"AI literacy isn't just about using tools. It's about judgment, reflection, and decision-making in context."
– Dr Andrew Woon, Queen Mary University of London
Business educators face a familiar challenge: students use ChatGPT for assignments, but can they apply AI critically in professional contexts? At Queen Mary University of London, Dr. Andrew Woon tackled this by integrating AI tools into business simulations.
His 290 students used Edumundo's PhoneVentures platform while learning to collaborate with AI tools like ChatGPT and Copilot.
Students ran virtual mobile phone companies in teams of five, making weekly strategic decisions about pricing, market expansion, and supply chains. AI tools were available throughout, but students had to justify every AI-assisted choice.
The competitive element created authentic pressure. Teams could use AI to analyze market data, but poor decisions led to falling behind competitors. This immediate feedback taught students when AI helped and when it misled them.
Dr. Woon used three key design elements:
Framework-Based Analysis: Students applied business frameworks (PESTLE, Porter's Five Forces) to validate AI suggestions rather than accepting them blindly.
Scaffolded Learning: Starting with low-stakes tasks like logo creation, then progressing to complex strategic decisions as students became comfortable with the tools.
Weekly Reflection: After each simulation round, students examined their decision-making process and AI usage through structured questions.
Students developed what Dr. Woon calls "human skills": communication, teamwork, and critical thinking through group collaboration. They also gained technical competencies in prompt writing and data analysis.
According to Dr. Woon, one student noted, "Using AI to analyze the potential of different markets stood out to me, such as comparing market growth rates, competitive intensity, and customer demand."
Ready to implement this approach?
Dr. Woon offers four key recommendations:
Provide comprehensive support: Students enter with different AI literacy levels. Create inclusive environments with step-by-step guides and accessible tools.
Master the platforms: Students will ask detailed questions. Faculty needs hands-on experience with both simulation platforms and AI tools.
Connect theory to practice: Help students link simulation decisions to business concepts. Without this connection, simulations become "number-plugging games."
Emphasize reflection: Both simulations and AI use require structured reflection to maximize learning outcomes.
The approach achieved over 60% in-class attendance and improved module evaluation scores.
Employers increasingly expect AI competency. One student reported that her job assessment center specifically asked how she would use AI to increase productivity. Students without meaningful AI experience struggled to provide relevant examples.
Queen Mary's model shows how institutions can prepare graduates for this reality. By combining experiential learning with AI integration, students develop critical evaluation skills that employers value while gaining confidence in professional AI use.
Discuss implementing this at your institution: