Graduation Term
Fall 2024
Degree Name
Master of Science (MS)
Department
Department of Technology
Committee Chair
Dr. Borinara Park
Committee Member
Dr. Jaby Mohammed
Committee Member
Dr. Sundeep Inti
Abstract
This study addresses challenges in Discrete Event Simulation (DES) education, where traditional methods focus heavily on theory but lack hands-on, real-world application. To bridge this gap, the research explores using AI, specifically GPT models, to create interactive, accessible learning experiences in DES. By comparing structured and unstructured questioning approaches, the study demonstrates that structured interactions using a Work Breakdown Structure (WBS) produce more accurate, realistic DES models. Findings show that structured AI-driven methods help learners better understand and apply DES concepts, providing a practical pathway from theory to application. This research highlights AI’s potential to transform DES education, supporting diverse learning needs and advancing model quality and engagement. Future directions include expanding AI-driven DES training across various fields to enhance simulation-based learning and operational decision-making.
Access Type
Thesis-Open Access
Recommended Citation
Bhadoriya, Esha, "UNLOCKING SIMULATION MODELING PROFICIENCY: AI AS A KEY TO AUTONOMOUS EXPERTISE DEVELOPMENT" (2024). Theses and Dissertations. 2009.
https://ir.library.illinoisstate.edu/etd/2009