faculty: https://libguides.berry.edu/genaibasicsforfa culty • Pschaller@berry.edu How does AI fit into research instruction? • Brainstorming topics/key terms • Creating outlines to organize thoughts and arguments • Critically thinking about outputs: o Bias o Hallucinations o Ethical considerations • Coming Soon: Research Aggregators!
What are Gen AI Research Aggregators? • Generative AI tools designed to help researchers with literature and systematic reviews • How: Using semantic similarities to take keywords and find articles from over 2M+ Open Access articles that match desired output. • What else: o Give abstracts and summaries of located articles o Citation chasing o Zotero Integration o Unique functionality depending on tool • Examples: Research Rabbit, Elicit, Consensus,
The Big Three • Research Rabbit: https://www.youtube.com/watch?v=J1YXarr8U0A • Elicit: https://www.youtube.com/watch?v=Xj3RtBADb60&t=178s • Consensus: https://www.youtube.com/watch?v=I8VC6R7-J6M
Great, but far from perfect... 2M+ articles and yet... • Only Open Access o Misses many articles behind paywalls or in paid journals o Sometimes only citations • Not always the cream of the crop o Haven't seen hallucinated citations...yet o Have seen; non peer-reviewed articles, pre- published articles, undefended dissertations o Still need to vet/evaluate credibility of outputs Article summaries are great but... • Can miss vital context of the article • Sometimes extract incorrect key points and takeaways from article These tools do not give you the whole scholarly conversation. They are best used in conjunction with Library Databases not instead of Library Databases
Can this help in your courses? INSTRUCTION SESSIONS • Students are tech savvy, they may find these on their own. • Can be a great help, concern they are hamstringing their own Research and Critical Information Literacy skills • Librarians can help! CANVAS MODULE • https://berry.instructure.com/accounts/ 1/external_tools/36?launch_type=global _navigation&toolId=commons-36
C O U R S E D E S I G N I N S T I T U T E 2 0 2 6 : A I a t B E R R Y AI in the Classroom Writing learning outcomes and syllabus language for student AI use Jeremy Worsham – Dir. Instructional Design & Technology
Why Your Syllabus Has to say Something Silence is not a neutral policy — students will assume a rule and act on it. 01 Students are already using it Assume every class has AI users. An unstated rule becomes an inconsistent one, enforced only after something goes wrong. 02 Rules differ course to course What counts as help in a one course may count as misconduct in another. Students can't read your mind across five syllabi. 03 Integrity needs a standard A written expectation is what makes an academic integrity conversation fair, teachable, and defensible.
Student Learning Outcomes for AI Use Write outcomes about judgment, not about tools. Each one is observable and assessable. Evaluate Students will be able to… Assess the accuracy, bias, and limitations of AI- generated content against credible disciplinary sources. Apply Students will be able to… Use generative AI tools appropriately for a defined stage of the work — brainstorming, revision, or analysis. Document Students will be able to… Disclose and cite AI use accurately, describing what was generated, what was prompted, and what was revised. Reflect Students will be able to… Explain the ethical, disciplinary, and professional implications of AI use in their own field of study.
Provost’s Office Suggested AI Outcomes From the Provost's Office — five institution-level outcomes offered as a shared starting point. 1. Ethical Judgment and Integrity Students will exercise judgment about when, whether, and how to use AI across academic, LifeWorks, and professional settings, distinguishing uses that strengthen their learning, creativity, and agency from uses that compromise it. They will be able to explain their choices in light of what a given class or workplace allows, take accountability for the accuracy of submitted work, and acknowledge AI assistance when appropriate. 2. Hands-On Facility and Effective Integration Students will develop and demonstrate working facility with available AI tools by applying them to context- specific tasks and integrating them into processes that produce useful results and increased productivity. Adapt rather than adopt wholesale: pick the one or two outcomes your course can actually assess, and map each to a specific assignment.
Provost’s Outcomes, Continued Evaluation, authorship, and disciplinary practice. 3. Critical Evaluation of AI Outputs Students will critically evaluate AI-generated outputs for accuracy, bias, reliability, and provenance. They will verify results against trustworthy sources, judging whether a given output is fit for the purpose at hand. 4. Independent Authorship and Intellectual Ownership As appropriate, students will use AI to support their own thinking and voice. By actively refining, adapting, or rejecting AI outputs, students will remain the authors and fully responsible for what they produce. 5. Professional Application and Societal Impact Students will examine how AI is used within the methods and standards of their own fields. They will anticipate how AI may be used responsibly in their future careers, exercising discernment about the impact AI has on the people, organizations, and communities it touches, including the labor it draws on and the environmental resources it consumes.
Pick a Tier, Then say it Clearly Most courses fit one of three approaches. Name the tier for the course — or for each assignment. Tier 1 — Not permitted Work must be entirely the student's own. Best when the outcome is the thinking itself: diagnostic writing, language acquisition, foundational problem sets. Tier 2 — Permitted with disclosure Allowed for defined stages, with a citation or use statement. The common middle ground. Specify which stages qualify — outlining, feedback, code debugging — and what disclosure looks like. Tier 3 — Expected AI use is part of the assignment and is itself assessed. Use when disciplinary fluency with AI is the point: prompt design, output critique, professional workflow simulation.
Crosswalk: Outcomes to Syllabus Tiers Which policy posture each Provost outcome needs in order to be teachable and assessable. Provost outcome Fits tier What the assignment asks for 1. Ethical Judgment and Integrity Tiers 1–3 A short use statement, plus a rationale for the choice the student made. 2. Hands-On Facility and Effective Integration Tiers 2–3 A tool applied to a real course task, with the process visible, not just the result. 3. Critical Evaluation of AI Outputs Tiers 2–3 Source-checking an AI output and documenting what was wrong or unsupported. 4. Independent Authorship and Intellectual Ownership Tiers 1–2 Draft-to-final evidence showing what the student kept, changed, or rejected. 5. Professional Application and Societal Impact Tier 3 A field-specific analysis of responsible use, including labor and environmental cost. Tier 1 courses can still carry outcomes 1 and 4 — the judgment is about restraint and authorship, not tool use.
Sample syllabus language you can adapt Illustrative drafts — adjust to your discipline and your department's policy. If AI is not permitted “The use of Generative AI is prohibited in this course unless otherwise stated: Because of the learning goals and teaching approach in this course, use use of AI is not allowed. Students should not use AI tools to write of any portion of an assignment for them. All submitted work should be generated by the students themselves, working individually or in groups, as assigned.” If AI is permitted with disclosure “Responsible use of generative AI tools is permitted in this course for students. To adhere to our scholarly values, students must cite any AI-generated material that informed their work (this includes in-text citations and/or use of quotations, and in your reference list). Using an AI tool to generate content without proper attribution qualifies as academic dishonesty. Students maintain responsibility as authors of any material they submit for course assignments.” If AI use is expected “You can use generative AI tools to help brainstorm assignments or projects or to revise existing work you have written. When you submit your assignment, I expect you to clearly attribute what text was generated by the AI tool (e.g., AI- generated text appears in a different colored font, quoted directly in the text, or use an in-text parenthetical citation). Students maintain responsibility as authors of any material they submit for course assignments.”
Before Your Next Syllabus Goes Out 1 Choose your tier Decide the default posture for the course, then flag any assignment that departs from it. 2 Add one AI outcome Attach a single AI-literacy outcome to the course and map it to one assignment you already grade. 3 Write the statement Adapt the sample language, name the consequence, and put it near your integrity policy. 4 Say it out loud in week one Walk through the policy in class. Most violations are misunderstandings, not intent. Questions and syllabus review: Instructional Design & Technology
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