Generative AI (GenAI) continues to disrupt higher education, offering both challenges and opportunities. IU has been developing extensive resources around teaching and working with GenAI, and this page seeks to curate some of those resources under several questions based on what you are trying to do. We have tried to provide a variety of resources—print, video, and live workshops. You may always contact the CITL if you want to talk with a consultant about specific course or assignment design questions.
Before we can think about the ways GenAI impacts our teaching, we need to understand how it works, what GenAI tools are available to us, and how we can effectively use these tools by writing effective prompts.
Unfamiliar with how GenAI works? Learn the basics in this first module of an IU Canvas course on GenAI. You will need to enroll in this Canvas course through the link below, and then you can access this and other modules.
Most of us think of Chat GPT when we think about GenAI, but there are a variety of GenAI tools available, each with different capabilities and strengths. Learn about various GenAI tools, including Microsoft Copilot and Adobe Firefly, tools that IU has vetted and licensed to provide extra security for your GenAI work. As with other non-IU-vetted technologies, instructors should be cautious when using other GenAI tools with students, and students should never be required to use an unapproved tool. Learn more aboutPrecautions about Using ChatGPT at IU.
Writing effective prompts is essential to getting useful responses from GenAI. The module and workshop below will teach you skills in “prompt engineering.”
There is currently not a comprehensive policy at IU about Generative AI. Most of what exists focuses on security and intellectual property issues, as well as the relevant pieces of the Student Code of Rights and Responsibilities. Some IUB schools— including Kelley, O’Neill, and the College of Arts and Sciences—have provided guidance to their faculty around GenAI in teaching.
IU does not currently approve of any tool to be used detecting GenAI use in student work. For a variety of reasons—data security, intellectual property, tool bias against non-native speakers, and accuracy—instructors should not use GPT Zero or other GenAI tools to check student work. Our license for Turnitin does not include their GenAI “Originality” tool, and the content-matching tool (“Similarity”) we do subscribe to only finds matches with existing texts and does not attempt to determine potential GenAI use. Recommendations for other approaches to identifying inappropriate GenAI use are found in the "Restrict Inappropriate Use” section below.
It is important to include a clear GenAI statement in your syllabus about how students may or may not use GenAI in your course. Look to any guidance provided by your school and/or refer to IUB VPFAA’s Start of Semester Memo which points to Teaching.IU's guidance on drafting strong syllabus statements.
Students do not have a specific academic integrity policy around GenAI. Instead, the IU Code of Student Rights, Responsibilities, & Conduct mentions “artificial intelligence” as once example of potentially “unauthorized external assistance.”
It is important to include a clear statement in your syllabus about how students may or may not use GenAI in your course. Try to offer a learning-based explanation of these rules—how reliance on AI in a certain activity might shortcut the learning process or hinder their ability to develop skills expected in the industry. Rules designed to benefit the student have a greater chance of buy-in. Look to any guidance provided by your school and/or refer to IUB VPFAA’s Start of Semester Memo.
Sample syllabus language for various approaches to including or prohibiting GenAI is available at Teaching.IU.
Justin Hodgson (Department of English) has developed an “ethics of practice” that goes beyond a course policy to encourage students to think critically about the ethical use of GenAI.
Learn about limits of AI detection tools and how to develop a GenAI policy for your course in the GenAI in the Classroom Canvas Modules: Module 3: Responsible Use.
While GenAI has the capacity to enhance student learning, some instructors want to limit its use on particular assignments and assessments. This can be to ensure students are practicing and developing skills rather than over-relying on GenAI, or to ensure that assessments are accurate reflections of students’ knowledge and skills. Trying to make assignments “GenAI resistant” can be tricky, particularly as the technologies continue to evolve, but these resources provide some suggestions. Many of the issues below are addressed in our How to Productively Address AI-Generated Text in Your Classroom page.
Ensure you have clear policies and assignment descriptions that describe appropriate uses of GenAI on that assignment. See the policy section above for syllabus policy guidance.
Learn to design assignments that encourage students to work independently of GenAI—approaches like building relevance, personalizing assignments, drawing on in-class cases and examples, breaking assignments into smaller and scaffolded chunks, and asking for meta- or reflective statements on their work and processes. For more, see our recommendations on how you can adjust assignments to make them more AI-resistant. Also see the GenAI in the Classroom Canvas Modules: Module 4: Designing Assignments and Assessments.
