Talking with students about academic integrity involves demystifying - making explicit - our expectations regarding purposes and practices of integrity related to (1) What constitutes originality, (2) How students will be expected to maintain integrity in completing coursework, and (3) Where they’ll find specific information about integrity expectations within stand-alone descriptions of assignments and examinations. This page offers links to resources for each of these considerations, and opens with a few words from students:
UMN Students Share: Why is Academic Integrity Important?
Communicating Support
Learners working with Disability Resource Centers and their access consultants will work directly with faculty in setting up official accommodations that draw on uses of assistive technologies that cluster under the Generative AI umbrella. It is also common for a broad range of learners to use a variety of technology-mediated tools as accessibility supports while learning course content and completing course work.
- A web resource, “Generative AI and accessibility in education,” from the UK National Centre for AI, examines ways AI has been integral to many assistive technologies, as well as noting some key concerns and challenges for learners and teachers to take into account.
- We’ve collected a set of Accessibility Focused AI Resources into a google folder for instructors wanting to take a deeper dive into this topic.
Communicating about Originality
What constitutes originality - for you, and within your field given the range of practitioners and scholars currently communicating with peers and community, as well public and professional audiences?
- Preserving artistic integrity while creating AI art addresses questions including “How can we attain integrity when the process by which AI creates images is not clear?” webpage
- The Best Cheating Prevention: Open Discussion about Academic Integrity provides a framework and prompting questions for shaping a discussion about policy, purpose, and practice of academic integrity in a discussion among and with students.
- Our framing of Academic Honesty Pledges & Honor Codes as an Active Learning Strategy notes that the presence of codes and the signing of a single pledge is an inadequate strategy on its own, and proposes two active learning strategies to engage students in doing the effortful work of learning about integrity, speaking to link the policy to the course, and identifying difficulties as well as resources.
- We offer the combination of 6 Principles to Guide Use of Plagiarism Detection Software and Tools and Responding to Plagiarism - Fostering Integrity, to guide instructors in making decisions about how to use plagiarism detection tools to support learners and learning, and about ways of talking with students when you, they, and/or technology detect plagiarism.
Communication about Integrity Policies and Practices
How might you embed policy and practices regarding academic integrity in the syllabus narrative you compose, keeping in mind that learners new to you, your course, and your field are the primary audience for this document?
- Drawing from a selection of learning-centered syllabuses recently composed UMN faculty, and one Canvas site example addressing contract cheating, this Syllabus Statements and Course Site Language document is meant to serve as a springboard for thinking about ways to tailor integrity-related language to your own course.
- “AI in the Syllabus” provides three examples to what the writer calls “the challenge” instructors face in creating syllabus policies even as tools and access change.
- A crowdsourced “Syllabi Policies for Generative AI” spreadsheet can be overwhelming, so we suggest starting with Daniel Stanford’s “The Best AI Syllabus Policies I've Seen So Far” that distills key characteristics in 3 examples - one open use, one moderate use, and one don’t use.
- Interested in co-creating AI academic policies with your students - at course and assignment level? This slidedeck (with Note field annotations) and final google document combination offers a glimpse into that process.
Communicating about Using AI in Course Assignments
Where might you outline integrity expectations within descriptions of assignment purposes, tasks, and skills, and in setting out your expectations regarding exam preparation and completion processes?
- In Reference, Appropriation, or Plagiarism (PDF), Heather Layton (University of Rochester) combines narrative and examples to distinguish among these three field specific practices for her “Introduction to Painting” students.
- The Transparency Framework resource offers short videos, examples of revised assignments, and a template for setting out an assignment's core purpose in learning; criteria, tasks, and skills to be assessed; and main audience for that specific assignment.
- Regularly review the short resource-sharing Generative AI in Teaching and Learning document maintained by the Center for Educational Innovation, especially the “Teaching in Light of AI - Examples of Practice,” to learn more about strategies for guiding learners in critical, supportive use of GenerativeAI in assignments and assessment.s
- With an awareness of how to effectively Prepare Students for Assessments and Reduce Anxiety we can, as instructors, also work to enhance academic integrity.
- Online Assessments and e-Proctoring resource documents are curated to support faculty in building exam questions and exam settings that foster student learning.