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Concordia College professors find AI solutions for educators

A group of Concordia College professors spent their summer vacations learning about artificial intelligence — and thoughtfully incorporating it into their work in innovative ways, sharing their efforts at a fall faculty workshop.

“My view of AI is: it’s the next set of tools,” said Dr. Ahmed Kamel, professor of computer science. “It’s not the human crisis that people are making it out to be, but because it’s a set of tools, we need students to know about these tools and how to use them. What can they do for them? What can they not do for them? And how can they use them successfully?”

Kamel began working in AI in 1986, when it was a relatively exclusive area of research, and long before general use by the public became common online and at schools worldwide. Many applications of AI existed before the recent boom — including some built by Kamel himself.

He reworked a course on the IT components of business, and designed two new assignments he plans to use in multiple classes this fall. In the first one, a student must choose a topic and have an AI tool produce an academic paper about it. Then the student must write a critique of that paper — and that’s what gets graded.

It’s an assignment that can be adapted to any topic and tailored to nearly any class.

“My idea is for students to realize what are the strengths and weaknesses of these AI tools,” he said. “I want students to be aware of them and know what it can do for them and what it cannot do for them.”

Another assignment Kamel gives has students choose three of the popular AI tools, ask them all the same question, compare the answers, and then discuss the results together as a class.

AI can: find patterns in music lessons

Dr. Nat Dickey, chair of the music department and professor of low brass at Concordia, had a different strategy for incorporating AI into his work. For years, he has recorded spoken notes to himself and transcribed them, using them as raw material for written work. This summer, he started experimenting with those notes, using AI to look for patterns in techniques, principles, and motivation.

“Probably the most profound outcome of that is that I’m starting to think more about doing my own trombone pedagogy texts that would be based on these principles,” he said.

AI also helped Dickey reexamine the framework of his music education lessons, in which he teaches students how to teach others.

“The class really needs to be about how a beginner learns to play the trombone more than it is about how a college student learns enough about the trombone to teach it,” Dickey explained. “It really helped me rework more of the frame of the class than the actual teaching of the class.”

AI can: solve equations and offer recommendations

Dr. Robert Gholson, assistant professor of finance, used AI to redesign a course on portfolio construction and management, in which students learn to create and effectively manage collections of financial investments. Typically, their work is based on case studies drawn from real situations, filled with ambiguities and often, lacking a clear “correct” answer.

Gholson is asking students to deploy AI in these case studies throughout the process — solving the quantitative aspects of the problem, then asking multiple AIs for recommendations on the case using multiple, varying prompts, and then asking the students to analyze the AI output, ensuring all the AI answers are sourced and actually true. The final step is to synthesize and integrate the AI answer into their own solution to the problem, creating a final recommendation the student must then defend.

“Overall, the ultimate goal of this is to hopefully develop students who can tell a good AI answer from a good-sounding AI answer,” he said.

AI can: be critiqued as an intern

Dr. Jorge Scarpin, chair of the Offutt School of Business and associate professor of accounting, reshaped assignments in one of his upper-level accounting courses to include AI.

“Our issue is always if I give them a lot of calculations, AI is quite good on doing these calculations, so it’s a challenge for us to make it work,” he said. “So I decided to do the opposite.”

Instead, he tells students to use AI to do the calculations. The idea is to think of the AI as an intern, and themselves as the manager of that intern. While interns are helpful, they aren’t typically decision-makers, so AI work also needs to be judged, critiqued, and evaluated. As such, students must explain how they used AI, what prompts they used, and what they did to improve outputs.

“They need the foundational knowledge,” Scarpin said. “They need the application knowledge to critique what AI is doing.”

AI can: be addressed as a tool for educators

Dr. Teri Langlie, chair and associate professor of education, redesigned her graduate course on meaningful assessment practices to incorporate the many questions about AI involved in education.

“I couldn’t teach meaningful assessment practices in 2026 without addressing AI,” she said. “I really like the idea of moving away from simply asking whether students used AI and instead asking them to make their use of AI visible and think about it appropriately.”

She created an AI transparency form for her students, giving them a place to disclose their AI use and reflect on that use, so they become more intentional about their choices — even if they choose not to use AI at all.

AI can: be viewed through many disciplines

Dr. Darin Ulness, professor of chemistry, spoke about his involvement in producing a series of books on machine learning in various subjects, starting with “Foundations of Machine Learning in Chemistry.”

“One of the things we noticed was that chemistry was just a wrapper on the fundamental concepts that have been around for a long time,” Ulness explained. “So we thought we could wrap other things around this.”

The project has since expanded, with a book focusing on ecology, and another on “Foundations of Machine Learning in the Humanities” in the works.

AI can: serve as a legal assistant, if carefully verified

Bree Langemo, JD, executive director of the Center for Entrepreneurial Leadership and associate professor of law and entrepreneurship, worked on developing more confidence in teaching AI in the classroom over the summer. She shared recommendations of some AI tools and professional development opportunities for educators, and explained how she’d incorporated AI into her own courses.

“In our Business Law course, students will incorporate an AI legal assistant to help them build a business, but they will be required to verify their legal sources, which has become an issue in the field of law. There’ve even been some lawsuits for malpractice against attorneys who write briefs with made-up citations in them,” she said.

Students are also encouraged to use AI to draft contracts, leverage their negotiation techniques prior to live negotiations, and use AI to look for risks and gaps in contracts.

AI can: be a source of tension, yet still useful

Heather McDougall, JD, program director and assistant professor of entrepreneurship, announced that this academic year’s High School Entrepreneurship Day will have an AI theme, noting that 250 students will head to Concordia for a day to learn how to solve problems using an entrepreneurial mindset.

“There’s this really interesting dissonance that students face. The overwhelming majority of students in this generation have a philosophic resistance to AI. But then we all see that they’re using AI all the time, and a lot of times, not really very well,” McDougall said.

In entrepreneurship, AI can help people solve problems and do research, but in order to use it well, students need to work through their tension with AI. To help with that, the upcoming Entrepreneurship Day will pair high school learners with Concordia College students to work through interdisciplinary problems. In addition, Concordia will be hosting a workshop for educators on how adaptive teaching and learning can empower students to become more AI-literate.

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