Address possible misuse of GenAI in learning-focused ways. Talking to students about such suspicions is a delicate task, where outright accusations can lead to confrontational situations rather than educational ones. For suggestions, see our video on talking to students about potential misuse of generative AI.
Students will increasingly require digital literacy skills related to GenAI in their careers, so we will need to consider ways of incorporating these skills and tools into our courses and curricula. Much of the Digital Gardener Initiative's GenAI series addresses this topic. The schedule of their upcoming events is available online, as are recordings of many of their previous sessions.
For recommendations on designing assignments and courses to incorporate GenAI, see the GenAI in the Classroom Canvas Modules: Module 4: Designing Assignments and Assessments, and Module 5: Course (Re)Design
While incorporating GenAI skills into some courses is useful, a curricular approach will provide better opportunities for student growth across classes within a major or minor. The curriculum mapping process around GenAI would include these steps:
Set programmatic goals and learning outcomes. What will graduates of your program need to be able to do with GenAI when they leave your program and enter their professions? What knowledge and skills (both technical and intellectual) will they need in future careers, and how do you know that? Have you engaged with industry leaders to find out what those skills are? Are your outcomes flexible enough to account for a rapidly-changing technology?
Identify pathways across students' careers. Consider how students should grow over the course of their time in your program, en route to those final outcomes. What skills should they demonstrate at the freshman, sophomore, junior, and senior level, and how do those develop over time? You will want to consider a developmental or scaffolded process, building more complex skills over time.
Where will these fit into your curriculum? What classes will introduce, reinforce, and assess these skills? Consider whether skills are addressed in required courses and/or if students can meet the requirements through elective courses.
The curriculum mapping process can be complex, but it is valuable for taking intentional approaches to integrating digital literacy or other skills into your curriculum. The CITL can lead your department through this process, and we are planning a GenAI Curricular Mapping workshop for early summer 2025. Contact us for details about how we can assist you.
Generative AI can be useful in our professional roles as teachers, scholars, and administrators. As its capabilities grow, it offers the potential to save us precious time in many of the tasks that fill our schedules. We offer some guidelines and suggestions below, but for a faculty-led exploration of this topic, see the Digital Gardener Institute's webinar on Generative AI in my Professional work, available as a live event on April 21, 2025, 12:45-1:45, or as a recording of the previous offering last November.
Guidelines for professional use of GenAI:
Make sure to follow IU's data security guidelines. This typically means using Microsoft Copilot with your IU login, since that accesses a secure version that can be used with University-internal data.
Double-check its work. GenAI tools still "hallucinate" (make stuff up) and get things wrong. Use the tools as assistants, but don't rely completely on their accuracy.
Think about authorship and how GenAI use changes that. Whether you are using it to help with an article, an email, an assignment, or a student recommendation letter, consider how your use of GenAI changes authorship and the relationships behind that act of writing.
Here are some (of many) possible uses of GenAI in your professional work:
Refine learning outcomes. Prompted well, GenAI can produce well-written, measurable learning outcomes. This can be useful when generating a course or reviewing a curriculum. When you are stuck, GenAI can help with ideas or give you feedback on outcomes you have generated.
Generate assignment or activity ideas. Stuck on ideas for an active learning activity on a topic? GenAI can help you create class activities.
Generate multipe cases, problems, or examples, so that each group in your class has a separate case or problem to work on.
Create administrative reports quickly. Given parameters, GenAI can figure out how long a budget will last under certain circumstances. Or it can help you create an annual report based on your notes and CV. Or it can summarize multiple documents quickly.
Organize meetings. If you are meeting online in Microsoft Teams, it can create and summarize a transcript of the meeting, complete with a to-do list.
Summarize open-ended comments. If you survey students with open-ended comments, GenAI can find patterns and common themes very quickly, and if prompted, provide example quotes that support those themes.
Write letters or emails. We don't recommend letting GenAI write letters of recommendation or official emails for you, but it can get you started or review your draft for conciseness or tone.
As always, the CITL can partner with your department to address concerns and opportunities around Generative AI. We can visit department meetings to talk through your questions, offer tailored departmental workshops, guide you through mapping GenAI throughout your curriclum, and showcase your successes. Contact us to explore partnership opportunities.
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