Integrating Contemporary Topics and Methodologies into Experiential Learning for Business Analytics Students

Abstract

This reflection explores the integration of contemporary topics and methodologies into experiential learning for business analytics students at Carnegie Mellon University. It highlights curriculum innovations, including the incorporation of digital twins, collective intelligence, and large language models (LLMs), and describes a novel AI-augmented system for capstone project team formation. The authors also allude to insights from a pilot study on collaborative deliberation methods using swarm intelligence platforms. Key takeaways emphasize the pedagogical value of real-world, data-driven projects and the importance of scaffolding support to address domain complexity and diverse student backgrounds. The work potentially demonstrates how LLMs can enhance both instructional design and educational operations research.