Faculty field notes for AI

“I used ChatGPT to help me design the project assignments and to provide starting code for the programming portion of the assignments. Both courses assumed that the students were competent in their programming skills. I would not have allowed students who were learning how to program use the tools.

Students were given permission, and in the case of generating Android code, encouraged to use auto-code generators to provide starter code. For the midterm exam for the Android programming course, I made it open book/Internet. One of the problems on the exam asked the students to provide the prompt(s) they used to generate portions of an Android program. Student feedback was positive, and most students had success in completing the assignments. Many students commented on my willingness to use, and let the students use, the technology that they will likely have to use once they start working.

As for the capabilities of the technology. I was impressed by the code generated and the scope of the help I could get from ChatGPT and Gemini, however…and it’s a big however. Pretty much everything auto-generated required extensive dialog w/ the tool, and more often than not, the solution did not work, and I had to troubleshoot and modify the auto-generated code.”

“I have used AI in the classroom in the graduate research methods course WR 579 Researching Book Publishing. Many students are very nervous for the oral exam where they have to defend their research to graduate. To alleviate this nervousness and help them practice, I gave them an AI prompt to help generate practice questions that they could try responding to aloud.”

“In my course, I use AI to enhance both engineering problem-solving and digital literacy. One specific assignment involves designing a steampunk-inspired robotic knee joint for “The Iron Voyager”, an automaton built to traverse harsh environments. Students use AI as a brainstorming tool to generate ideas for mechanical configurations, material selection, and aesthetic integration. After generating initial concepts, students must fact-check all AI-generated suggestions using engineering calculations, CAD simulations, and industry standards (such as AGMA for gears or ASME for welds). This process teaches them to critically evaluate AI outputs, distinguishing between creative inspiration and technically feasible solutions. Additionally, students document where AI provided useful insights and where it failed, fostering discussions on AI’s limitations in engineering design. By the end of the assignment, students not only refine their technical skills but also develop a nuanced understanding of how AI can aid—but not replace—rigorous engineering analysis.”

“Students arrive in WR 466/566 Digital Skills presenting a huge range of experience with HTML and CSS. Some have never looked at source code. Others have passing familiarity; a few have built websites for years. The assignment is to build a webpoem using HTML and CSS (and JavaScript, for those with pre-existing expertise). The challenge: each student must create learning goals that push them beyond their existing level, including a “stretch” learning goal. Students reflect on how they pursue those goals in a structured learning reflection they submit with the webpoem. GenAI is a tool that students triangulate with traditional resources such as W3Schools, sample exemplary webpoems that we study and annotate, and code snippets found on fora such as StackOverflow and GitHub. Students find GenAI performs variably. Sometimes its suggestions work well. But, especially for the least experienced learners, GenAI doesn’t provide the conceptual framework with the same coherence as class discussion or tutorials on LinkedIn Learning. Students identify workshops of their webpoem-in-progress as a valuable learning tool. Workshops are dynamic, improvisational discussions of how other students approach aesthetic goals and problem solving. Workshops build camaraderie. They are both fun and efficient. This affective reinforcement supports the intellectual and experiential learning.”

“Rather than rely solely on the textbook/course materials, I used ChatGPT to help scaffold the input phase of an assignment. Specifically, students read a chapter that included some content about Moore’s Law. The textbook chapter did not cover the topic very cohesively, and so on a quiz question about this topic, I instructed students to ask ChatGPT about it in addition to reading the chapter. Students then shared the output of that conversation.”

“BA 336U is a minor course for the School of Business that covers (among many other things) data analytics and spreadsheet management. A variety of majors enroll in the course, and students can vary in data literacy. Within the course, there is a list of critical terms that students need to be aware of by the end of the term. To assess their knowledge of the critical term, students can pick a term for the week and then use a Generative AI tool to define it. Then, students are asked to compare and contrast the answer against the textbook and explain any similarities or differences. I also require them to cite their sources using APA. Many students responded that they appreciated the exposure to Generative AI and that I allowed it to be used within my classroom.”