AI Tools for Teaching and Learning

MBA 231: Managing in High Performance Work Organizations

leadership, experiential learning, graduate business education

Reflection on Instructional Change:

I used Copilot to generate descriptions of MBA students' leadership styles during a virtual leadership simulation. The analysis generated by Copilot discussed and helped associate different leadership styles demonstrated by 41 students in 7 teams and associate with the goals that they achieved and the challenges that they solved. Copilot efficiently and comprehensively analyzed and reduced multiple opinions, experiences and descriptions of leadership styles into a manageable set of experiential leadership lessons for the MBA students and for me as the instructor.

One practice that I had implemented was an AI use policy in both undergraduate and graduate courses. The undergraduate course has weekly discussion posts and the MBA course has a written case study assignment. A practice that I implemented was prompt engineering for analyzing the leadership moments during a virtual simulation in the MBA class. Essentially, students leadership demonstrated in the virtual simulation were subjected to Copilot's analysis using frequency counts, word clouds and converted into graphs and data displays. This was done so that students could associate leadership moments with high performing teams that achieved goals and solved challenges that were built into the simulation.

Students were curious but since the analysis using Copilot was anonymized, it lacked a personal connection for them. There weren't words that were expressed or exclaimed, however, Copilots analysis helped many of them to share their own leadership lessons with the rest of the class. Copilot triggered an enriched discussion.

This FLC helped identify the AI resources such Illuminarty, ZeroGPT and the AI user policy.

AI Tools for Teaching & Learning Workshop from the Chancellor's Office course Course Activities:

- Define AI in Simpler Terms: a dynamic variable that can serve as a discussion starter for the professor and students.
- AI Generated Content: Limitless, from neutrality of arbitrators and leadership styles.
- AI Detection: This is a mixed bag where detection of AI generated text have given different outputs.
- AI Resources: CoPilot, ChatGPT, MS Designer
- AI Policy Development: AI-use policy that is now included in my undergraduate and graduate syllabus (including discussion boards and drop boxes).

CTL "Observe and Analyze" synchronous Zoom session with your colleagues

One takeaway, from Bridget and Leah was to utilize Copilot to dialog leadership acts that did not work, including unethical leadership.

**Evidence of Instructional Change**
Example 1	Example 2	Example 3

Practice and Reflect Teaching and Learning with AI:

I have started exploring the use of artificial intelligence in simulations. The experiential moments, the simulation data after completing a simulation can be subject to AI just as I was able to do with neutrality of students role-playing as arbitrators in an undergraduate course and the leadership moments of graduate students during a virtual simulation. The AI generated insights are useful to trigger discussion and link to course concepts and students own real-world experiences especially the workplace.

Course Syllabus (upload your course syllabus here)

Course Syllabus and Schedule: MBA-231-Boniface-Michael-syllabus-250122 CTL.pdf

**Faculty Bio**
Faculty Picture	Faculty Professional Background
	Boniface Michael, PhD is a Professor of Management and Organizations in the College of Business at California State University, Sacramento. He is the Co-Editor for the Journal of International Education in Business and serves on the Editorial Board for Management and Research Review. He has also served on the Carlsen Center for Innovation and Entrepreneurship’s Board and two terms on Sac State’s Faculty Senate. He earned his PhD in Industrial Relations and Human Resources from the School of Management and Labor Relations at Rutgers University, USA. He also has an MBA from FORE School of Management and an undergraduate degree in Economics from Hindu College, University of Delhi, India.

Funding Source
This work was supported by:	Logos
US Department of Education P031S230256 and P031C210012 *Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation or the US Department of Education.