Shannon McKeen

Shannon McKeen

Professor of the Practice
Executive Director, Center for Analytics Impact
School of Business

Courses: Business Analytics Practicum


What do you teach and how have you been thinking about artificial intelligence in the context of those courses?

I am excited by the opportunity to scale up feedback, reflection, and tutoring for my course. I mostly work in an experiential learning course where students are put in teams and assigned a business problem with an external stakeholder. With 27 teams individualized feedback is challenging. Using AI I can provide exercises and examples that better meet each student’s and each team’s needs.


I used ChatGPT 3.5 to help my students learn about themselves and work better in teams. I wrote a prompt so the AI would act as a virtual Strengths Finder coach to facilitate a team-building exercise. The goal was to help students understand their individual strengths, as identified through the Strengths Finder tool, and explore how these differences could affect team effectiveness. The prompt asked each student to share their unique strengths from the assessment one at a time. The AI would report on potential advantages and cautions for that profile to be on a team. The AI asked the student to comment on the AI’s observations, including asking them which strengths surprised them the most or least to know about themselves.

Once everybody shared their strengths, the AI had the team discuss how all their strengths could be useful or challenging as a team. The AI then shared some ideas about potential benefits or problems it could see happening based on their strengths mixes. Finally, the AI prompted the team to brainstorm how they could use their strengths to benefit the team and avoid pitfalls their weaknesses might cause.

In addition to the above, my expectations for class assignments have increased. My course is about how to apply the tools students are learning, so using AI to complement what they already know to better apply the tools and techniques makes for a better experience for them and more value to the client.


The prompt provided many benefits including the students thought it was cool using this AI. They seemed to really get into the activity and think about how they can use their strengths. Also, it provided scale advantages because with 27 teams it would not have been possible for me to give each team personal attention.

The response has not been as great as I would have expected. Students seem hesitant to use the tools. I am trying to probe why. It could be the stigma of using AI, or they are uncertain what is acceptable because requirements are different for different classes, or they might be resistant to change.

If you are familiar with the 5 stages of technology adoptions, the first two stages (innovators and early adopters) experience glitches, fits and starts, and limited support but soldier through to get the benefit. Fewer of my students are in these first two stages. It appears more of my students are in the early or late majority stages of waiting for peer validation, proof of success, and frictionless use than I had expected.

Lessons Learned

This AI-assisted exercise allowed students to engage in meaningful discussions, gain self-awareness regarding their strengths, and develop strategies for effective teamwork. It also demonstrated how AI can enhance the learning experience by providing expertise and structure to complex group activities.

I would encourage more direction on specific use cases and more scaffolding for students to see the benefit.

Disciplinary Insights

I teach Analytics. AI is all about analytics and data. I heard someone say AI is analytics at speed and scale. Providing enough knowledge of how Generative AI and AI works can give students a level of comfort for using it and, I hope, enough knowledge to use it correctly and wisely.