“Keeping Learning Human While Using AI,” the fourth and final installment of the College of Graduate and Professional Studies’ webinar series, “AI Community Conversations,” featured examples of strategies for using artificial intelligence in course and lesson design.
Senior Director of Digital Teaching and Learning Sean Nufer, Psy.D., and the IO/Business Psychology Division Head Kristijan Civljak, Ph.D., led the discussion under the premise that AI is already ingrained in higher education, so the key to productive coexistence with it is to design courses that allow for its use to enhance learning rather than overly limiting or banning it.
The “AI Community Conversations” webinar series is a component of the 2025-26 Institute on AI, Pedagogy, and the Curriculum. In the beginning, this year-long initiative focused on developing policy recommendations and formal frameworks. “However,” its final report states, “through survey data and ongoing conversations with faculty and students, it became clear that the most immediate need was not additional rules, but clear, practical, and consistent guidance on how to use AI in ways that align with learning, ethics, and professional expectations.”
This guidance includes limiting the use of AI for coursework through the creation of clear guidelines, viewing AI as a learning tool, and designing coursework to make assignments resistant to the unethical use of AI. “The point is to design a class that is inclusive of AI and where the learning is clear, so that misuse decreases and engagement increases,” Dr. Civljak says.
To show how instructors can maximize the effectiveness of AI use in the classroom while encouraging and modeling ethical use by students, the presenters offered four strategies, each of which addresses the challenges and opportunities of AI-supported learning:
- Structured AI Use. This approach allows students to use AI for brainstorming, outlining, and clarifying assignments but not for drafting the work itself. One example of a class assignment employing this strategy might be having students use AI to generate ideas and to research a topic in preparation for posting on a class discussion board, but not to write the actual post.
- Processed-Based Assignments. Assignments for which students follow prescribed steps to produce a final product can be effective in discouraging overreliance on AI. For example, requiring students to submit outlines and preliminary drafts allows the instructor to track the student’s process and progress.
- AI as a Teaching Tool. Reviewing with students the ways in which AI can either benefit or undermine research clarifies the limits of fast-working applications as primary investigative tools. For example, a side-by-side comparison between a peer-reviewed paper and an AI search result on the same topic might demonstrate the need for rigor and critical analysis in a professional setting.
- AI-Resistant Design. Assignments that require students to include personal experiences and judgment prevent them from submitting AI-generating work as their own. “When assignments require thinking, reflection, and application, AI becomes a tool and not really a substitute,” Dr. Civljak says.
Lesson designs that establish guidelines for students to use AI responsibly accept the reality that AI is already a fact of life in many professional fields. Therefore, beyond creating a learning environment in which AI can be used effectively and ethically, instructors who design such lessons also prepare students for their careers. “Students are going to be using AI after they graduate,” Dr. Nufer says, “and there’s going to be an expectation that they should have a certain proficiency.”
Jay Burke, Psy.D., division chair of the Marriage and Family Therapy program at The Chicago School, agrees. “We have to prepare them for what employers are looking for and the skill set they’re going to need,” he says.
Dr. Burke was co-lead of the 2025-26 Institute on AI, Pedagogy, and the Curriculum, along with April Demers, Ph.D., chair of the Master of Biomedical Sciences and Master of Public Health programs, as well as team members Dr. Nufer; Dr. Civljak; Cody Dickson, Ph.D., director of clinical training for the Counselor Education and Supervision Department; and Kelly Torres, Ph.D., chair of the Educational Psychology and Technology Department. The efforts of these educators reflect a commitment by The Chicago School to be proactive about AI training and implementation; to provide guidance on acceptable classroom use for instructors and students alike; and to prepare students for tomorrow’s workforce. According to the institute’s final report, “The most important next steps center on deepening faculty support, increasing consistency, and beginning intentional integration of AI into teaching and learning across the college and university.”
To read more about the “AI Community Conversations” series, click here.
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