Request Information
Ready to find out what MSU Denver can do for you? We’ve got you covered.
Navigating AI in the Classroom serves as a comprehensive guide for MSU Denver faculty navigating the impacts of artificial intelligence –particularly generative AI tools like ChatGPT– on teaching and learning. This page, which has been created in collaboration with members of the Generative AI Taskforce (GAIT), is focused on providing frameworks to assist instructors in establishing their course policies around AI usage, a requirement for all MSU Denver courses:
I support the GAIT’s recommendation that every course at MSU Denver should explicitly address the use of generative AI in the syllabus or other course information. As such, this request will need attention from virtually every instructor and department at MSU Denver.
– Dr. Marie T. Mora, Interim Provost, July 31, 2023
As generative AI continues to evolve, it becomes crucial for educators to understand these technologies’ potential impacts and benefits. This page provides essential information to help you develop, communicate, and enforce AI usage policies in your courses, ensuring that these powerful tools are used ethically and effectively to enhance educational outcomes.
This guide also serves as a starting point for vital conversations about AI policy development within your departments and across your colleges/schools. We encourage faculty to engage with colleagues, both within their own fields and from diverse disciplines, to share insights and develop cohesive strategies where appropriate. Such collaborations can help in establishing department-level or even college-level policies, reducing uncertainties, and aligning standards across different areas. While this resource aims to provide foundational knowledge and tools, the creation of shared policies remains at the discretion of individual departments and colleges/schools.
If you are seeking further assistance with broader AI strategy and policy development, Dr. Samuel Jay ([email protected]) is available to support these efforts, helping to ensure that our approach to AI in education is both ethically grounded and universally beneficial.
For guidance on integrating AI into course content, assignments, and assessment, see Teaching & Learning with AI, which provides specific examples of how faculty can leverage AI—via tools like ChatGPT and Copilot—to enhance student learning. Additionally, the MSU Denver Center for Teaching, Learning, and Design has developed several supports to assist faculty in this arena. Do not hesitate to visit the CTLD’s Ready page for more insight.
Developing Your Course Policy: Considerations to Start
Let’s hit on the basics:
- Establish a definition of generative AI. For example, “Generative AI refers to a range of emerging technologies that draw from training on large datasets to generate new content in written, visual and other forms based on user instructions” (University of Kentucky’s “UK Advance” Initiative). This definition may be expanded or revised to include information that is relevant to the course and discipline.
- Develop a clear statement on whether the use of generative AI will be permitted for coursework, and if so, how and to what degree it will be permitted.
- Outline what constitutes inappropriate use of generative AI in the course as well as the consequences for inappropriate use.
- Find a process that works for you and your students that will allow students to document or cite the use of generative AI for assignments and other course activities (if it is permitted).
- Provide rationale for the policy that is grounded in the context of the discipline/department, the learning goals of the course, the skills that will be assessed and/or ethics and academic integrity.
- Share links to resources for understanding and using generative AI ethically and effectively. (This document from Western Michigan University is a great place to start.)
- Establish a learner-centered and student-friendly tone that builds understanding and motivation for students in the course.
- Invite students to discuss any questions or concerns regarding the policy, making sure they understand the expectations when it comes to using AI in your course.
Consider both the potential benefits and risks to ensure that the use of AI aligns with the educational goals of your course.
Looking for more? Check out this slide deck from UC San Diego which includes a flowchart to support your course AI policy development process.
Evaluate how the use of AI fits within the ethical guidelines and academic standards established by your department, your college/school, and MSU Denver.
For additional resources, consider the following:
- For the Health Sciences, check out the University of Kentucky’s guidelines for using AI in clinical care.
- For Engineering and Computer Sciences, BYU has some helpful guidance to assist.
- For more general supports -including info on how to frame AI use in the Humanities and General Studies courses, Austin Community College has some great examples for their faculty.
Identify specific risks such as dependency, inaccuracy, or bias in AI outputs and think about strategies to mitigate these issues.
Carnegie Mellon University offers some “quick hits” on addressing this question depending on the nature of your policy.
Reflect on how AI can be used inclusively to address the varying needs and preferences of students, thereby enhancing personalized learning.
The University of Pittsburgh has clear opportunities for how generative AI can be used to enrich the course, no matter the learning style.
Consider establishing criteria and methods for assessing whether the integration of AI tools is positively impacting student learning and engagement.
This is a blog post from a faculty member at the University of Melbourne who presents some approaches for setting outcomes that can be met using generative AI.
Sample Policies
Guidance for Graduate-Level Course Instructors from the MSU Denver Office of Graduate Studies (OGS):
- Course instructors are expected to indicate clearly in their syllabi in which way and to what extend the use of AI in a course is permitted. They also should state that students are required to follow up with the instructor in writing if they need further clarification of the instruction, and the instructor is expected to respond to all students in the course (with redaction of the identity of the student who reached out).
Sample Syllabus Language from OGS:
- AI is not infallible, and it is the students’ task not only to reference the specific AI tool plus the date when it was employed, but students also have to make sure that they truly agree with the statements or conclusions that AI provides. The use of AI does in no way suspend students from using independent critical thinking and data verification. Bypassing proper referencing or critical evaluation of the AI-produced work will put the student at fault and will lead to point or grade reduction and/or more severe sanctions. By attending this course, students agree to an oral exam that an instructor might impose to verify the depts of knowledge that has been acquired though independent intellectual work.
As you navigate what can be an overwhelming amount of information and examples of policies, remember, you do not need to reinvent the wheel.
Here are two highly-recommended collections of policies that can help you figure out what approach works best for you, your course, and your students:
- Scribbr’s collection of University Policies on AI Writing Tools is organized and easy to navigate.
- Northern Illinois University’s Center for Innovative Teaching and Learning has an easy-to-access list of sample policies they have collected from institutions across the country.
- CourseHero put together some nice graphics to visualize your decision making and policy writing process, leveraging faculty experts to share what they are doing to help navigate our AI-influenced pedagogy.