Integrating AI and Simulation for Teaching Power System Dynamics: An Interactive Framework for Engineering Education
Osasumwen Cedric Ogiesoba-Eguakun, Phani Kumar Inkollu, Rupesh Sah, Zia Rashid, Douglas Jussaume, Suman Rath

TL;DR
This paper introduces an AI-driven interactive framework combining simulation and feedback to enhance teaching power system dynamics in electrical engineering education.
Contribution
It presents a novel integrated AI and simulation framework that improves student understanding and engagement through real-time interaction and guided learning.
Findings
Framework enhances student engagement and understanding.
Combines AI explanations with real-time simulation.
Provides a step-by-step guide for educators to implement.
Abstract
Artificial Intelligence (AI), especially cloud platforms and large language models (LLMs), is changing how engineering is taught by making learning more interactive and flexible. However, in electrical engineering and energy systems, students often find power system dynamics difficult to understand because the concepts are abstract, math-heavy, and there are limited opportunities for hands-on practice. This paper presents an AI-based interactive learning framework that combines simulation with intelligent feedback to improve understanding and student engagement. The framework has three connected parts: an AI layer that provides explanations and guidance, a simulation layer that models system behavior, and a user layer that allows students to interact with the system in real time. These parts work together in a continuous loop where students explore how the system behaves, change…
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