Yale instructors are considering how to redesign elements of their courses to address AI technologies and platforms. Examples across the disciplines demonstrate some of the novel ways instructors are engaging their students as this technology evolves.
AI Guidance for Teachers: broader guidance around AI for instructors
Cooke invited students to use ChatGPT to write labels for objects from the Yale University Art Gallery. He assessed students on the quality of their prompts in developing the AI-generated label and their critique of the label—demonstrating how an instructor supports students in being critical consumers of generative AI tools.
Fuentes provided his graduate students with the option in SPAN 846 Introduction to Digital Humanities II: Algorithmic Approaches to Culture to engage with ChatGPT for their final paper instead of completing a computational final project. His description included: “Option B: The ChatGPT Final Paper. This final paper may be the strangest final paper you have submitted for a grade in your whole life. You won’t be writing this one alone. You won’t be writing it with another person either, not directly in any case. You also won’t even be writing the first draft. No, AI will do that. The way this works is simple: pick a topic related to your current research. Using GPT3, or GPT4 (if it’s out already) you will have the machine write the first pass. Your job is to correct and edit the work to bring it up to your standards. You will submit the original AI draft and your final version.”
This AI-related assignment for ITAL 140: Intermediate Italian II exists within a media and technology unit. The purpose of the overall unit is for students to compare the use of mediatic information, websites, and social media across different generations worldwide and within the students’ specific age group in Italy. The assignment incorporates a tutorial ChatGPT video from YouTube and is modified with Edpuzzle. The video introduces questions for comprehension for students to respond in Italian regarding the limitations and advantages of using ChatGPT and other related topics.
This was a short, ungraded assignment for the course ENG 429: Writing Humor. The primary goal was to have students reflect on what elements of their writing could be replicated by ChatGPT and what elements were unique to a human author. Wepler was hoping a deeper understanding of the difference between what a robot could draw from a corpus of existing texts and what a human could create would nudge students away from the predictable and toward originality in their writing. Wepler shared that he is “not sure this was ultimately the outcome, though their reflections on seeing how a machine wrote a paper they’d already authored were deep and compelling—and [they] talked in class about the implications of what they figured out for the practice of writing.”
Farrell assigned his students in the course ENV 770 Western Lands & Communities Field Clinic: Research to Practice to use ChatGPT to dig deeper into the problems they want to solve in their research project for the course. In this AI-specific assignment, each student posed a question relevant to their problem statement and research question to ChatGPT and then annotated what ChatGPT produced by focusing on the ways the AI-produced write-up may be inaccurate, misleading, incomplete, and/or unethical. The students also considered how ChatGPT helped them refine their research project or generated a new way for them to see their problem.
Macdonald has encouraged his students in the course S&DS 361: Data Analysis to use ChatGPT but has cautioned them that it can have trouble with technical topics where precise language is essential, and small changes in wording can make a statement incorrect. In this question as part of an assignment about the assumptions and appropriate uses of Poisson regression, the students were asked to identify two errors in ChatGPT’s response (one of which students often make!) when it was asked about the appropriate uses of Poisson regression.
Messeri created a blanket policy on her syllabus for how students might consider engaging with ChatGPT in their assignments for the course ANTH 367: Technology and Culture. Within this framing, she asked ChatGPT to create a plagiarism statement for her syllabus and then asked students if doing so was plagiarism.
Morse created a comprehensive guide for faculty on Designing Writing Assignments in the Era of AI. Although specifically written for instructors in the Jackson School of Global Affairs, the guidance is applicable across most disciplines. If an instructor is brand new to AI and primarily uses writing-based assessments, this guide is a great place to start.
In PHYS 678: Computing for Scientific Research, a graduate-level course in Physics, Moore and his colleagues encourage students to use ChatGPT when developing code to write simple functions, correct and debug syntax, and in general, to complete their exercises in class and in the homework. In less than a year, generative AI tools of this type have become important for more quickly developing code, including by working physicists. Hence, Yale Physics faculty want students to learn and take advantage of these tools at an early stage in their graduate careers. So far, in many cases, Moore and his colleagues have found this allows students to focus on the physics ideas, problem-solving, and algorithms covered in the course while reducing the development time for their code. While students are encouraged to make use of these tools, they must treat these resources similarly to discussions with classmates or other web resources — i.e., they can consult them freely but must understand and write up their code independently and cannot directly copy/paste code from any sources, including ChatGPT.
Szefer and PhD student Sanjay Deshpande co-authored a short paper about the course EENG 201: Analyzing ChatGPT’s Aptitude in an Introductory Computer Engineering Course. They report that as a text-only tool, ChatGPT cannot handle questions with diagrams or figures, nor can it perform hands-on lab experiments. It does well on quizzes and short-answer questions but could confuse students when generating incorrect but still plausible, human-sounding answers.