Post by Dr. Jess Kahlow, Instructional Designer in the Center for Distance Education & Adjunct Associate Professor in the College of Education (Faculty Profile)
Dr. Jess Kahlow debuts our new AI Essentials for Instructors Canvas course in this blog post.
TLDR
Curious about using AI in your teaching? Our new AI Essentials for Instructors is your one-stop guide to the effective, ethical, and practical use of AI at UTA. The course takes about two hours, and you’ll get an “AI Essentials” badge!
Self-enroll in the course now!
Key Ideas
My background is primarily in writing and communication, so the impact of technologies like Copilot and ChatGPT has interested me from the start. Because of that, it shouldn’t be surprising that I started using these technologies in every way I could think of and allowed AI in my courses.
I often use AI tools like Copilot, Notebook LM, and ChatGPT. As I started experimenting with AI, I first focused on understanding what these tools are really good at (we knew they were bad at a lot of things, but finding things they were consistently good at was a bit more challenging). Soon, I realized that AI is good at restructuring information; for example, it was good at turning a bunch of information into a nice, short overview or general summary. This was great for writing chapter or article summaries and even for writing module overviews. Then, I applied this same idea to using AI to make rubrics. Since a rubric is essentially a differently formatted version of the assignment, AI is a very helpful tool for doing this (and you can learn more about it in my chapter on Using AI for Rubrics!). From there, I became more curious about how AI could support instructors, and in my chapter on Instructors’ Use of AI in Teaching, I talk more about how AI can be used to develop assignments, discussions, and quizzes. While writing this, I came across the idea of AI-proof assignments; I realized that AI-proofing basically just meant creating meaningful and authentic assessments. I had already been doing this, but it did give me a more persuasive argument for getting the faculty I worked with in my role as an instructional designer to include more meaningful and authentic assessments in their courses.
Then, once I figured out how I was using AI, I started addressing AI in my courses and started explicitly telling students that they could use it. But, allowing AI in my courses wasn’t as simple as just saying, “Go ahead!” In my courses, I used one of the syllabus statements provided by UTA that says students can use AI as long as they cite that they used it. I included it in the syllabus and on the “Academic Integrity” page in my courses. The first semester I used this statement, I noticed students immediately started disclosing that they used ChatGPT for some of their assignments. That’s fine—I expected as much when I decided to allow it. However, simply citing that they used ChatGPT was not at all helpful to me as an instructor. First, most students just included a vague statement that said something like “ChatGPT was used to complete this assignment,” while others provided an APA citation that resembled something like “Copilot. (2025, April 25). Conversation.” Neither of those gave me enough information to know how students actually used the AI tool, nor did they give me any kind of idea of how much thinking happened. Did they use it for brainstorming general ideas? Did ChatGPT write the whole assignment? I honestly had no idea.
The following semester, I adjusted my approach. I kept the same syllabus statement, but I added information about how to cite AI, and I asked students to include AI tools in their in-text citations and in their reference list. I also asked them to include links to the conversation they had with ChatGPT and the prompt they entered. You’ll never guess what happened. (Seriously, try.) Students completely stopped citing ChatGPT. I’m naive, but not so much so that I believed none of my students used ChatGPT or other AI tools. I could still see evidence of it in their writing (e.g., random bolded words throughout paragraphs, the overuse of words like “delve” and “journey”, etc.). So, by requiring more strict directions for citing AI use, I either discouraged its use altogether or simply dissuaded them from disclosing their use of AI. Neither of those options was great.
Feeling defeated and like the Cybermen returned yet again, I started looking into how other instructors and universities were navigating AI in courses. That’s when I stumbled across the idea of AI use statements. Up until this point, I was missing a way for students to tell me how they were engaging with AI on their assignments. At a minimum, they explain what AI was used to create the materials and how it was used, which already goes beyond what a basic citation asks. I then took it a step further and asked students to describe how the way they used the tool aligns with the honor code, specific information about the prompt, including the prompt itself and the number of iterations, a link to the prompt (or printout), and even a reflection about how the AI tool contributed to the quality, clarity, or depth of their submission. (I now call them “AI use supplements” because they ended up becoming a bit more than a “statement”.) Somehow, seemingly doubling down on AI use directions made students start disclosing that they’re using AI tools again, and they’re being more specific about how they use them. This shows that having clear and specific directions helps students understand exactly what my expectations are and how to meet them when using AI; it’s about helping make sure students have the resources they need to use AI thoughtfully, not out of convenience.
While AI use statements (or supplements) were helpful, it became clear that students probably aren’t super aware of what they are or why they should include them. Since I was making directions anyway, I ended up making the AI Essentials for Students Guide that provides an overview of how students can effectively and ethically use generative AI in academic work. It introduces the basics of AI technology, ethical considerations, and privacy concerns when using AI tools. It talks students through university policies on AI use, practical applications for academic tasks, and how to properly cite AI-generated content.
However, once the student-facing guide was done, I couldn’t help but feel like something was missing. The student guide was great for students, but it left out all of this other stuff I did as the instructor to try to navigate this new AI landscape. This led to the final thing I came across about how to navigate AI in courses: a guide just for instructors. With the support of the Center for Distance Education and the Center for Research on Teaching and Learning Excellence, the AI Essentials for Instructors course was then born. The course takes all of what I learned as I tried to figure out how to let students use AI in my courses while also making sure they’re still learning and thinking for themselves, combined with common concerns and questions I get from faculty that I work with as an instructional designer.
AI Essentials for Instructors is a quick, practical course to help you make informed decisions about using AI in your courses (so you don’t have to go through all of these iterations like I did!). The purpose of this course isn’t to talk you into (or out of) using AI—it’s about recognizing that AI is a powerful tool that we need to be aware of. The AI Essentials course does just that; it’s there to help you make informed, thoughtful decisions about what works best for you, your course, and your students. Whether you end up fully integrating AI or barely touching it, you’ll walk away with strategies, examples, and guidance to help you navigate this new terrain with confidence.
References
Center for Distance Education, & Center for Research on Teaching and Learning. (2025). AI Essentials for Instructors. University of Texas at Arlington. CC BY-NC-ND. https://uta.instructure.com/enroll/J4BXH8
Kahlow, J. (2025). Artificial Intelligence (AI) Essentials for Students. [H5P]. University of Texas at Arlington, Center for Distance Education. CC BY-NC-ND. https://utarlington.h5p.com/content/1292539455670252558
Kahlow, J. (2024). The Alchemy of Assessment and Evaluation: From Lead to Gold. Mavs Open Press. uta.pressbooks.pub/thealchemy
Magruder, A. M. L. Cavallo, & A. M. Clark (eds.) (2025). AI-Powered Education: Innovative Teaching Strategies to Elevate Student Learning. Mavs Open Press. https://uta.pressbooks.pub/aipowerededucation