Since starting teaching at the college level, I have often been pretty early to adopt various technology-based teaching and learning tools. For example, in the “early” days of Twitter, I had an account for my public speaking classes (that had one follower). However, I was not really sure exactly where to start with this newer wave of artificial intelligence tools, which is why I was interested in the initiative and the SNC digital fellows program.
I started with a comparative analytic mindset in the Fall 2025 semester, which was also my first semester teaching at SNC. I thought it might be useful for students to compare and contrast their efforts with what AI tools might generate. The general idea was to get an idea of what AI had to offer teachers, students, and professionals in communication and media studies fields. For the Spring 2026 semester, I branched out a bit more and tried to use AI tools in ways beyond just a single assignment.
While working on my syllabus and assignment prompts, I tried using an AI tool to review my draft or idea. I would ask it to specifically consider the material through the lens of a 100-level student, for example, so that I could get an idea of what might be (un)clear. I would then occasionally ask follow ups like whether an assignment could be interesting and engaging. If this was clearly in doubt, to the AI tool and/or myself, I would ask for ideas as to how to improve it to better fit a student audience. I used this strategy to help clarify some syllabus language as well. A few times I also then prompted the AI tool to do a final review through the lens of an education professional (with an Ed.D.) so that I could compare and contrast what I saw with what it provided as a student and professional educator perspective. Though I do have my doubts as to whether either interpretation was super accurate, the combined feedback was still useful in revising, particularly with assignment rubrics. In the past I have sometimes felt “trapped” by rubrics that I created, and I feel like the AI tools identified some “blind spots” that I had and hopefully helped to make some criteria there a bit more clear for students.
Thinking again of clarity for students, I also wanted to create something that could serve as a bit of a study guide but could also be referenced in class. I tried making some different infographics as vehicles for weekly content. They were nice to be able to bring up in class and then students could look at that same exact file (and even print it out perhaps) later, but I think these might have gotten a bit dense, and perhaps overly complex. I also used AI tools to help develop some exam content like application-based questions, by prompting with specific parameters. Seldom could a first draft be used, but they offered good starting points at times from which I could then focus in on a specific strategy or concept. I found it useful for generating images that could be analyzed and for code that could be used to make graphs and other visuals to test on different statistical concepts. I’m not sure if much time was actually saved though, because this typically took quite a bit of revising.
For specific assignments, I tried to have students critically think about what they sent (i.e., prompts) and received (i.e., outputs) when using AI tools. I also learned myself to think about having non-AI based alternate assignments that could get to the same general ideas and outcomes without the use of AI tools so students could have an alternate option if they did not want to use AI tools for specific assignments for ethical and/or personal reasons. I am not sure that I would ever use AI tools to this same extent in teaching again, but it was a useful learning experience and I appreciate the support of everyone involved with the initiative on campus and through the digital fellows program.
