Pitt Faculty Integrate AI Tools for Grading, Lecture Notes, and Research

University of Pittsburgh faculty members are integrating artificial intelligence tools into their daily academic duties, a trend that has gained momentum over the past year. The adoption varies by department, but common uses include generating exam problems, drafting lecture notes, and organizing research materials. This shift comes as many professors seek to manage large class sizes and complex curricula with limited time.

Anne Yust, a teaching associate professor of mathematics, employs AI to create variations of calculus problems for her students. She teaches approximately 150 students and previously found it difficult to provide detailed feedback on every exam. This year, she used an AI tool to generate short written responses for each part of her students' exams. She reported that students responded positively to the additional feedback, with many attending office hours more frequently to discuss their errors. Yust noted that she spends roughly 40 hours grading a single midterm and hopes to use AI to reduce that time, allowing her to spend more time with students.

Yust observed a marked improvement in AI capabilities for mathematical tasks compared to the previous year. She stated that last year the tools made frequent errors even on standard calculus problems, whereas this year mistakes are rare. She also used the technology to rewrite her course policies, aiming for clarity without overwhelming detail. She described the process as finding a balance where all policy points are covered in a concise format.

Maggie Jones, a teaching professor of English and a contributing writer for The New York Times Magazine, uses AI for high-level brainstorming and locating primary source material. However, she expressed hesitation about using the technology for writing. Jones described the idea of using AI for journalism or personal essays as horrifying, stating that the writing must remain her own. She noted that while AI sources can be unreliable, the tool is useful for the initial stages of her research process.

Weifeng Xu, an assistant professor of neuroscience, generates lecture notes for her students using AI based on her slides and assigned readings. She informs her students that the notes are AI-written and fact-checks the content before distribution. Xu said the process saves her time compared to writing the notes manually. She believes the AI maintains scientific accuracy while providing students with an additional resource for review.

Ross Harrison, an adjunct associate professor of political science, uses AI sparingly to create charts and graphics for his lecture slides. He does not use it to structure his courses, which he has taught for several years. However, he finds the tool helpful for reframing his research articles for broader audiences. He described the experience as similar to having a colleague offer suggestions on organization and structure. He suggested that early-career faculty might benefit more substantially from AI when developing new course materials.

Nick Canada, a graduate student in the English department, observes that faculty often use AI to handle what he calls unnecessary busy work. These tasks include organizing information, finding sources, and skimming large PDF documents. Canada noted that a stigma exists in academia, where some view AI use as a sign of laziness. He said the rapid development of the technology makes it difficult to define the line between appropriate usage and overreliance.

Canada believes that AI can help professors transfer their teaching and ideas more effectively. He cautioned, however, that the tool should not become a crutch for poor teaching. He said the conversation about ethical AI use in education will evolve as the capabilities of the technology become clearer.