Background and students feedback of Sample 4 (Stenard et al., 2024)
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Title: MBA Strategic Management Capstone Course
Pedagogy: integrating business simulations and GenAI for deeper learning
Background
Students compete in small teams running companies that produce sensors, making decisions about the product offerings, marketing mixes, sales channels, operational investments, and financial management.
Students were asked to use GAI tools such as ChatGPT to see if it could assist with their understanding of, and performance in, the simulation competition. Queries might relate to strategy development, decision-marking and support, communications, learning and adaptability, data anslysis and visualization, and problem solving.
Assignment
· Pre-test assignment, students were learning the simulation was a discussion post. They were prompted to ask a question of their chosen GAI system. Then in the discussion post, they shared the specific question and their evaluation of the GAI response. After each student posted, they were able to view others’ contributions.
· The post-test assignment asked more detailed. And structured questions near the end of the course about their experiences with GAI throughout the simulation.
Student’s work and feedback
| Reported ways of GAI uses by application and simulation function | · Strategic development (pre < post) · Decision marking (pre ≈ post) · Communication (pre < post) · Learning and adaptability (pre < post) · Data analysis and visualization (pre < post) · Problem solving (pre < post) | | --- | --- | | Perceived help with understanding the simulation and business uses of GAI | · Over 60% of the students surveyed considered simulation somewhat or very helpful for understanding. · Over 70% of student responses indicated that Business Use for GenAI was somewhat or very helpful for understanding. | | Insights into whether GAI helped improved simulation performance | · When asked about GAI’s help with business performance in finance, internal business processes, customers and learning, the student responses were very neutral, despite most students reports that GAI use enhanced their understanding of the simulation. | | Implications about the ethical use of GAI | · Ethical Concerns · Perceived Benefits · Fairness and Accessibility |
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Overall: Students found GAI helpful for brainstorming, problem-solving, and pattern recognition. Decision-making provided insights rather than definitive answers, thereby fostering critical thinking and creativity. However, the ethical implications of AI use should be considered, along with transparency in its application.
Feedback:
A practical application of AI in education is demonstrated by Mercer University’s Stetson-Hatcher School of Business. As noted by Stenard et al. (2024), they believe that encouraging students to “leverage AI to solve complex interdisciplinary problems in a controlled learning environment with defined end-state goals” will accelerate the pace at which they learn the new technology. Students in this MBA capstone course confirmed this value, stating that deploying AI in the classroom is “integral for real-world preparedness because it bridges the gap between classroom learning and corporate expectations.”
To support this integration, Williams (co-author of Stenard et al., 2024) proposes that universities take three key steps in addition to using AI in capstones:
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Implication:
The design of the Strategic Management capstone, which integrates a business simulation with GenAI experimentation, establishes a best practice for preparing leaders for an AI-augmented business environment. This approach moves beyond theoretical discussion by creating a controlled, risk-free sandbox where students must actively leverage tools like ChatGPT to inform strategic decisions on everything from marketing to finance. The pedagogical approach lies in the mandatory pre- and post-test assignments, which foster a critical, evaluative stance towards AI outputs rather than passive acceptance. This process effectively cultivates higher-order skills, as evidenced by student reports of significant growth in strategic development, problem-solving, and data analysis. While GenAI was seen as an enhancer of understanding rather than a direct performance booster, it precisely achieved the course’s deeper objective: to develop discerning judgment and critical thinking. By explicitly grappling with the ethical implications and accessibility of AI, the course design ensures graduates are not just technically proficient but also ethically prepared to harness GenAI as a strategic partner in leadership. Therefore, developing students’ evaluative judgement is urgently needed, as proposed by Bearman et al. (2024), a process that includes developing evaluative judgement of GenAI outputs and processes, as well as employing GenAI to assess their own evaluative judgements.
Source:
Stenard, B., Sisk, F., Brennan, L., & Williams, G. (2024). Teaching AI Skills Through Capstone Simulations. Retrieved from https://www.aacsb.edu/insights/articles/2024/06/teaching-ai-skills-through-capstone-simulations
Stenard, B., Brennan, L., & Sisk, D. F. (2024). Leveraging Artificial Intelligence (Ai) in Strategic Management: Integrating Simulations and Generative Ai for Deeper Learning in an MBA Capstone Course. Available at SSRN 5065259. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5065259
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