Professors Rethink Learning with AI

When artificial intelligence (AI) entered the classroom, it didn’t just change how students work: It changed how professors teach.

At Webster University, some faculty say AI has pushed them to rethink assignments, grading and even the purpose of education itself. Instead of focusing on perfectly correct answers or uber-polished writing, the focus of learning has shifted toward process, critical thinking and personal engagement.

For Professor Kim Kleinman, who teaches Science in the News, the change has been less about rewriting his syllabus and more about reinforcing what matters most.

“I think I have doubled down on the ‘do your own project, do things that are meaningful to you,’” Kleinman said.

Before AI, writing assignments were already central to his courses. Now, he sees traditional essays as easier than ever for students to outsource. Rather than fight that directly, he has shifted his expectations.

“I’m not grading writing,” Kleinman said. “Good, clear communication helps … but what matters is that students find their own voice.”

He described AI-generated work as technically polished but lacking substance.

“AI writing is bland,” Kleinman said. “It’s not good … It’s dull, disposable information repackaged.”

That belief has shaped how he approaches teaching. Instead of emphasizing perfect structure or grammar, he now values originality and effort — even if the work is less refined.

“I’ve found myself being more sympathetic to somebody grasping toward trying to explain something that’s important to them,” Kleinman said.

Kleinman’s goal is to make learning feel less like a chore and more personal.

“I am trying to fight alienation,” Kleinman said.

In the economics department, Professor Steve Hinson has taken a different approach to adapting his teaching.

“It’s changed what I teach … and where the value is for students,” Hinson said.

In the past, many of his assignments focused on correct answers — problem sets, homework and written responses. But with AI now capable of completing much of that work, Hinson said those methods no longer reflect student learning.

“I quit evaluating students based on output,” Hinson said. “Now I want to see the struggle.”

Instead, he grades students on process — how they arrive at answers, how they interact with material and how they use AI as a tool. In some cases, he has redesigned assignments entirely.

For example, students now use AI as a guided tutor, following specific prompts and submitting transcripts of their work. The goal is not just to get the right answer, but to demonstrate engagement.

Hinson also noted that AI has made certain traditional practices, like detecting plagiarism, less practical.

“It is almost impossible to determine AI plagiarism,” Hinson said. “So I try to design assignments where students can use AI.”

Rather than banning the technology in his classroom, Hinson incorporates it into his curriculum, preparing students for a future in which AI will likely be part of most careers.

Both Kleinman and Hinson agree that AI is not simply a disruption, it is forcing education to evolve in ways that may have been overdue.

Kleinman compared it to past technological shifts, noting that each generation has faced tools that changed how people learn.

Hinson believes the long-term impact could be positive, especially if it leads to more personalized learning.

“I think, in the long run, it’s going to be a boom,” Hinson said.

Still, the transition is not without challenges. Both professors expressed concern that AI can make it easier for students to disengage or avoid difficult work.

AI isn’t replacing education at Webster, but it is forcing change. For a growing number of professors, that means paying less attention to the final answer and more to the thinking behind it.